The Effects of Mass Incarceration on Communities of Color

Understandably, most of us would expect that removing criminals—those who would victimize others—from a community would be welcomed by the populace, and that both residents and their property would be better off as a result. For most places, that is likely true. Removing a person who has hurt others or who does not respect the property of others is tantamount to removing a thorn from a tender foot. But there is a growing body of evidence that suggest that this may not always be the case, because of the effects that time in prison has on individuals and their home communities. There are collateral consequences that accrue to imprisoned people even after their sentences are completed, and some criminologists believe that when the number of felons removed from a community is “too high,” it may actually harm the places where they use to live. And, since most people who are incarcerated return to the same neighborhoods, or very similar places as those they were removed from, their presence in large numbers, when they go home, adds a substantial burden there, too.

Although the United States has made some progress, it remains a substantially racially segregated nation residentially. And, the country stays very economically segregated as well. It is not surprising that poor people of color have been incarcerated disproportionately during the massive increase in imprisonment that has occurred in the nation since the early 1980s. It is from poor communities of color that a very large number of felons are removed, and to these same neighborhoods that they return when their sentences end. This population churning has been called “coercive mobility” by criminologists. Although it is the intent of legislatures, judges, police, and prosecutors to protect citizens and communities, there is reason to believe that coercive mobility has the unintended consequence of actually increasing crime and victimization.

Some of the changes during this period of increased incarceration that disadvantaged people of color coming into the justice system were implemented with the help and support of African American political leadership, with the express purpose of protecting black and brown communities. Perhaps the best example of this is the initial federal sentences for crack cocaine offenses: conviction for crack selling (more heavily sold and used by people of color) resulting in a sentence 100 times more severe than for selling the same amount of powder cocaine (more heavily sold and used by whites).

A long-running academic debate among criminologists has gone on during this same period about race and justice, the central question being how much of high minority incarceration is a consequence of differential involvement in criminal behavior versus a biased criminal justice system. That debate is not settled. But one factor is pretty much agreed upon: There is overrepresentation of minority group members among those engaging in crime, but even after this is taken into account, people of color are overrepresented in U.S. prisons and jails. The question is how much of the high levels of incarceration of African Americans and Latinos is warranted by higher levels of crime and what proportion is unwarranted. The best research indicates that the answers to these questions should be answered by looking specifically at types of crimes. Among the most serious violent crimes, the evidence suggests that unwarranted racial disparity is modest. For less serious crimes, the proportion of unwarranted racial disparity increases. This can be seen clearly by considering the evidence on drug imprisonments resulting from the war on drugs. Good evidence indicates that racial and ethnic groups use and sell drugs proportionally to their representation in the population; so about 13percent of drug users and sellers are African Americans, about 17 percent are from the various Latino groups, and approximately 65 percent are whites (whites tend to sell to whites; blacks to blacks). But, more than 50 percent of those imprisoned for drug sales or possession are people of color. In fact, one study by the group Human Rights Watch found that black men are sentenced on drug charges at a rate that is more than 13 times higher than white men.

Some observers have claimed that African American and Latino drug dealers are more likely to be arrested because their activities are more likely to occur in open air public drug markets than does the dealing of whites. But at least one study has found that police elect to pursue open air drug markets with minority dealers and ignore those where whites are selling. Overall, the war on drugs has been especially hard on minority individuals and communities, and this cannot be justified by overrepresentation of these groups in this particular form of criminal behavior.

Contrary to what some casual observers might think, residents of African American and Latino communities want crime control, as well as effective and fair policing and a criminal justice system that removes crime perpetrators but that is also accountable to those communities. Popular media reports that focus on the “don’t snitch” norm of some segments of those communities mask important distinctions. First, the belief that a don’t snitch mindset exists in black communities tends to “criminalize” the entire population. This feeds into the historical experience of many law abiding citizens living in these communities that as far as “the system” is concerned, they are all criminals. Most people living in communities of color are law abiding citizens who have little in the way of other housing options. They feel that they are stopped, hassled, and disrespected by police just as often as those who are actually committing crimes. For these folks, there is little incentive to cooperate with a system they believe will ultimately abandon them when a case is over. Second, people in these communities have to live there 24 hours a day, seven days a week. They know that law enforcement won’t be there to protect them forever. They have to live with the very real fear of retaliation from criminals in the community if they cooperate. It is not unusual for witnesses, and even victims, to a crime to refuse to testify or cooperate because they believe that the system will abandon them when a case is over. To the extent that a don’t snitch norm exists, it is primarily observed among some young people in very socially and economically disadvantaged communities. Also, the populations in even the most disadvantaged sections of cities are very heterogeneous with respect to views of police and criminal justice agencies and institutions. Young African Americans who wear “don’t snitch” t-shirts are no more representative of their communities than young whites with multiple piercings and tattoos are of theirs.

Some observers perceive the “black lives matter” movement to include a demand to remove police from black neighborhoods. Nothing could be further from the truth. That movement is calling for effective and accountable policing. So when serious criminals—those who victimize and terrorize black and brown communities—are arrested, convicted, and imprisoned, there are multiple responses in the places where they lived and, more often than not, engaged in their predatory behavior. There may be those who see and lament “another brother oppressed by the man, but the vast majority of people who live there will be pleased that someone who hurt and victimized others is, at least for a time, no longer roaming their streets free to wreak more havoc.

Problems with the “solutions”

As is the case for every community, when criminals are removed from socially and economically disadvantaged African American and Latino communities, there is a benefit to those places. Not only is a person who would victimize others not able to do so, but crime, especially high levels of crime, are bad for the collective good of communities. Crime can destabilize neighborhoods. When people live in fear of personal or property victimization, they view their environment as a threatening, scary place. Such spaces do not promote the kind of cohesion and closeness among neighbors that is important for healthy and productive social engagement. When residential areas, and even commercial districts, are cohesive and individuals are engaged with each other, people can participate in the kinds of social life that make crime less likely. So, too much crime actually increases the likelihood of more crime.

What some criminologists fear is that going too far in the opposite direction—with the criminal justice system removing too many residents from a neighborhood—potentially causes two separate but related types of problems. With incarceration there is collateral damage to those locked up, as well as to those who they are connected to: partners, children, extended family, and any positive friendship networks they had. Also, and perhaps less obvious, removing too many people from a troubled neighborhood can have a detrimental, crime-causing effect.

The overwhelming majority of inmates will be released from prison after serving their sentences, and the nation has struggled with how to help them reenter society. Generally, released prisoners must return to the county where they last lived, which, for most, means returning to a poor and socially isolated inner-city neighborhood or community. The unprecedented numbers now being released have compounded the problem. Many prisoners entered the system with drug, alcohol, or mental problems. In the vast majority of instances, they received little or no treatment or counseling during their incarceration because of reduced funding for rehabilitation programs as well as the closing or scaling back of state mental facilities. Prisons, and even jails, have become the dumping grounds of necessity for those who have mental health issues. On another level, general health care within prisons, including mental health care, has been woefully inadequate, resulting in a number of lawsuits against both federal and state corrections systems. Unfortunately, this means that prisoners released back into their old communities return no better off—or, in many instances, worse off—than they were before being incarcerated.

In addition, released prisoners face collateral consequences that they were largely unaware of at the time they were originally sentenced. Collateral consequences to the imprisoned are the effects that remain after the formal sentence has been served. These damages are inflicted by law and by social practice. Among the former, some of the more onerous consequences are the legal denial of some social benefits—public housing access, welfare benefits, some college loans and grants, the right to vote, the right to live or work in certain places (school zones for some offenders), and requirements to register with local authorities. These damages were enacted by legislative bodies to punish those convicted of crimes, in the belief that those who violate “the social contract” should not benefit from the public’s largess, or in the belief that barring convicted felons from some of the things that others have access to is for the good of the broader community. But, not having access to these “privileges” will inhibit some who have been released from prison from taking the straight, narrow, and legitimate path, and thus increase the likelihood of them becoming again involved in criminal behavior. In addition to legally specified collateral consequences of felony convictions (and in some jurisdictions some misdemeanor convictions), there are informal consequences as well. Those who are convicted frequently lose intimate relationships with partners or access to their children, and they are less likely to find employment. Significantly, these consequences accrue even among inmates who do not spend long sentences in “the big house.”

There are also collateral damages to the families of those imprisoned, both while they are locked up and when they are released. One study, for example, found that the financial and time strain on the wives and girlfriends of inmates in upstate New York prisons imperiled relationships with both the women in prisoners’ lives and their children. Since families are a good anchor for prisoners when they are released, disruptions in family life increase the chances of recidivism. Another study comparing neighborhoods with high and low rates of incarceration, found that in the former, the gender ratio is sufficiently thrown off by the number of men going into and coming out of prison that marriage markets are negatively affected.

It has long been known that adding too many new residents to cities and neighborhoods can have a “criminogenic” effect, because when there are more new faces, when there are ever changing faces, the integration of new arrivals into the community is inhibited, allowing greater individual anonymity. Such circumstances create fertile ground for crime to occur and perhaps flourish. To be clear, this does not mean that migrants bring crime with them. In fact, the evidence has long suggested that movers have less of the characteristics that are predictive of criminal behavior. The problem is the lack of social integration. Similarly, when communities lose too large of a segment of their population, this same important, crime-inhibiting social integration can be disrupted. It is important to remember that even people who break the law occupy many different roles. They are husbands or wives or girlfriends or boyfriends, sons, daughters, friends, coworkers, and neighbors. Families and the neighborhoods in which they reside struggle to fill the void when members are no longer there. The removal of too many people from communities can be disruptive. The nation has seen this in recent years when sections of formerly industrial capitals, such as Detroit, Cleveland, St. Louis, and Pittsburgh, have lost population as people left in search of jobs. Some criminologists believe that when people from a community are imprisoned at a high enough number—coercive mobility—the effect may also be criminogenic.

So there are two countervailing forces or arguments: that removing problem criminal people improves the life of neighborhoods, and that removing too many people and then returning them can be criminogenic. The two most prominent researchers who have made the case regarding coercive mobility and its deleterious effects are Dina Rose and Todd Clear. They believe that there is a tipping point, below which imprisonment is normally good for a community, but above which it becomes criminogenic. This effect, coercive mobility leading to crime, is not thought to happen everywhere, but in severely socially and economically disadvantaged places. This is, in part, because a large amount of serious crime occurs there, but also because such places have very limited resources and do not have the collective resiliency to overcome high levels of imprisonment and large numbers of released men and women returning to the same problematic neighborhoods from which they came, or ones very much like them.

An important way to address the problems for communities of color is to reduce the residential racial and economic segregation that continues to cause problems for social life in the U.S.

Before considering the evidence for coercive mobility’s effects on communities, one more very important negative force should be highlighted: the diminished state—human capital, in the words of sociologists—of most returning former prisoners. It is generally accepted that having a good, solid family life lowers the probability of a person becoming involved in crime, and that having employment (especially good employment) does the same. Predictably, those most likely to be sentenced to a term in prison are less likely than others of their age, race, and gender to be involved in a stable relationship or to have been employed in a high-quality job prior to their incarceration. When men and women return from prison, their family life has an even higher likelihood of having been disrupted, and their competitiveness on the job market is even more diminished than it was before they were incarcerated. Time in prison means that these already marginal people are more marginalized, and they tend to return to living in neighborhoods that are already distressed by the presence of too many disrupted families and high levels of joblessness. They add to the already overcrowded pool of residents likely to not be in good relationships, to not be good prospects as mates, and to be not competitive for the desirable good jobs that will help them stay out of jail or prison and might help their community’s dismal economic state.

Which brings things back to the coercive mobility argument, as it may be critically important. If its proponents are correct, the very effort to reduce crime in some of the nation’s highest crime communities is doing the opposite in the context of mass incarceration. As a consequence, the National Research Council (NRC) committee charged with studying the causes and consequences of high rates of imprisonment took some time to evaluate the evidence for and against this thesis. The evidence is not conclusive, but it is suggestive. As observed in cities across the country, incarceration is very concentrated geographically.

In addition, the evidence indicates that, indeed, the places that released prisoners return to are just as geographically concentrated in other ways, as shown by comparison of the racial and ethnic composition of high-incarceration neighborhoods with the rest of the city, and the poverty rates for these communities and the city as a whole. The areas of concentrated incarceration are in predominately minority districts. This is the case in cities throughout the United States. The committee also found strong evidence that these places are among the most economically and socially disadvantaged sections of U.S. cities.

Thus, there is little doubt about this portion of the argument: prisoners come from and return to a narrow group of neighborhoods, very disadvantaged ones. Two other aspects of the coercive mobility argument are less clear.

First, there is some evidence that this concentration pattern is criminogenic, but other researchers have not found evidence that this pattern increases crime above and beyond what would generally be expected for similar neighborhoods. The strongest evidence for the argument has been presented by Rose and Clear in “Incarceration, Social Capital and Crime: Examining the Unintended Consequences of Incarceration,” based on their work in Tallahassee, Florida, and published in the journal Criminology in 1998, and in Clear’s review of research in his book Imprisoning Communities, published in 2007. Some additional research has also provided support. The strongest evidence to the contrary comes from several studies conducted by James Lynch and William Sabol in Baltimore, which yielded mixed evidence, but could not confirm the idea that incarceration was increasing crime rates in some of the city’s neighborhoods.

Second, critical to this notion is that there is a tipping point below which incarceration benefits communities, but above which high levels of coercive mobility increases crime rates. The research evidence does indicate that there is a nonlinear relationship between imprisonment and crime, which suggests that there is such a tipping point, but criminologists to date have not been able to settle on where that tipping point is.

After considering the evidence, the NRC committee concluded that it did not allow for affirmation that high levels of imprisonment cause crime in these neighborhoods. Interestingly, the committee reported that an analytically major problem for examining this thesis is that it is too hard—indeed, virtually impossible—to find enough white neighborhoods with the same levels of either imprisonment or disadvantage that exists routinely in many African American communities in nearly every major American city to allow for meaningful analysis. Cities in the United States are still far too racially segregated to make the analytic comparisons that are necessary, and the minority neighborhoods are where the disadvantaged are concentrated and from where prisoners are disproportionally drawn. So, although the committee could not affirm that high levels of incarceration increases crime in disadvantaged minority neighborhoods, it did find that the quantitative evidence is suggestive of that pattern. And a number of ethnographers—who have been spending time in these communities and watching how families, friendship networks, and communities are faring—are adding additional evidence that indicates that high levels of imprisonment, concentrated in disadvantaged communities of color, are indeed criminogenic.

Researchers are increasingly finding that both the collateral consequences of imprisonment, and living in communities from which many of the imprisoned come from and return to, do have detrimental effects. And these effects are visited upon the reentering individual, on their families, and on the communities at large. Reentering former inmates’ chances of success and reduced probability of recidivism are enhanced if they are returning to healthy families and can find decent employment. It has been well established that men, whether or not they have been to prison, are less likely to be involved in crime if they are in stable intimate relationships, employed gainfully, and living in decent housing. And for those returning from prison, those who establish these life patterns are more likely to have successful reentry to their communities. Importantly, a large proportion of men being released from prison hopes to and expects to live with their children. But families and children are negatively affected when parents go into prison, as well as when they return.

Unfortunately, in places characterized by high levels of incarceration, there are additional challenges. Studies of the effects of high incarceration rates in neighborhoods in Oakland have found that important institutions—families and schools, as well as businesses and criminal justice personnel, such as police and parole officers—have become reconfigured to focus on marginalized young boys, increasing the chances that they become more marginalized and involved in crime. Other studies in similar places in Philadelphia have also found that high levels of imprisonment undermined familial, employment, and community relationships, increasing the likelihood of criminal involvement. Additionally, researchers in San Francisco, St. Louis, Seattle, and Washington, D.C., have found that housing, family relationships, marriage, and successful reentry after prison appear to be negatively influenced by high neighborhood levels of incarceration.

Substantial policy changes that create more robust state efforts to support individuals during reentry will not only help them, but their families and the places they return to as well.

More ominously, evidence indicates that these patterns likely have a vicious intergenerational cycle. Children of individuals who have been imprisoned have reduced educational attainment, which obviously bodes ill for their future economic competitiveness. This means that in places with high levels of incarceration, this practice is contributing to another generation that has a heightened likelihood of living in disadvantaged communities. Additionally, researchers have found that judges are more likely to sentence children who come before the juvenile court more harshly if they come from disadvantaged neighborhoods than from more stable communities—yet again continuing the cycle of people moving from disadvantaged places to prison, which makes those neighborhoods more marginalized, which then increases the likelihood of the state removing more people, both juveniles and adults, into the corrections system.

What can be done?

There is an obvious and very straightforward answer to the policy question of how to confront the negative effects of mass incarceration—and that is to reduce it. Mass incarceration did not come about because of substantial increases in crime, but rather because of a set of policy choices that the nation has made. The same simple answer will address the policy question of how to confront the negative impact of mass incarceration on communities of color. Taking this step—reducing mass incarceration—will have profound effects on these communities, because they have disproportionally suffered from the increases in incarceration. And for anyone who may worry, there is no evidence to suggest that a move away from the high level of imprisonment, which characterizes the United States more than any other nation in the world, will result in a substantial increase in crime.

Another important way to address the problems for communities of color is to reduce the residential racial and economic segregation that continues to cause problems for social life in the United States. Admittedly, aiming for this goal will place greater challenges on policymakers and the public alike.

The good news is that there are efforts under way that, if moved forward, would mitigate some of the problems caused by the collateral consequences from imprisonment and some of the negative effects of coercive mobility on communities of color. In 2010, the National Conference of Commissioners on Uniform State Laws proposed the Uniform Collateral Consequences of Criminal Convictions Act, model legislation that might be adopted by the states. If passed, bills such as this would mandate that defendants be advised of all of the collateral consequences that formally accompany felony convictions at the time of sentencing and how they might be mitigated. Currently, courts have no obligation to advise defendants as to these collateral consequences because they are deemed to be “sanctions” rather than punishment. Furthermore, most criminal defense lawyers themselves do not know about or understand the range of collateral consequences that their clients face. In 2013, the National Association of Criminal Defense Lawyers released a book titled Collateral Consequences of Criminal Convictions: Law, Policy and Practice, written by Margaret Colgate Love, Jenny Roberts, and Cecelia Klingele and published jointly with Thomson Reuters Westlaw. It is described as “a comprehensive resource for practicing civil and criminal lawyers, judges and policymakers on the legal restrictions and penalties that result from a criminal conviction over and above the court-imposed sentence.” Yet, today, most defendants have no idea of the added consequences they will face upon release from incarceration.

It is hoped that discussions around the proposed Uniform Collateral Consequences of Criminal Convictions Act would have the collateral benefit of pressing policymakers to seek out means by which they might mitigate the negative consequences. Since the majority of convictions are the result of plea agreements, defendants might be better informed of the consequences of their decisions. To date, several states, including Vermont, New York, Maryland, and Oregon, as well as the U.S. Virgin Islands, have either enacted or introduced bills that contain elements of the model bill.

States may also elect to opt out of some of the federally mandated collateral consequences for some convictions. For instance, people convicted of drug offenses are, according to federal law, not permitted to receive some “welfare benefits,” or to live in federally subsidized housing. This is especially problematic for the families of the convicted, because they are then faced with the choice of receiving these benefits or turning away from the stigmatized family member. The latter option is hard on the maintenance of families and removes from the formerly incarcerated important support systems that enable successful reentry. States are permitted by Congress to opt out of these penalties, but their legislatures need to formally affirmatively enact laws to not have those sanctions applied in their state.

Before federal and state lawmakers decided to get tough on crime by increasing sentencing, most jurisdictions had more robust community services providers for returning prisoners. They were called parole officers. The role of these agents varied from place to place; some of the agents emphasized the police and enforcement aspects of the job, but others emphasized their roles to assist with what is now called reentry. Unfortunately, with the elimination of parole in some states, restrictions on it elsewhere, and declines in budgets for these services, too few people are charged with the responsibility to aid in the reentry process. This is a problem for both the returning individuals and for their families and communities. For example, now that the state of Washington has legalized the recreational use of marijuana, the state is in the process of releasing inmates currently held for possession convictions. One of the young men about to be released told a visiting academic researcher that he was worried because he had no home to return to, no job, and few prospects to help him when he stepped out of the prison door. As far as he knew, the state would not be providing him with reentry assistance. Both the negative effects of imprisonment to individuals and to high-incarceration communities can be mitigated if those returning are aided by having stable housing, their families are supported, and they are assisted in finding and holding employment. Although there were problems with the old sentencing practices and with parole, it was never the case that those systems did not perform important positive functions. Substantial policy changes that create more robust state efforts to support individuals during reentry will not only help them, but their families and, if the coercive mobility thesis is correct, the places they return to as well.

It may be tempting to suggest that those released not be allowed to move back to the communities they lived in when they got into trouble. But the simple truth is that most released prisoners have no place to go other than the communities they know. That is where their families and the people they know are. The likely outcome of such relocation policies would be less successful reentry and greater recidivism. For example, restrictions in some states on where sex offenders can live has led to increased homelessness in this population, making the task of keeping tabs on them more difficult for officials.

Ultimately, the best way to reduce the collateral consequences and the criminogenic effects of high rates of incarceration and their subsequent negative effects for communities of color is to reduce the number of people going into prisons and to create a more just society. On the first front, President Barack Obama recently commuted the sentences of 46 men and women who were serving federal prison time for nonviolent drug offenses, saying: “These men and women were not hardened criminals. But the overwhelming majority had been sentenced to at least 20 years; 14 of them had been sentenced to life for nonviolent drug offenses, so their punishments didn’t fit the crime.” These and other overly punitive sentences neither serve justice nor protect communities.

It is also clear that continued racial residential segregation exacerbates existing inequalities and fosters severe social and economic disadvantage. More robust enforcement of federal and state fair housing laws will reduce the disparity between minority and majority crime rates. Such action, along with eliminating society’s over use of prisons to confront social problems, will substantially reduce the effects of the collateral consequences from incarceration and coercive mobility on communities of color.

Jailhouse Rot

Americans seem to have a thing for prisons. Not only do we have the world’s largest prison population, we have a rich and incongruous pop culture heritage of films and songs about prison life. On film from Cool Hand Luke to Jailhouse Rock, from Shawshank Redemption to Orange Is the New Black. In song from the traditional “Midnight Special” to Snoop Dogg’s “Murder Was the Case,” with side trips to Merle Haggard’s “Life in Prison,” Sam Cooke’s “Chain Gang,” and Johnny Cash’s “Folsom Prison Blues.” The result is that many of us have vivid but completely inaccurate images of prison. Perhaps it’s not surprising, then, that we also have incarceration policies founded on myths and misunderstanding.

A recent National Academies report, The Growth of Incarceration in the United States, seeks to establish the facts about how incarceration policies have evolved in recent decades and what social science research can tell us about the effectiveness of these policies in deterring crime, rehabilitating prisoners, and making our neighborhoods safer and more livable. The extent of the changes in recent years is shocking. Even more disturbing is the absence of social science research or clearly stated normative principles to justify the new incarceration policies.

The report comes at an opportune time. After a long period during which politicians from both parties eagerly presented themselves as “tough on crime,” a recent bipartisan groundswell has begun to reconsider incarceration policies. The push for reform emerges from a diverse mix of rationales and a variety of ideological perspectives, which makes for a shaky coalition. This report provides the social science research and guiding principles that could unite these varied perspectives and create a foundation for sensible bipartisan incarceration reform.

From 1973 to 2009, U.S. state and federal prison populations rose from about 200,000 to 1.5 million; it declined slightly in the following four years largely because of reductions in state prison populations. An additional 700,000 men and women are being held in local jails. With only 5% of the world’s population, the United States has close to 25% of the world’s prisoners. Its incarceration rate is five to 10 times higher than rates in Western Europe and other democracies.

And of course there are further disparities within the U.S. system. Long and often mandatory prison sentences, as well as intensified enforcement of drug laws, contributed not only to overall high rates of incarceration, but also especially to extraordinary rates of incarceration of African Americans and Hispanics, who now comprise more than half of our prisoners. In 2010, the incarceration rate for African Americans was six times and for Hispanics three times that of non-Hispanic whites. And although there is no significant difference in the prevalence of illegal drug use in the white and minority communities, African Americans and Hispanics are far more likely to be arrested and to serve prison time for drug offenses.

The growth in the U.S. prison population is not a result of an increase in crime, but of a change in incarceration policy. A wave of concern about preserving social order swept the country in the late 1960s and early 1970s. One manifestation of this anxiety was that officials at all levels of government began implementing new policies, such as requiring prison time for lesser offenses, increasing the recommended sentences for violent crimes and for repeat offenders, and taking a much more aggressive approach to the sale and use of illegal drugs, particularly in urban areas. The trend continued into the 1980s. Federal and state legislatures enacted “three strikes and you’re out” laws and “truth in sentencing” provisions.

As the impact of changes in incarceration policy became apparent, social scientists began studies to determine if new policies were achieving their desired effect. The Growth of Incarceration study committee reviewed this research and reached the following consensus: “The incremental deterrent effect of increases in lengthy prison sentences is modest at best. Because recidivism rates decline markedly with age, lengthy prison sentences, unless they specifically target very high-rate or extremely dangerous offenders, are an inefficient approach to preventing crime by incapacitation.”

Social science and health researchers also examined the effects of incarceration on the physical and mental health of prisoners and on the stability and well-being of the communities from which prisoners came and to which they usually returned. For those who are imprisoned, “Research has found overcrowding, particularly when it persists at high levels, to be associated with a range of poor consequences for health and behavior and an increased risk of suicide. In many cases, prison provides far less medical care and rehabilitative programming than is needed.” The detrimental effects for families and children can be deduced from one shocking and tragic statistic: “From 1980 to 2000, the number of children with incarcerated fathers increased from about 350,000 to 2.1 million—about 3% of all U.S. children.”

Although the report emphasized the importance of heeding social science research and the need for more study, it also noted that scientific evidence cannot be the only factor guiding incarceration policy. It concluded: “The decision to deprive another human being of his or her liberty is, at root, anchored in beliefs about the relationship between the individual and society and the role of criminal sanctions in preserving the social compact. Thus, sound policies on crime and incarceration will reflect a combination of science and fundamental principles.” The committee proposed four principles that could light the way to a more humane and effective incarceration policy: “1) proportionality of offense to criminal sentences; 2) parsimony in sentence length to minimize the overuse of prison time; 3) citizenship so that the conditions and severity of punishment should not violate fundamental civil rights; and 4) social justice in which prisons do not undermine society’s aspirations for fairness.”

The committee did not presume to propose a detailed blueprint for a new incarceration policy. The system of federal, state, and local policies is too complex for any cookie-cutter remedy. Instead, it urged all responsible officials to reconsider the human, social, and economic costs of their incarceration policies in light of their modest crime-prevention effects and to consider reforms that are informed by social science research and guided by clearly stated principles.

The four articles that follow build on the findings and recommendations of The Growth of Incarceration, but in each case the authors go further in understanding particular aspects of incarceration and proposing ways to improve the performance of the system. These articles should serve as a catalyst for a local, state, and national effort to act on the report’s recommendations. Policymakers are recognizing the need for reform of a justice system that is often unjust, and these articles can help them identify the most pressing problems and most promising solutions.

CRISPR Democracy: Gene Editing and the Need for Inclusive Deliberation

Not since the early, heady days of recombinant DNA (rDNA) has a technique of molecular biology so gripped the scientific imagination as the CRISPR-Cas9 method of gene editing. Its promises are similar to those of rDNA, which radically transformed the economic and social practices of biotechnology in the mid-1970s. Ivory tower rDNA science morphed into a multibillion dollar technological enterprise built on individual entrepreneurship, venture capital, start-ups, and wide-ranging university-industry collaborations. But gene editing seems even more immediate and exciting in its promises. If rDNA techniques rewrote the book of life, making entire genomes readable, then CRISPR applies an editorial eye to the resulting book, searching for typos and other infelicities that mar the basic text. Gene editing shows many signs of being cheaper, faster, more accurate, and more widely applicable than older rDNA techniques because of its ability to cut and alter the DNA of any species at almost any genomic site with ease and precision.

Since their development, gene editing techniques have been used for many purposes: improving bacterial strains used in dairy products, making new animals for research, and experimenting with knocking out disease-inducing mutations in human genes. Some of these uses are already producing commercial benefits while others remain distinctly futuristic. Uncertainty, however, has not deterred speculation or hope. To many it appears all but certain that so precise and powerful a technique will revolutionize the treatment of genetically transmitted human disease, correcting defective genes within diseased bodies, and potentially banishing genetic errors from the germ-line by editing the DNA of human gametes and embryos. Some researchers have already initiated experiments on human gametes and embryos to develop techniques for this purpose.

Hope is understandable. Up to 10% of the U.S. population is estimated to carry traits for one or another rare genetic disease. The consequences for individuals and families may be tragic, as well as economically and psychologically devastating. Our moral intuition rebels against pointless suffering. Any discovery that serves medicine’s ethical mandate to help the sick therefore generates immense pressure to move quickly from labs into bodies.

These established, socially approved ways of thinking explain the air of inevitability surrounding CRISPR’s application to germline gene editing. In Craig Venter’s words “the question is when, not if.” Human curiosity and ingenuity have discovered a simple, effective means to snip out nature’s mistakes from the grammar of the human genome, and to substitute correct sequences for incorrect ones. It seems only logical, then, that the technique should be applied as soon as possible to those dealt losing hands in life’s lottery. Yet, as with all narratives of progress through science and technology, this one carries provisos and reservations. On closer inspection, it turns out to be anything but simple to decide how far we should go in researching and applying CRISPR to the human germline. CRISPR raises basic questions about the rightful place of science in governing the future in democratic societies.

Recapitulating the rDNA story, prominent biologists have been among the first to call for restraint. In March 2015, a group, including such luminaries as Nobel laureates David Baltimore of Caltech and Paul Berg of Stanford, proposed a worldwide moratorium on altering the genome to produce changes that could be passed on to future generations. In May, the U.S. National Academy of Sciences (NAS) and National Academy of Medicine (NAM) announced their intention to hold an “international summit” later this year “to convene researchers and other experts to explore the scientific, ethical, legal, and policy issues associated with human gene-editing research.” The NAS-NAM plan also calls for a “multidisciplinary, international committee” to undertake a comprehensive study of gene editing’s scientific underpinnings and its ethical, legal, and social implications.

That leading scientists should call for responsible research is wholly laudable. But the human genome is not the property of any particular culture, nation, or region; still less is it the property of science alone. It belongs equally to every member of our species, and decisions about how far we should go in tinkering with it have to be accountable to humanity as a whole. How might a U.S. or international summit on gene editing attempt to meet that heavy responsibility?

Thus far, one historical experience has dominated scientists’ imaginations about the right way to proceed, an experience that takes its name like many ground-breaking diplomatic accords from a meeting place. The place is Asilomar, the famed California conference center where in 1975 some of the same biologists now proposing a moratorium on germline gene editing met to recommend guidelines for rDNA experimentation. In the eyes of Paul Berg, one of its chief organizers, this too was a meeting that changed the world. Writing in Nature in 2008, he portrayed Asilomar as a brilliant success that paved the way for “geneticists to push research to its limits without endangering public health.”

That description, however, points to the dangers of using Asilomar as a model for dealing with CRISPR. It implies that geneticists have a right to “push research to its limits” and that restraint is warranted only where the research entails technically defined risks like “endangering public health.” But both notions are flawed. We argue here that an uncritical application of the Asilomar model to CRISPR would do a disservice to history as well as democracy.

Asilomar shows how under the guise of responsible self-regulation science steps in to shape the forms of governance that societies are allowed to consider. As a first step, questions are narrowed to the risks that scientists know best, thereby demanding that wider publics defer to scientists’ understandings of what is at stake. Even where there are calls for “broad public dialogue,” these are constrained by expert accounts of what is proper (and not proper) to talk about in ensuing deliberations. When larger questions arise, as they often do, dissent is dismissed as evidence that publics just do not get the science. But studies of technical controversies have repeatedly shown that public opposition reflects not technical misunderstanding but different ideas from those of experts about how to live well with emerging technologies. The impulse to dismiss public views as simply ill-informed is not only itself ill-informed, but is problematic because it deprives society of the freedom to decide what forms of progress are culturally and morally acceptable. Instead of looking backward to a mythic construct that we would call “Asilomar-in-memory,” future deliberations on CRISPR should actively rethink the relationship between science and democracy. That reflection, we suggest, should take note of four themes that would help steer study and deliberation in more democratic directions: envisioning futures, distribution, trust, and provisionality.

Whose futures?

Science and technology not only improve lives but shape our expectations, and eventually our experiences, of how lives ought to be lived. In these respects, science and technology govern lives as surely as law does, empowering some forms of life and making them natural while others, by comparison, come to seem deficient or unnatural. For example, contraception and assisted reproduction liberated women from the natural cycles of childbirth and enabled a degree of economic and social independence unthinkable just a half-century ago. But increased autonomy in these domains necessarily changed the meaning and even the economic viability of some previously normal choices, such as decisions to have many children or simply “stay home.” Similarly, the digital era vastly increased the number of “friends” one can call one’s own, but it curtailed leisure and privacy in ways that brought new demands for protection, such as employee rights not to answer email after hours, for instance in France and Germany, and the rights of individuals now recognized in European law to demand the erasure of their outdated digital footprints in search engines like Google. Prenatal genetic testing enabled parents to prevent the birth of seriously ill children but made disability rights groups anxious that members would be stigmatized as accidents who should never have been born.

The research community acknowledges the unfair distribution of health resources but tends to shrug it off as someone else’s business.

As in moments of lawmaking or constitutional change, the emergence of a far-reaching technology like CRISPR is a time when society takes stock of alternative imaginable futures and decides which ones are worth pursuing and which ones should be regulated, or even prevented. Asilomar represented for the molecular biology community just such a moment of envisioning. The eminent scientists who organized the meeting rightly recognized that at stake was the governance of genetic engineering. How should the balance be struck between science’s desire to push research to the limits on a new set of techniques with extraordinary potential, and society’s possibly countervailing interests in protecting public health, safety, and social values? Intelligence, expertise, a strong sense of social responsibility—all were amply represented at Asilomar. What was in shorter supply, however, was a diversity of viewpoints, both lay and expert.

To molecular biologists flushed with the excitement of snipping and splicing DNA, it seemed obvious that rDNA research should continue without what they saw as ill-advised political restrictions. Many scientists regarded this as “academic freedom,” a constitutionally guaranteed right to pursue research so long as inquiry harms no one. The primary risk, Asilomar participants believed, was that dangerous organisms might be accidentally released from the lab environment, injuring humans or ecosystems. What would happen, they asked, if a genetically engineered bacterium containing a cancer-causing gene escaped and colonized the human gut? To prevent such unwanted and potentially grave errors, the scientists adopted the principle of containment, a system of physical and biological controls to keep harmful organisms safely enclosed inside the experimental spaces where they were being made. Public health would not be risked and research would continue. The Reagan administration’s subsequent decision to use a coordinated framework of existing laws to regulate the products, but not the process, of genetic engineering reflected this end-of-pipe framing of risks. Upstream research remained virtually free from oversight beyond the narrow parameters of laboratory containment. This is the science-friendly settlement that Paul Berg celebrated in his Nature article and that the National Academies have invoked as a guiding precedent for the upcoming summit on gene editing.

A full accounting of the Asilomar rDNA conference, however, highlights not the prescience of the scientists but the narrow imagination of risk that their “summit” adopted. The focus on containment within the lab failed to foresee the breadth and intensity of the debates that would erupt, especially outside the United States, when genetically modified (GM) crops were released for commercial use. U.S. policymakers came to accept as an article of faith that GM crops are safe, as proved by decades of widespread use in food and feed. Ecologists and farmers around in the world, however, observed that Asilomar did not even consider the question of deliberate release of GM organisms outside the lab because the assembled scientists felt they could not reliably assess or manage those risks. As a result, when agricultural introductions were approved in the United States, with little further deliberation or public notice, activists had to sue to secure compliance with existing legal mandates, such as the need for an environmental impact statement.

If the Asilomar scientists’ imagination of risk was circumscribed, so too were their views of the forms and modes of deliberation that are appropriate for the democratic governance of technology. Understandably, given the United States’ lead in rDNA work, American voices dominated at the scientists’ meeting, with a sprinkling of representatives from Europe and none from the developing world. Questions about biosecurity and ethics were explicitly excluded from the agenda. Ecological questions, such as long-term effects on biodiversity or non-target species, received barely a nod. The differences between research at the lab scale and development at industrial scales did not enter the discussion, let alone questions about intellectual property or eventual impacts on farmers, consumers, crop diversity, and food security around the world. Yet, those emerged as points of bitter contestation, turning GM crops into a paradigm case of how not to handle the introduction of a revolutionary new technology. In retrospect, one can see the long, at times tragic, controversy over GM crops—marked by research plot destructions, boycotts and consumer rebellion, import restrictions against U.S. crops, a World Trade Organization case, a global movement against Monsanto—as a reopening by global citizens of all the dimensions of genetic engineering that Asilomar had excluded.

Biomedicine achieved greater political acceptance in the intervening decades than agricultural biotechnology, but even here the record is ambiguous. As we will discuss, the political economy of drug development, an issue that even scientists with substantial commercial interests typically regard as lying outside their remit, remains highly controversial. Specific public worries include the ethics of transnational clinical trials, access to essential medicines, and intellectual property laws that discriminate against generic drugs produced in developing countries.

Given these demonstrable gaps between what scientists deliberated in 1975 and what the world has seen fit to deliberate in the 40 years since, it is the myth of Asilomar as the “meeting that changed the world” that warrants revisiting.

Whose risks?

In biomedical research, the notion that scientists should “push research to its limits” reflects not only the desire to satisfy curiosity but the hope that progress in knowledge will produce victories against disease. Given its power and versatility, there is plenty of speculation that CRISPR might be not just any therapy, with hit or miss qualities, but a magic bullet for generating customized gene and cell therapies, more targeted treatments, and, most provocatively, direct editing out of disease-causing genes in human embryos. These visions are not unlike several that preceded them, for instance with embryonic stem cell research, gene therapy, rDNA, and others. As with these precursors, imaginations of the technique’s therapeutic potential—and thus the imperative to proceed with research—eclipsed the complexities of biomedicine in practice. Although CRISPR might produce treatments, people will benefit from them only if their ailments are the ones treated and only if they have adequate access to therapies. Access, in turn, depends in important respects upon the political economy of innovation. Thirty-five years after Genentech produced recombinant insulin, the first major biomedical payoff of rDNA, insulin remains an expensive drug. Its cost keeps it out of reach for some Americans, with disastrous implications for their health. A therapeutic as complex as CRISPR gene therapy with multiple macromolecular components (protein, RNA, and delivery agents) is likely to be engineered and reformulated for decades to come to maximize safety and efficacy. That process, in turn, may generate a succession of “evergreening” patents and limit the immediate benefits to those with the resources to afford them.

The research community acknowledges the unfair distribution of health resources but tends to shrug it off as someone else’s business. Science, after all, should not be burdened with solving complex political and economic problems. The social contract between society and science, as encapsulated in Vannevar Bush’s metaphor of the endless frontier, calls on science only to deliver new knowledge. Yet the commercial aspirations of twenty-first century normal science play no small part in sustaining the very political economy of invention that gives rise to distributive inequity. These days it is expected (and indeed required by law) that publicly funded discoveries with economic potential should be commercialized: science, in this view, best serves the public good by bringing goods to market. CRISPR is no exception. A patent battle is taking shape between the University of California, Berkeley and the Broad Institute, with predictions that upward of a billion dollars in royalties are at stake. With such forces in play, “pushing research to its limits” easily translates into pushing biomedicine’s commercial potential to its limits, meaning, in practice, that urgent needs of poor patients and overall public health may get sidelined in favor of developing non-essential treatments for affluent patients. Under these circumstances, it is hard not to read defenses of scientific autonomy and academic freedom as defenses of the freedom of the marketplace. Both freedoms are rooted in the same disparities of wealth and resources that separate the health expectations of the poor from those of the rich.

The apparent inevitability of CRISPR applications to editing embryos takes for granted the entire economics of biomedical innovation, with the assumption that the push to commercialize is by definition a universal good. These arrangements, however, are not natural expressions of the market’s invisible hand. They grow out of specific political and legal choices whose consequences have typically not been revisited in the decades since they were made, even where mechanisms exist to do so. The National Institutes of Health (NIH), for instance, retains march-in rights for intellectual property produced with its support, but it has never seen fit to exercise them, even where pushing profits to the limit has compromised access to therapeutics with detrimental effects on public health. In contrast, many developing countries initially exempted pharmaceutical drugs from patent protection on the belief that access to health should not be limited by commercial interests—an exemption eliminated by the 1994 Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS).

Good governance in a complex world does require accommodation of private interests, and democracies have struggled to insulate governance from undue influence by the power of money. CRISPR and its biotechnological predecessors exemplify cases where it is especially hard for democratic processes to strike the balance between public good and private benefit. For here, as already noted, delegating to experts the right to assess risk strips away many features of the social context that shape technologies and eventually give rise to disparities in health and health care access. Scientists at the frontiers of invention do not see it as their responsibility to address even the most obvious equity issues, such as whose illnesses are targeted for intervention or when money should be directed from high-cost individualized treatment to lower-cost public health interventions. As technologies come to market without prior collective assessment of their distributive implications, it is the potential users of those technologies who will have to confront these questions. Limiting early deliberation to narrowly technical constructions of risk permits science to define the harms and benefits of interest, leaving little opportunity for publics to deliberate on which imaginations need widening, and which patterns of winning and losing must be brought into view.

Trust

The leaders of the research community recognize that trust is essential in securing public support for any recommendations on how to handle CRISPR, including rules for the manipulation of germline cells. The NAS-NAM proposal seeks to build trust on three levels: (1) by invoking the National Academies’, and more generally science’s, prior achievements in consensus-building; (2) by reaching out to stakeholders in accordance with principles of pluralist democracy; and (3) by constructing a multilayered institutional structure for decision making. In important ways, however, these proposals misremember history, misconceive the role of participation, and misunderstand the relationship between expertise and democracy.

Looking back on the history of rDNA policy, it is crucial to remember that public trust was not cemented at Asilomar. It took years, even decades, to build anything like a consensus on how genetic and genomic developments affecting biomedicine should be governed, even in the United States. Indeed, many would say that trust-building is still a work in progress. Democratic demands soon forced the scientific community to open up its deliberations on rDNA to a wider public than had been invited to Asilomar. Publics and policymakers responded to Asilomar with skepticism for having neglected their concerns. As Senator Edward M. Kennedy put it, the Asilomar scientists “were making public policy. And they were making it in private.” Not only were the recommendations produced by those who stood to gain the most from a permissive regime, but the conference failed to entertain questions that mattered most to the wider public. Facing the threat of legislation, the scientific community sought to appease such criticisms, for instance, by adding a handful of public interest representatives to the Recombinant DNA Advisory Committee (RAC) of the NIH. Whether such token representation had effects on policy remains questionable.

For many U.S. biomedical scientists, demonstration of successful self-regulation was a tactic for avoiding premature legislative intervention—and in this they were consistently and eminently successful. The absence of national legislation, however, is not a good measure of Asilomar’s success or, more broadly, of trust in science. Indeed, it has proved necessary to add layers of institutional oversight at critical junctures in the development of genetic sciences and technologies, showing that the laissez faire approach did not sufficiently produce trust. One of these occurred at the start of the Human Genome Project (HGP), when James Watson, the HGP’s first director, set aside funds for research on the ethical, legal, and social implications (ELSI) of research. Regardless how one draws up the balance sheet with respect to ELSI (and it is not straightforward), the point is that the program was conceived as a defensive move by big biology to demonstrate enough ethical and social responsibility to deserve public funding and the trust that such funding implies. As Watson himself explained, “My not forming a genome ethics program quickly might be falsely used as evidence that I was a closet eugenicist.”

Limiting risk to accidental releases of pathogens left untouched the economic, social, and political implications of biotechnology.

Similarly, debates around human embryonic stem cell (hESC) research at the turn of the century show that claims of self-regulation were not alone enough to satisfy public concerns and silence politics. U.S. biomedical science had to publicly demonstrate its commitment to ethical norms. The National Academies issued guidelines for work with stem cells, in conformity with the congressional mandate not to use public funds for deriving hESCs, but going well beyond that minimum requirement. These included a new layer of formal supervision, comprising (Embryonic) Stem Cell Research Oversight (SCRO or ESCRO) committees, established at each institution working with these potentially controversial materials. In practice, therefore, the price of avoiding congressional oversight was a new, more visible, display of self-regulation that stem cell scientists accepted to shore up their claim on public trust.

Challenges to trust and legitimacy, moreover, may resurface at any moment, as NIH learned in 2010-11 through a protracted, though ultimately unsuccessful, legal challenge to its authority to fund downstream research on lawfully derived stem cell lines. The point is not so much that federally funded stem cell research survived the attack. It is that, in a robust, decentralized democracy, there is no one-shot silver bullet for building trust. Political power, as every citizen knows, demands continual regeneration at the polls and elsewhere to maintain its legitimacy. Trust in science is just as fragile and just as much in need of regeneration when science, in effect, takes on the tasks of governance by shaping society’s visions of the future. Decades of experience with the genetic revolution make it clear that narrowing the debatable questions, as at Asilomar, is not a strategy for maintaining trust over the long haul or for living up to the forms of responsibility that democracy rightfully demands from science.

Provisionality

Revolutionary moments do not reveal the future with map-like clarity. Far more, they are moments of provisionality, in which new horizons and previously foreclosed pathways become visible. The challenge for democracy and governance is to confront the unscripted future presented by technological advances and to guide it in ways that synchronize with democratically articulated visions of the good. This demands thoughtful conversations about alternatives for as long as it takes to build new norms for the new futures in view. Conversations are compromised if they are limited to narrow constructions of near-term risk, thereby foreclosing opportunities to build such norms.

Worldwide controversies about the limits of genetic modification, whether in agriculture or biomedicine, signal that Asilomar’s framing of the risks, the stakes, and the scope of deliberation was too narrow to encompass the wide range of ethical, legal, and social issues that accompany a scientific revolution and the forms of collective deliberation they demand. The history of half-measures and repeated eruptions of public distrust around rDNA reveals weaknesses in the NAS-NAM conception of an expert summit as the right instrument of democratic deliberation on gene editing. The very notion of a summit suggests that a view from the mountaintop will provide an authoritative image of the lay of the land, to be charted once and for all through ethics or regulation. Past experiences indicate, however, that good deliberative processes need to be recursive as well as inclusive. The initial framing of an issue shapes the analysis of alternatives, whether scientific, ethical, or political. This is one reason inclusivity at the agenda-setting table is so valuable: it helps to ensure that important perspectives are not left out at the start, only to surface after possibly unjust judgments and decisions have been taken.

The Asilomar meeting on rDNA framed the risks to society in terms of physical hazards to people and, to a limited extent, ecosystems. The solution provided was equally narrow: four levels of physical and three of biological containment of engineered organisms. But as noted above, limiting risk to accidental releases of pathogens left untouched the economic, social, and political implications of biotechnology, and consensus has not yet been achieved on those initially excluded issues. By treating risks as resolvable by technical experts and the responsibilities of governance as settled, Asilomar failed to recognize the virtues of social ambivalence as a resource for building and rebuilding solidarity between science and society by continually rearticulating norms and aspirations to guide an unfolding technological future.

Many experiments have been tried in recent years to involve publics in deliberating on emerging sciences and technologies before their course is set in stone. These “public engagement” exercises include focus groups, citizen juries, consensus panels, public consultations, and technology assessment processes. Initially such efforts presumed that the main reason for public hostility to technological innovation was lack of information. Although public engagement efforts have grown more sophisticated, they remain one-shot consultations whose agenda and terms of debate are still narrowly defined.

Approaching public engagement in this manner misses the point that living well with technology involves more than reacting to information about it. Changes in social interactions and relationships with technology are unpredictable and emerge only through long-term experiences in varied settings. The stakes cannot be accessed, let alone addressed, in highly scripted deliberations that “engage” a limited range of citizens in terms that are defined in advance. Though such exercises purport to satisfy the need for public engagement, they fail to reach the poor, the marginal, and the socially excluded in meaningful ways. They afford little opportunity for the emergence of dissenting voices and perspectives that challenge experts’ imaginations. Consequently, they are more likely to perpetuate than correct Asilomar’s legacy of exclusion. They are, at best, ineffectual in assessing ambivalence and doubt, and still worse at inviting sustained deliberation on humanity’s collective ownership of its technological future.

A 1996 report of the National Research Council proposed an alternative approach to understanding risk that would build in mechanisms for taking the provisionality of people’s judgments into account. This was the analytic-deliberative model, a recursive decision-making paradigm aimed at revisiting early framing choices in light of later experience. In this model, the movement from fact-finding to incorporating value judgments is not linear, as in the conventional risk assessment-risk management approach. Instead, the analytic-deliberative model presumes that, in democracies, the process of understanding risk requires constant revisiting, through deliberation, of the risks framed and the questions asked. Reframed questions in turn lay the ground for meaningful further analysis and keep publics engaged in the process of governance.

Ongoing debates on privacy and civility in the era of digital communication and social media illustrate this need to revisit apparently settled issues in light of lived experience. Facebook users only gradually discovered the need to filter their postings so that messages intended for friends would not be unintentionally disclosed to parents or prospective employers. Twitter users learned the devastating effects of casual messaging and careless jokes only after many episodes of such postings going destructively viral. In a celebrated and still not fully resolved development, European law has diverged from that of the United States in asking Google and other Internet search engines to remove links to excessive or irrelevant information. This controversial “right to be forgotten” emerged only after 20 years of rising information traffic on the Internet. Users could not have foreseen the potentially perverse consequences of a permanent digital memory bank, recording the most trivial aspects of daily lives, when they discovered the informational wealth of the Internet in the 1990s.

Provisionality in the face of new technologies includes, at the limit, the choice to say no to particular visions of progress. In 2011, Germany’s national Ethics Council issued a report on preimplantation genetic diagnosis (PGD) with a substantial minority of 11 members recommending that the procedure should not be permitted in Germany under any circumstances. Even the 13-member majority, followed by the German Parliament, only approved PGD under highly restrictive conditions, including prior ethical review and informed consent by the mother-to-be. These arguments and actions deserve attention as an affirmation that technology’s unimpeded progress is not the only collective good recognized by free societies: as the minority opinion stated, “an enlightened and emancipated relationship to technology is the decision not to use it if it violates fundamental norms or rights.” A regime of assessment that forecloses in advance the very possibility of rendering such enlightened and emancipated judgments opens the way to a politics of dissent and frustration rather than to shared democratic custodianship of the technological future. Perhaps this is Asilomar’s true legacy.

Coming down from the summit

CRISPR-Cas9 offers, at first sight, a technological turn that seems too good for humankind to refuse. It is a quick, cheap, and surprisingly precise way to get at nature’s genetic mistakes and make sure that the accidentally afflicted will get a fair deal, with medical interventions specifically tailored to their conditions. Not surprisingly, these are exhilarating prospects for science and they bring promises of salvation to patients suffering from incurable conditions. But excitement should not overwhelm society’s need to deliberate well on intervening into some of nature’s most basic functions. That deliberation, in our view, demands a more sophisticated model than “Asilomar-in-memory,” a flawed and simplistic approach to evaluating alternative technological futures in a global society.

Summitry organized by science, in particular, needs to be handled with care. Such events, as we have seen, start with the almost unquestionable presumptions that scientists should “push research to its limits,” and that risks worth considering are typically reduced to those foreseeable by science. Physical and biological risks therefore receive more attention than risks to social relationships or cultural values. Such narrowing is inconsistent with democratic ideals and has proved counterproductive in societal debates about genetic engineering. The planned NAS-NAM event would better serve science and society by moving down from the “summit” to engage with wider, more inclusive framings of what is at stake. Good governance depends on visions of progress that are collectively defined, drawing on the full richness of the democratic imagination. Opportunities for deliberation should not be reduced, in our view, to choreographed conversations on issues experts have predetermined to warrant debate. Confining public engagement exercises to such constrained parameters too easily presumes that the entry card for engendering deliberative democracy is speaking the right language, that of scientific rationality.

In the musical My Fair Lady, based on George Bernard Shaw’s Pygmalion, Eliza Doolittle, a Cockney flower girl, takes speech lessons from Professor Henry Higgins, a phoneticist, so that she may pass as a lady. Having transformed Eliza, the professor wishes to control not just how she speaks, but how she thinks. The authors of the NAS-NAM proposal run the risk of acting like Henry Higginses of CRISPR democracy. Having taught the Eliza Doolittles of the world how to articulate their concerns properly, they may be inclined to think that judgment should follow suit, because right language must lead to right reason about the need for research. Yet, the audience’s sympathy rests with Eliza, not Henry, when he sings, “Why can’t a woman be like me?” The rarefied reasons of science are essential to any good deliberation on gene editing, but it is to be hoped that the deliberative processes we design will be expansive enough to let the unbridled Cockney in the rest of humanity also sing and speak.

Coordinating Technology Governance

A new institutional mechanism is needed to serve as an issue manager to coordinate and inform responses to emerging technologies with powerful social implications.

This spring, a new but widely available technology for editing genomes called CRISPR suddenly burst into public view, making headlines around the world. A group of Chinese researchers published a paper describing their attempt, using CRISPR, to modify a blood disorder–causing gene in nonviable human embryos. Although the scientists emphasized that the method is not yet ready for medical applications, CRISPR technology is far superior to previous techniques for precisely splicing and editing genomic information. But not only might CRSPR hold the potential to cure genetic ailments, its successful development might also lead to the capacity to directly modify the human germline, and thus human evolution. The implications of emerging synthetic biology technologies such as CRISPR are thus profound—not just for medicine but for the future of our species. How might democratic societies provide oversight, cultivate public debate, and evaluate the ethical, legal, social, and economic ramifications of CRISPR and other important new technologies? We propose the creation of a new coordinating body, which we refer to as a Governance Coordination Committee (GCC), to fulfill this urgent need.

Emerging technologies such as nanotechnology, biotechnology, synthetic biology, applied neuroscience, geoengineering, regenerative medicine, robotics, and artificial intelligence involve a complex mix of applications, risks, benefits, uncertainties, stakeholders, and public concerns. As a result, no single entity is capable of fully governing any of these multifaceted and rapidly developing fields and the innovative tools and techniques they produce. A diverse set of governance actors, programs, instruments, and influences apply to each form of technology. Within the federal government alone, regulations, guidance documents, studies, and reports produced by several different agencies; White House Executive Orders and reports; congressional overview; and decisions by the Supreme Court all affect technology policy. This is augmented by decisions from lower courts, state and local government actions, and assessments and recommendations from scientific and policy commissions and advisory committees. Furthermore, the business community can shape the governance of an innovative technology through industry-wide stewardship programs, public/private partnerships, and individual companies that set their own standards and establish their own risk management programs. Other stakeholders provide input through think tanks, international standard-setting bodies, statements of principles and recommendations by nongovernmental organizations (NGOs), scholarly articles, certification bodies, codes of conduct, voluntary programs proposed by a variety of organizations, media coverage, and public opinion.

With so many actors and pronouncements in the governance space for any given emerging technology, the result is predictable: inconsistent recommendations, duplication of efforts, and general confusion lead to valuable contributions falling through the cracks or being lost in the cacophony of voices. A current example is hydraulic fracturing (or “fracking”), where literally hundreds of industry groups and companies; governmental entities at the federal, state, and local levels; NGOs; scientific and academic experts; think tanks; and local citizen groups are flooding the public discussion space with a range of arguments, studies, concerns, and positions, with no forum to bring these disparate voices together. This lack of coordination fosters unnecessary complexity that undermines effective governance, as well as a muddled approach to whatever governance is put in place—a muddle that calls out for some form of coordinating entity or function.

Take, for example, the development of nanotechnology policy in the United States in the first decade of this century. A plethora of groups, meetings, and networks were simultaneously working separately on the same issues of nanotechnology governance. Multiple federal agencies were involved, coordinated to a large extent through the National Nanotechnology Initiative, which also convened various stakeholder meetings. The Wilson Center’s Project on Emerging Nanotechnologies emerged as another locus of important activity, issuing a series of significant reports on nanotechnology governance and again convening various meetings of stakeholders. The International Council on Nanotechnology (ICON) was created as a multistakeholder forum to discuss and advance nanotechnology safety and governance. Centers for Nanotechnology and Society, created by the National Science Foundation at universities such as Arizona State University and the University of California–Santa Barbara, generated research and ideas for nanotechnology governance and also created new opportunities and approaches for stakeholder engagement. A multitude of nongovernmental voluntary governance initiatives were created or proposed, such as the DuPont–Environmental Defense Fund Nano Risk Framework. Various NGOs issued their own recommendations and proposed frameworks for nanotechnology regulation and governance. Standard-setting bodies such as ISO, ASTM, and IEEE created additional spaces where safety and governance proposals were debated and developed. And on and on. In some ways, this diversity and number of entities, forums, and initiatives was a strength. Yet there was no coordination or synergy between these disparate efforts that might have reached a critical mass to make a real difference—something a coordinated committee might have achieved.

Indeed, a number of recent commentaries have advocated for the establishment of a coordinating body to provide oversight for various different emerging technologies. For example, in a report on the numerous voluntary programs that have sprung up to help manage nanotechnology, Daniel Fiorini, a long-time Environmental Protection Agency (EPA) expert on alternative regulatory approaches who is now at American University, proposes the creation of a “Nano Stewardship Council” that would “provide an ongoing, neutral forum for discussions on nanotechnology policy issues and options and [serve as] a clearinghouse for information.” Similarly, the Presidential Commission for the Study of Bioethical Issues called for the formation of a “coordinating body” within the government for synthetic biology that, among other things, would “(1) leverage existing resources by providing ongoing and coordinated review of developments in synthetic biology, (2) ensure that regulatory requirements are consistent and non-contradictory, and (3) periodically and on a timely basis inform the public of its findings.” David Winickoff and Mark Brown, writing in this magazine, also called for a new government advisory committee to coordinate the governance of geoengineering research. Susan Ehrlich, a retired appellate judge and charter member of the National Science Advisory Board for Biosafety, has emphasized the need for a new autonomous advisory commission to coordinate governance of dual-use research. Ryan Calo, a professor at the University of Washington School of Law specializing in cyberlaw, proposes the creation of a federal robotics commission to coordinate robotics policy.

Governance Coordination Committees

The structure and function of these various proposed coordinating entities, while varied, all focus on the core need to coordinate the stakeholders, proposals, and diverse issues posed by the governance of individual emerging technologies. We propose that this need for a coordinating entity can best be met with the creation of GCCs. In essence, a GCC would be an issue manager. It would act like an orchestra conductor and attempt to harmonize and integrate the various governance approaches that have been implemented or proposed. Its functions would be wide-ranging.

Among these functions would be the collection of, and reporting on, information concerning existing governance programs for a specific technological field and the identification of gaps, overlaps, and inconsistencies within existing and proposed programs. In monitoring the development of a technology, the GCC would give particular attention to underscoring the gaps in the existing regulatory regime that pose serious risks. It would search, in concert with the various stakeholders, methods to address those gaps and risks. For example, a GCC overseeing the introduction of drones into domestic airspace might flag the issues and expenses that would not be addressed by the Federal Aviation Administration. It could consult with industry, legislatures, and advocacy groups to forge methods to manage and pay for the oversight of privacy and surveillance concerns.

A GCC could provide a forum for stakeholders to deliberate on governance issues and to produce recommendations, reports, and roadmaps. And the GCC would serve as a trusted “go-to” source for stakeholders, the media, and the public to acquire information about the technology and its governance.

In the following sections we address the characteristics of emerging technologies that necessitate this type of novel coordinating entity. We also present examples of precursor coordinating institutions, the possible structure and operation of the GCCs, and responses to some of the most obvious challenges for implementing this proposal.

Different emerging technologies each present their unique sets of issues and regulatory challenges, but also share some features in common. The concerns raised by many emerging technologies go well beyond the health and environmental risks traditionally covered by regulatory statutes, to also include broader ethical, social, and economic concerns, including privacy, fairness, ownership, and human enhancement issues. The benefits of many technologies are highly uncertain, and their risks are often contested. The increasing number and diversity of research trajectories, applications, and participants within each emerging technology category have complicated matters further because, unlike previous fields of innovation, most emerging technologies are not limited to a single industry sector or application. More important, each of the major emerging technologies is progressing at a faster pace than can be handled by traditional governmental regulatory oversight, which appears to be slowing down rather than speeding up.

Traditional forms of government regulation are too slow, ossified, and limited to provide comprehensive and meaningful oversight of emerging technologies. Given these limitations, monitoring and managing the development of emerging technologies requires a governance model that acts quickly and more efficiently than traditional forms of oversight and regulation. Effective governance will expand the circle of responsibility for managing a problem beyond government regulators to encompass other entities, including industry, NGOs, insurers, think tanks, courts, and additional national and international institutions. Government regulation must still play an essential role. Nonetheless, other entities can share responsibility and supplement governmental oversight with various types of “soft law” mechanisms, including codes of conduct, public/private partnership programs, voluntary programs and standards, guidelines, certification schemes, and a variety of other industry initiatives.

Soft law approaches offer many potential benefits. First, they tend to be participatory, cooperative, reflexive, and adaptive. They can involve a mixture of tools and invoke resources and responsibility at multiple levels and from multiple parties. Of course, these soft law approaches also have their weaknesses. They are generally unenforceable and do not ensure full participation by targeted industries. Furthermore, they fail to offer the procedural opportunities and protections for public participation that are provided by traditional government regulation. But the shortcomings of traditional regulatory mechanisms, such as endless litigation and a damaging blurring of the boundaries between science and politics, mean that soft law approaches will be an inevitable component of any successful governance of emerging technologies.

Soft law programs can be plagued by big coordination problems. The presence of numerous soft law initiatives for the same emerging technology is all too common. For example, there are over a dozen significant soft law initiatives for nanotechnology, such as the DuPont-EDF Nano Risk Framework discussed above and the European Union Code of Conduct for Responsible Nanosciences and Nanotechnologies Research. This proliferation of diverse soft law approaches and proposals is a function of their strength. Soft governance initiatives are not limited to centralized federal agencies, but rather can be launched by any entity or coalition of organizations as was the case for the International Council on Nanotechnology described above. What is important but lacking is a credible approach to facilitate the coordination of the independent concerns and actions of these nongovernmental entities; specifically, one able to reconcile these soft law initiatives not only with each other but also with traditional government regulation.

In sum, the governance of emerging technologies has generally proceeded in a fragmented fashion. Government agencies and developers of soft law programs propose new oversight initiatives one piece at a time, with little regard to how different initiatives affect the same technology. The fragmented response to the recent announcement of the Chinese CRISPR experiment, the pronouncements of Stephen Hawking and Elon Musk about the potential existential dangers of artificial intelligence, and even the crash landing of a small drone on the White House lawn in early 2015 should raise serious doubts as to whether the problematic challenges posed by the rapid and unpredictable emergence of new technological possibilities and developments has been, or will be, effectively managed and monitored by this piecemeal, incremental approach. In his observation of biotechnology, technology regulatory expert Gregory Mandel of Temple Law School perceives the lack of coordination to be one of the biggest challenges. He notes, “The multiplicity of statutes and agencies has created confusion among regulated industry and the public, reduced clarity regarding scientific standards and requirements, and retarded the efficiency of biotechnology development and regulation.” This holds true for all new and complex technologies.

Emerging technologies require a coordinated, holistic, and nimble approach, while not sacrificing diligence in overseeing discernible dangers. In short, emerging technologies need an issue manager to orchestrate and serve as the central hub for the various parts that contribute to the governance of that technology. Our societies do not have a lot of experience or models for managing such complex technologies, because in the past most technology issues, whether it be chlorofluorocarbons in the atmosphere, the safety of medical devices, or worker exposure to asbestos, could be dealt with by a single government agency and a discrete group of companies and NGOs. Even then, our regulatory systems were challenged and overextended in many cases, as evidenced by the thousands of untested and unreviewed chemicals in commerce today. It will be even more difficult to effectively manage today’s emerging technologies, which bring with them much more complex and diverse sets of risks, applications, and stakeholders. Nevertheless, there are a handful of relevant institutional precedents that may be helpful in planning for GCCs.

Precedents

Although a formal coordinating entity of the type proposed here has yet to be established, there are numerous examples of institutions serving as de facto coordinating bodies, even when their initial institutional objectives were more limited. For example, as discussed above, several entities filled, either intentionally or by default, the need for policy coordination within nanotechnology. ICON is perhaps the closest real-world attempt to implement the type of coordinating functions we propose here. ICON sought to involve a wide range of stakeholders in an effort to “develop and communicate information regarding potential environmental and health risks of nanotechnology.” Although no longer active, its activities included sponsoring multistakeholder forums to better understand the health and environmental risks of nanotechnology. ICON created an online database and virtual journal of published studies on the risks of nanomaterials, and an online wiki site called the GoodNanoGuide, which listed best practices for handling nanomaterials. Its main source of funding was a $50,000-per-year membership fee from industry members; as a result some NGOs expressed concern and were reluctant to participate. The primary difference between ICON and the GCCs proposed here is that ICON focused primarily on the scientific and risk management aspects of the technology. A GCC would give greater emphasis to the variety of governmental and nongovernmental oversight and governance mechanisms that are in place or have been proposed.

Another precedent is the series of entities that have served as a de facto issue manager for specific emerging technologies, such as the Pew Initiative on Food and Biotechnology (2001–2007) and the Project on Emerging Nanotechnologies (2005–2011). These projects became focal points in the governance of the technology they each individually addressed by issuing influential reports, identifying key gaps and needs in regulatory programs, and serving as a forum for stakeholders to deliberate about the technology.

The committees established by the National Research Council (NRC) to issue consensus reports on controversial or emerging science and technology issues provide another relevant point of comparison. Both the proposed GCCs and the NRC committees seek to provide a credible, honest-broker forum for addressing controversy, but they do it in quite different, if complementary, ways. The NRC committees assemble 12 to 20 leading experts without a direct stake in an issue to meet for a limited time (usually periodic meetings over a one- to two-year time frame) to deliberate, partially behind closed doors, and produce a consensus report on the issue at hand. In contrast, the GCC would directly engage the stakeholders, sometimes numbering in the hundreds of organizations and entities, to interact in a transparent way to promote communication, understanding, and the narrowing of differences without an express expectation of consensus. The effective role that NRC committees perform in bringing order out of chaos on a controversial issue again demonstrates the value of the coordinating function that a GCC could provide, whether or not an NRC committee has been convened for the same issue.

These precedents and examples all achieved some success in providing a coordinating function, whether by design or not, and demonstrate the importance of these functions for an emerging technology. Nevertheless, none of the various institutions described here attempted or achieved the full range of coordinating activities and tasks that the GCCs would fulfill. Moreover, the proliferation of coordinating entities for a single technology undermines the objective of having a single, central, coordinating hub.

Although the examples mentioned above have all made substantial contributions to the governance of specific emerging technologies, they are each limited in different ways in their scope, activities, visibility, participation, and longevity with respect to a nationwide coordinating function. A more comprehensive, inclusive, high-profile, and stable entity is necessary to fill the coordination gap in the governance of emerging technologies.

A proposal

The influence and effectiveness of a GCC in meeting the critical need for a central coordinating entity will depend on its ability to establish itself as an honest broker that is respected by all relevant stakeholders. For example, it can provide an industry with a roadmap that clarifies acceptable risk management practices for the responsible governance of a technology. Similarly, the executive and legislative branches of government are likely to take seriously the recommendations of the GCCs if they consider these committees to be credible and diligent. A GCC will need to be vigilant in not usurping the authority of regulatory agencies, but rather focus on pointing out gaps or potential synergies in regulatory frameworks. Perhaps most important, if GCCs can establish a reputation for fairness and effectiveness in the earliest stages of an emerging technology’s development, they may build the legitimacy necessary to merit the trust of interested members of the public and civil society groups.

In seeking an appropriate means to address a gap in oversight that might expose the public to dangers, the staff of a GCC could draw upon an array of different governmental and nongovernmental approaches and mechanisms. The committees would be mandated to first look for solutions within soft governance mechanisms, and turn to laws and regulations only once all other solutions are determined to be impossible to put in place or insufficient. A GCC with adequate influence might even be able to play various stakeholders off against each other. For example, in proposing that an industry establish a vehicle for self-governance to address a potential danger, the GCC could indicate that the alternative laws and oversight agencies it would propose to the legislature are likely to be more bureaucratic and less adaptive. A legislature, cognizant that the GCC looked first for other means to remedy a problem, would be more likely to look favorably on the proposals that a GCC brought to its attention.

To forge a comprehensive understanding of the challenges posed by a new technology, the staff of a GCC will not only require exposure to research done by scientists and social scientists, but must also listen to concerns raised by social critics and NGOs. Engaged public stakeholders have become increasingly motivated and well organized in participating in technological decision making on problems ranging from breast cancer screening to genetically modified foods to energy technology choices, and the effectiveness of GCCs will be strongly dependent on their ability to bring such voices into their deliberative processes. In turn, the GCC will probably submit recommendations to federal agencies and foundations regarding research that needs to be performed to better manage the potential risks and ethical and social challenges arising from new technologies.

Emerging technologies need an issue manager to orchestrate and serve as the central hub for the various parts that contribute to the governance of that technology.

The private sector will also be a critical participant in GCCs, because many of the key decisions on commercializing emerging technologies are made inside companies. Furthermore, they can provide the expertise and resources that are likely to be critical for a GCC to succeed. If the GCC is structured in a way that provides a forum for evidence-based and nonadversarial dialogue for sharing ideas and concerns, companies should have the necessary incentive to actively support and participate in GCCs. Gone are the days when a company could plow ahead unilaterally with the deployment of potentially controversial technologies. Modern companies understand the necessity of engagement with the public and stakeholders, and would benefit from a process that signals what technology applications are likely to be broadly acceptable and which may be problematic. They will appreciate guidance as to whether and how those problematic applications might be made more acceptable by adjustments or appropriate stewardship measures. A GCC could serve these vital needs of private companies and their investors.

Moreover, the GCC may be helpful in modulating the rate of development of an emerging technology. Just as an economy can stagnate or overheat, so also can technological development. For example, a potentially transformative industry may need to be stimulated in the form of coordinated funding for research. Or to overcome uncertainties that are standing as barriers to development, the private and public sectors might jointly develop critical infrastructure, standards, or test methods. In addition, research and development can be stimulated by bringing companies together to seek collaborative solutions for patent “thickets” that may be blocking innovation. On the other hand, there will be occasions when an emerging technology could spawn an array of societal problems that will need to be addressed before innovative products should be deployed.

For example, take artificial intelligence. No regulatory agency has jurisdiction or programs addressing the potential risks of this powerful technology that holds so much promise. Yet, as we’ve mentioned, prominent scientists and technologists such as Stephen Hawking, Bill Gates, and Elon Musk are raising concerns about the potential future direction and adverse effects of this technology. A GCC could fill the urgent gap in our ability to consider, debate, and address such concerns.

It would be an illusion to think that a GCC, or any other body, could resolve these problems altogether. However, through advice, influence, and building rapport among stakeholders, a GCC could play a key role in modulating the development and deployment of new technologies. Today, no single institution is positioned to play such a role.

Another function of a GCC would be to serve as a central repository for the publicly available science and the research on the social challenges and issues posed by the field of technology it oversees. The GCC would not generate new data itself but would act as a clearinghouse to organize and make available relevant data and studies produced by a variety of other organizations. Depending on what its funds permit, a GCC might commission external reviews or analyses of existing data sets to provide assessments of what is or is not known about a particular technology. Or it could collect and integrate stakeholder views of concerns, benefits, policies, and future projections relating to the technology in question. The precedent set by the Wilson Center–Pew Project on Emerging Nanotechnologies may provide a useful model, particularly in making available a public database with a series of influential reports on the emerging science of nanotechnology. Other examples of online databases include Pharos, GreenScreen, and ChemHAT, which provide information about chemical toxicity aimed at allowing private-sector firms and consumers to make safer decisions about substances and processes they use.

The public and the media often have great difficulty in knowing who is credible and whether various potential harms are real or merely speculative. A GCC might be able to provide some clarity through snapshots and reports that capture the state of a technology’s development and when critical thresholds are about to be crossed. Although it will not be possible to eliminate the challenges and controversies inevitably associated with limited and contested knowledge, a semi-authoritative committee report would nevertheless facilitate determinations as to which harms are imminent and which are highly speculative or dependent on future scientific discoveries. In addition, the GCC would be monitoring the literature and studies from a variety of perspectives and disciplines, and serve as a clearinghouse for important new data and viewpoints. Members of the press could read reports from the GCC or interview representatives of the GCC as a way of grounding their articles about a wide variety of societal concerns arising from the introduction of new technologies.

A current example where such a function may be useful is genetically modified organisms (GMOs). There are legitimate concerns about GMOs, such as the spread of herbicide resistance, cross-contamination with organic and non-GMO crops, potential economic effects on small farmers here and in developing countries, international trade conflicts, and even the effects of GMOs on the taste, quality, and availability of some foods. There are also many alarms and claims, mostly spread through social media that appear to be frivolous and inconsistent with current scientific evidence. A GCC could help journalists, citizens, regulators, and even expert participants in industry, NGOs, and government to focus on the most serious concerns and issues.

However, as a result of all the noise and confusion over the past two decades, without any entity providing the type of moderating and convening role a GCC could have provided, the GMO issue has now become highly polarized and charged. Moreover, unlike, say, the National Academies/NRC, which must focus on technical questions and is limited in its recommendations to matters of expert consensus, GCCs could explicitly acknowledge and make clear the cultural, political, and socioeconomic aspects of disagreements over emerging technologies.

In addition to a GCC for each emerging technology, it would be useful to form a governing council for representatives of GCCs for different technologies to compare approaches, successes, and failures; to note issues that might affect multiple technologies; and to identify cross-technology or convergence concerns that give rise to new challenges. In some cases, it will also be necessary for a GCC to coordinate its activities with that of similar bodies from other countries in order to initiate and promote harmonized approaches to the governance of specific technologies such as, for example, geoengineering.

Challenges and concerns

Creating new institutions is always a challenging task and should not be undertaken lightly. Although there are obvious difficulties in establishing effective GCCs, the transformative potential of a number of powerful emerging technologies signals the overriding need for such a coordination mechanism and justifies trying to address and overcome these issues. For example, the success and effectiveness of any new body in coordinating the activities of various stakeholders will depend on those parties perceiving cooperation as being in their best interest. This suggests that it could be more challenging for a GCC to make progress once a technology has become highly polarized, as might be the case now with genetically modified foods. However, it may be more successful, at least as an initial experiment, in helping to manage an emerging technology where ideological positions have not yet solidified, such as artificial intelligence/robotics or synthetic biology.

There are many additional practical and implementation questions that would need to be answered. For example, from where does the GCC get its power (influence), authority, or legitimacy? How are the constituent members and staff of a GCC chosen? How would the GCC be governed and overseen? How can its credibility be established? To whom is the GCC accountable? Would it be better if a GCC were a government institution? Or private? Or a private/public partnership? And probably most problematic, from where will the GCC receive its funding?

Although we will not attempt to offer comprehensive answers to these implementation questions here, some preliminary thoughts are provided. The effectiveness of a GCC will be largely determined by perceptions of its credibility and its usefulness to the government, technology developers, industry, NGOs, the media, and the public. In other words, there is circularity where influence, authority, and credibility all affect each other. Certainly each of these could, at least in theory, be built over time. But in contemporary society, influence and credibility do not come easily. It would be helpful if individuals who already have a high degree of respect and credibility, such as retired leaders of industry, the government, the military, or academia, took on the establishment of a GCC as a personal mission. Clearly the selection of a credible and respected leader for a GCC will be critical for establishing its bona fides.

There is no single model for how the GCCs might be funded or managed. One option would be legislation providing funding for creating one or more GCCs, perhaps as a pilot project. Another option is for a private foundation to provide funding. Yet a third option would be some sort of combination funding, similar to that of the Health Effects Institute, which is co-funded by the EPA and the auto industry. Finally, funding could be provided through membership fees from industry, as was the case with ICON. Industry funding alone, however, would probably not be a good model because of actual or perceived conflicts of interest, although even here there may be innovative approaches to structure the industry funding to ensure no undue influence. For example, several industry groups, such as the cellphone industry, have funded safety research by creating an intermediary entity composed of credible neutral experts to allocate the funds to try to minimize the reality and perception of funder influence.

The process for the selection of leadership and the number of staff hired for a GCC would, in all probability, be influenced by its funding model. Finally, some sort of advisory or steering committee, composed of representatives of relevant stakeholders, including government, industry, NGOs, the public, scientists, social scientists, and concerned citizens, would also be helpful in building and maintaining credibility and relevance.

We recognize that these practical issues and concerns might make some believe that establishing an effective and credible GCC in the contemporary political context is either too complicated, hopelessly naive, or perhaps both. We contend that the implementation issues can be worked out. Modern governments and private institutions have been capable of implementing complicated solutions to difficult problems once the need is fully recognized. Unfortunately, all too often this occurs only after a tragedy and the realization that similar calamities will occur if protective measures are not put into place. Such shortsightedness and reactive policymaking make more-anticipatory and future-oriented strategies challenging, but not impossible.

A GCC offers a different and more comprehensive approach to monitor, manage, and modulate an emerging technology. As a first step, we recommend implementing a GCC as a pilot project for one or more relatively new technological fields that are not yet encumbered by a large network of oversight bodies, regulatory programs, and adversarial relations. Given the high social and scientific standing of those voicing concerns about artificial intelligence/robotics or synthetic biology, these would be good candidates for pilot projects.

Although there are risks in the GCC approach, we think those risks are worth taking. A new and more ambitious form of governance coordination is one of the most pressing needs for many emerging technologies. Although there may be other (as yet largely undefined) approaches for performing this much-needed coordination function, the GCC is an idea that would be useful to try. A pilot project offers the opportunity to work out the implementation challenges, as well as the opportunity to witness whether GCCs can be a comprehensive, coherent, and effective means of governing the governance of emerging technologies.

Gary Marchant ([email protected]) is Regents’ Professor of Law at the Sandra Day O’Connor College of Law, Arizona State University, where he directs the Center for Law, Science, and Innovation. Wendell Wallach ([email protected]) is a scholar at Yale University’s Interdisciplinary Center for Bioethics. His book A Dangerous Master: How to Keep Technology from Slipping Beyond our Control (Basic Books, 2015) has just been published.

Recommended reading

David Baltimore et al., “A Prudent Path Forward for Genomic Engineering and Germline Gene Modification,” Science 348, no. 6230 (2015): 36–38.

Ryan Calo, The Case for a Federal Robotics Commission (Brookings Institution, September 2014); available at http://www.brookings.edu/research/reports2/2014/09/case-for-federal-robotics-commission.

Susan A. Ehrlich, “H5N1: A Cautionary Tale,” Frontiers in Public Health 2, article 117 (2014): 1–3.

Daniel J. Fiorino, Voluntary Initiatives, Regulation, and Nanotechnology Oversight: Charting a Path (Project on Emerging Nanotechnologies Report 19, November 2010); available at http://www.nanotechproject.org/process/assets/files/8347/pen-19.pdf.

Gregory N. Mandel, “Regulating Emerging Technologies,” Law, Innovation & Technology 1, no. 1 (2009): 75–92.

Gary E. Marchant and Wendell Wallach, “Governing the Governance of Emerging Technologies,” in Innovative Governance Models For Emerging Technologies, Gary E. Marchant, Kenneth W. Abbott, and Braden Allenby, eds. (Cheltenham, UK: Edward Elgar, 2013): 136–152.

Presidential Commission For The Study Of Bioethical Issues New Directions, The Ethics of Synthetic Biology and Emerging Technologies (December 2010); available at .

David E. Winickoff and Mark B. Brown, “Time for a Government Advisory Committee on Geoengineering Research,” Issues in Science & Technology (Summer 2013): 79–85.

Bomb Control

The provocative title for this provocative book by Elaine Scarry at once declares that humanity’s most destructive weapons of mass destruction are in too few (often just two) hands, and declaims against this reality as dangerous and undemocratic. Scarry is the Cabot Professor of Aesthetics and the General Theory of Value at Harvard University, and she argues here that thermonuclear weapons violate both the spirit of social contract theory and the letter of the U.S. Constitution. By these societal and legal standards, she concludes, the nuclear arsenal should be abolished. But how?

Scarry is awestruck by the destructive power of the United States’ 14 Ohio-class nuclear submarines, each bearing the equivalent of 32,000 Hiroshima bombs, or eight times the full blast power expended by all combatants during World War II. “The precise arithmetic of this blast power can be hard to keep in mind,” she writes. “But one pair of numbers is easy to grasp: the earth has seven continents; the United States has fourteen Ohio-class submarines.” And that’s just the sea leg of the U.S. nuclear triad: land-based missiles and bombers complete the nuclear array.

Since World War II, the science of nuclear destruction has created “out-of-ratio weapons” that Scarry sees as impossible to control by traditional social or political means. “New weapons,” she says, “inevitably change the nature of warfare but out-of-ratio weapons have changed the nature of government.”

She recounts how President Nixon once quipped, “I can go into my office and pick up the telephone, and in 25 minutes 70 million people will be dead.” In fact, it’s even easier than that. From anywhere—on a beach in Hawaii, at a diner in Boise, or in a hotel in Helsinki—the president of the United States has within arm’s reach a “nuclear briefcase” (or “black bag” or “football”) containing communication codes he can use on the spot to command a thermonuclear attack. Unless, of course, he misplaces those codes, as President Carter did one day when he sent to the cleaners a suit jacket with the card listing nuclear codes in a pocket, or as President Clinton did for months after binding his code card and credit cards with a rubber band and then losing them. Scarry stresses that controlling these weapons can be not only haphazard but also dangerous, and she cites multiple accidents with H-bombs.

Equally disturbing are examples of how often U.S. presidents have considered using these weapons since Hiroshima and Nagasaki. The list includes President Eisenhower in 1954 during a standoff with China over the islands of Quemoy and Matsu in the Taiwan Straits, and with the USSR in 1959 over Soviet-occupied Berlin; President Kennedy during the 1962 Cuban Missile Crisis; President Johnson when contemplating whether a strike might prevent China from developing nuclear weapons; and President Nixon during the Vietnam War and at three other times he later mentioned without giving details.

To counter this monarchical threat, Scarry constructs elaborate arguments to assert that the power (or at least authority) to abolish nuclear weapons is already at hand. Declaring that “the social contract is a contract for peace,” she concludes that “maintaining nuclear weapons places a country wholly outside the social contract; there is no minor or even major reconfiguring of a country’s contract that can accommodate these weapons.” Using philosophical reasoning that is sometimes arcane and often complex, she traces social contract theory back to the Greeks and then to Europeans such as Hobbes, Locke, Rousseau, and Montaigne. “The social contract outlaws nuclear weapons,” she concludes. But while sketching this concept’s origins and evolution, she stops short of explaining its force and functions today.

Similarly, Scarry’s historical analysis overlooks how the Roman Republic allowed for a constitutional dictator during emergencies, and how political theorists in the medieval and early modern period developed the “reason of state” doctrine, allowing a ruler to act independently to preserve the existence of the state.

While crediting ancient philosophical sources for the U.S. Constitution, she especially parses the founding fathers’ original intent as revealed in The Federalist Papers. In particular, she says that Article I of the Constitution requires a “congressional declaration of war” and that the Second Amendment “distributes to the entire adult population shared responsibility for the use of the country’s arsenal—the provision we know as ‘the right to bear arms’.” Congress has delegated to the president, as commander-in-chief, the authority to react promptly to an emergency, and when timing was not urgent, presidents have conferred informally with congressional leaders about possibly using nuclear weapons; although she believes such shared decisionmaking should be more formally delineated. Her argument that the Constitution requires all citizens to share in the use of the nation’s armed force is less convincing because it is based on closely assessing the founders’ reasoning at the time, when the only “arms” they might bear were handled by individuals: rifles they could carry and cannon they could roll.

Scarry argues that thermonuclear weapons violate both the spirit of social contract theory and the letter of the U.S. Constitution.

Yet by Scarry’s reading of the Constitution’s origins, “the existence of either is premised on the disappearance of the other: either the Constitution, as now seems to be the case, will disappear and our arsenal will thrive; or alternatively, our Constitution will be reaffirmed, causing our nuclear arsenal to disappear.”

But how? This either/or reasoning seems too simple in historical context, and overlooks gains by the United States, Russia, and other nuclear powers in destroying their arsenals, though not yet making them all disappear: from more than 60,000 warheads worldwide in the late 1980s to about 10,000 today. (This spring, the United States had 4,717 nuclear warheads, 1,597 deployed on delivery systems; Russia had about 4,500, with 1,582 deployed). That still leaves plenty more than enough to obliterate all life on this planet—to “make the rubble bounce,” as Churchill once put it—but it’s at least a significant trend in a safer direction.

Scarry also overlooks the tense and testy struggle that has persisted within and around the U.S. government since World War II. She gives scant credit to U.S. arms control and disarmament efforts by scientists and statesmen; initiatives that began with the Acheson-Lilienthal Report in 1946 calling for international control of all nuclear materials and that continue through official and other channels to this day. She seems to make no use of standard works that over the years have helped to clarify the puzzling issues she pursues; for example, by analyst Bruce G. Blair, who studies command-and-control hazards and options; by democratic theorist Robert A. Dahl, who speculated about controlling nuclear weapons by possible forms of civic “guardianship”; by physicist Freeman Dyson, who seeks a more rational understanding of how science and society may yet curb nuclear dangers; or by author Jonathan Schell, who analyzed societal responses to the unstable nuclear threats that still abound.

A chief complaint by Scarry is that the president’s monarchical powers are intensified by his need to order a possible nuclear attack so swiftly, deciding in a few minutes whether to retaliate by launching land-based missiles before they might be destroyed by the enemy. But as the Union of Concerned Scientists and other analysts have suggested, it is quite possible to eliminate this “hair-trigger” danger simply by removing these vulnerable land-based missiles from high-alert status. Then, instead of having mere minutes to respond, the president would have hours or days to confer with others—in the administration, in Congress, and abroad—knowing all the while that those invulnerable Ohio-class subs can still retaliate if needed.

Scarry describes her own evolutionary thinking about nuclear weapons as a search for philosophical and legal clarity, although in the years-long “transformation from a set of oral arguments into a book” she has retained a few glib lines that seem better suited to the podium than to the page. Examples include such items as “Nuclear weapons cannot be fired. They can only be misfired,” or “A free-standing missile is the realization of everything that ever was feared in a standing army.”

In her opening pages there is an implicit call to action, as when she urges readers to help dismantle the thermonuclear monarchy by taking “in our own hands” the Constitution’s Article I powers to declare war and its Second Amendment provisions to bear arms. Yet after detailed chapters that analyze the origins of social and constitutional principles, building what seems to be a historical basis for political reform, she concedes that “they will become very great tools once human hands pick them up and use them. We should use whatever tool can best accomplish the dismantling. If there is a better tool, please tell us what it is, and help us to see how to use it.”

Still, if her approach is ultimately more descriptive than proscriptive, this is an important and intrepid book that raises and questions the assumptions supporting these most awesome of weapons. The problem with controlling thermonuclear nuclear weapons may not be just hers, but ours: that no rational analysis can correct a profoundly irrational reality. Many people would agree that these menacing and now useless weapons need to be abolished. But how?

The Value of Sub-baccalaureate Credentials

Access to reliable data will help students and their parents—as well as government policymakers—make informed educational decisions.

Students, their families, and taxpayers invest in higher education for a variety of reasons. But one of the most-cited by students is that postsecondary education is an investment that leads to better jobs and higher wages. Through this lens, the return on investment (ROI) is central to discussions of the value of postsecondary education and the measurement of student success. Because ROI is driven by how much time and money students invest in attaining a credential, policymakers, students, and their families are paying increasing attention to the labor market success of students after gaining that end product. This is not surprising, because earnings are the “return” side of ROI calculations.

The costs of postsecondary education continue to escalate far faster than inflation. Indeed, since the late 1990s, the rate of tuition increases has been roughly twice the rate of inflation. Stories of the crushing burden associated with student debt continue to gain attention. And the failure of many students to launch adult lives and careers after earning bachelor’s degrees now attracts attention. Together, these issues have led many people to question the value of the bachelor’s degree, the most common postsecondary credential awarded in the United States.

Simply put, these issues lead to two questions: Do bachelor’s graduates earn enough to justify the time and money spent getting the degree? Are there more efficient ways to earn a postsecondary credential associated with middle-class earnings?

Even as these questions mount, the bachelor’s degree is still a good investment for most students, leading to higher rates of employment and higher wages for graduates as compared with peers without a bachelor’s degree. But not every student has the time, money, skills, or inclination to complete the degree. And detailed data from many states show that labor market success is possible without a bachelor’s degree—assuming that a student’s postsecondary credential is technically oriented and that at the end of his or her training a student can fix things or can fix people.

As Table 1 makes clear, students, the ultimate consumers of postsecondary education, are incorporating this information into their enrollment decisions. More and more students are enrolling in sub-baccalaureate training programs. Indeed, in 2013, the latest year for which national data are available, the number of sub-baccalaureate credentials awarded, close to 1.65 million, was approaching the 1.84 million bachelor’s degrees awarded that year.

But what is the value of these sub-baccalaureate credentials? How do they stack up against the bachelor’s degree and against one another? Do some lead to higher earnings than others? To answer these questions, it is useful to examine detailed wage data gleaned from state data files.

Through College Measures, I have worked with a number of states to measure the earnings of students after they have completed a postsecondary degree or credential. The states examined include Arkansas, Colorado, Florida, Tennessee, Texas, Virginia—and soon Minnesota. These states were selected because they have merged student-level data on degrees, programs of study, and institutions with wage data drawn from their state unemployment insurance systems. (It should be noted that no national data set allows the analysis of wage outcomes by program across the range of public institutions captured in state data systems.)

Here I focus on data from just two partner states, Texas and Colorado. However, the patterns that emerge are commonly found in the data from other states (see www.collegemeasures.org/esm). As with most of College Measures partners, these two states report wage outcomes for graduates at several time points after students complete their course of study: usually 1, 5, and 10 years after completion.

Overview information on first- and fifth-year wage outcomes is included in a few of the following tables, to show early career outcomes. However, my emphasis is on longer-term outcomes as a more accurate reflection of the overall returns associated with a postsecondary education. Moreover, many observers argue that bachelor’s graduates, especially those with traditional liberal arts majors, take longer to launch careers, so that using early post-completion earnings may produce a biased picture of the value of these degrees.

In Texas, fixing things pays

Texas, unlike most states, reports time to completion and median debt levels for graduates, along with the median earnings for each program of study. As the data in Table 2 show, the median wages of all bachelor’s graduates are higher than those of certificate completers one year after completion. Yet, in the short run, the wages of bachelor’s graduates are lower than the median wage of associate’s graduates by about $1,000. Because the earnings trajectory of bachelor’s graduates is steeper than that of sub-baccalaureate completers, by 10 years after completing, the median wages of bachelor’s graduates are substantially higher than those of students with only sub-baccalaureate credentials. Still, the bachelor’s degree takes on average longer to complete than sub-baccalaureate credentials, and students borrow far more to attain this degree than to earn sub-baccalaureate credentials.

Medians show central tendencies. Far more important is the variation in the wages associated with credentials from different fields. The next set of tables shows the wages at the 10-year mark for completers of some of the sub-baccalaureate programs with the highest and lowest median wages. Also reported are the median wages of bachelor’s graduates. (Since we are measuring the wages of individuals after completion, a per-capita measure is desirable, compared with, say, median household income.) For perspective here, the median per-capita income in Texas in 2013 was $26,000.

Clearly, in Texas some certificates lead to low wages. As Table 3 shows, completers with certificates in the five lowest fields earn less than the median per-capita income in Texas. Indeed, they earn less than the median wage of high-school graduates ($27,000). One possible explanation for this is that many people with these certificates work part time. In any case, certificates in these fields do not have high market value.

Now consider the wages of completers from the 10 high-paying certificate programs. The median wage of certificate holders in each is above the median of associate’s degree graduates, and completers from the top five programs have median wages above the median of bachelor’s graduates.

In short, some certificates have considerable market value and can lead to middle-class wages. One of the key distinguishing characteristics of high-paying certificate programs is that almost all provide skills designed to fix things. Four of the five certificates with the highest wages have the word “technician” or “technologies” in their program name, and the fifth program is associated with water supply and plumbing (also a field oriented toward making things work).

In Colorado, short-term credentials pay

Colorado’s story is somewhat different, partly because the detailed data are somewhat different. As in Texas, Colorado reports median wages 1, 5, and 10 years after completion for sub-baccalaureate credentials and also for bachelor’s graduates. But it is also possible to distinguish between the wages associated with shorter- and longer-term certificates. Colorado data also cover two different types of associate’s degrees: the transfer-oriented associate’s of arts/sciences (AA/AS), and the career/technically oriented associate’s of applied sciences (AAS). Results are presented in Table 4.

In Colorado, in the long run a bachelor’s degree is, on average, a good bet. Ten years after completion, the median wages of all bachelor’s graduates are higher than the median wages of students who completed any of the sub-baccalaureate credentials noted. However, graduates with the career/technically oriented AAS degree have the highest median wages both one and five years after completion. At year 10, these techies are only about $1,000 below the median wages of bachelor’s students. In contrast, the annual wages of graduates entering the labor market with the transfer-oriented AA/AS degree lag others substantially. And contrary to some other research suggesting that longer-term certificates have more market value than shorter-term ones, in Colorado the reverse is true.

Students completing technical sub-baccalaureate credentials aimed at fixing things or fixing people can earn middle-class wages and, often, more than graduates with bachelor’s degrees.

Comparing Texas and Colorado shows that there may be few national lessons in identifying specific postsecondary credentials of value. State labor markets vary considerably, so identifying high-earning credentials may require detailed data about both the field offering the credential and the state offering it. A variant of the late Thomas “Tip” O’Neill’s famous quip that “all politics is local” is that maybe not all the value of postsecondary education is local, but a lot of it is.

How do wages compare by the subarea in which the degree or credential was earned? In Colorado, the per capita income in 2013 was $31,000. As shown in Table 5, completers from three certificate programs (Human Development, Family Studies, and Related Services; Teacher Education and Professional Development; and Cosmetology and Related Personal Grooming Services) have median earnings below the state per capita income. At the other end of the scale, completers in four programs (Industrial Production Technologies/Technicians; Computer/Information Technology Administration and Management; Precision Metal Working; Criminal Justice and Corrections; and Fire Protection) had median wages higher than the median of bachelor’s degree graduates, and completers with certificates in Management Information Systems and Services had median wages equal to those of bachelor’s graduates. As in Texas, many of the programs that produce students with the best wage outcomes study technology or its application (more detailed Colorado data, including patterns for longer-term certificates, can be found at http:\\co.edpays.org).

These tightly focused career-oriented certificate programs are catching on, but the associate’s degree remains the country’s most commonly granted sub-baccalaureate credential—and its popularity is growing rapidly. Most associate’s degrees are awarded by community colleges, which typically offer at least two different kinds of associate’s degrees. The transfer-oriented associate’s of arts or associate’s of science (AA/AS) degree prepares students to attend a four-year bachelor’s-degree–granting institution, while the associate’s of applied science (AAS) degree is career-oriented.

Colorado students pursuing the AA/AS degree are all classified in a single program of study: Liberal Arts. In contrast, students pursuing the AAS degree are enrolled in many different programs of study. As the wage data in Table 6 for graduates from different AAS programs across Colorado and for completers of bachelor’s degrees and certificates shows, the AAS degree overall has market value. Median wages 10 years after completion fall just slightly below the median wages for all bachelor’s graduates, topping the median wages of AA/AS graduates by more than $11,000 and substantially outstripping those of certificate holders. Note that short-term certificate holders, AAS graduates, and bachelor’s graduates all earn roughly the same median wages.

Collectively, all of these data point to substantial earnings variations across fields of study. The AAS degree in teacher education has very low market value. Graduates with a degree in human development, a perennial low-paying credential, have higher median wages than those with the teacher education AAS, but still quite low. Of the highest-paid graduates, the “fix something, fix people” rule holds. Nursing and allied health are high-paying programs, as are construction and engineering programs.

Alternative paths to the middle class

The data from Texas and Colorado show the value of career/technically oriented sub-baccalaureate credentials. On average, graduates with bachelor’s degrees eventually outearn graduates with sub-baccalaureate credentials, but that’s on average. Students completing technical sub-baccalaureate credentials aimed at fixing things or fixing people can earn middle-class wages and, often, more than graduates with bachelor’s degrees, especially many graduates with liberal arts degrees.

That said, every state’s labor market is unique. Indeed, data available from College Measures show that although many technically oriented sub-baccalaureate credentials have high market value, the return on specific credentials depends partly on where workers live. (Which institution granted the credential can matter, too, but that’s another story and another data set.) The strong implication here is that the nation needs better information about the success of postsecondary students after they leave college. Only with these detailed data can students and policymakers better decide which postsecondary credentials yield the best ROI. And these data must be at the program level, not the institution level.

Although many technically oriented sub-baccalaureate credentials have high market value, the return on specific credentials depends partly on where workers live.

As the value of the bachelor’s degree comes under increasing scrutiny, new forms of competition are emerging. Not coincidentally, these competitors are proliferating just as the concern about the disconnect between the bachelor’s degree and student success in the labor market is accelerating. Many of these emerging alternatives—such as massive open online courses, badges, nanodegrees, competency-based education, coding boot camps, and the like—have garnered a great deal of attention in the press. Accrediting such alternatives (and making students enrolled in them eligible for federal student aid) will be a particularly large issue. However, Congress seems to be willing to consider new alternatives to the traditional system. Of particular note is a recent white paper by U.S. Sen. Lamar Alexander (R-TN) on accreditation, Higher Education Accreditation Concepts and Proposals, released in March 2015 as part of the process of renewing the Higher Education Act (see http://www.help.senate.gov/imo/media/Accreditation.pdf).

Although these high-visibility competitors to the bachelor’s degree may over time unseat the primacy of the bachelor’s degree, the more traditional career and technically oriented training offered via certificates and associate’s degrees are right now producing hundreds of thousands of students each year who are going on to earn middle-class wages; and often earn far more than bachelor’s graduates.

Mark Schneider is a vice president and an Institute Fellow at the American Institutes for Research in Washington, DC; the president of College Measures; and a visiting scholar at the American Enterprise Institute. He served as the U.S. Commissioner of Education Statistics from 2005–2008.

Fusion Research: Time to Set a New Path

The inherent limitations of the tokamak design for fusion power will prevent it from becoming commercially viable, but the lessons from this effort can inform future research.

Burning wood was an important source of energy for early humankind, because it had no competition, no cost concerns, and manageable environmental issues. Over time, new energy sources came into being with demonstrated superiority on key measures of value, such as cost, safety, and convenience. Beginning in the 1950s, fusion energy aspired to play a role, and at least in principle, it has several potential advantages over other sources of electricity.

Fusion is the merging of two atomic nuclei to form a larger nucleus or nuclei, during which energy is released. This is how the sun produces its energy. We know how to produce fusion reactions in the laboratory at small scale. However, a potentially viable fusion reactor would involve heating fusion fuels to very high temperatures (order of hundreds of millions of degrees) to form a gaseous plasma of electrons and ions and holding that plasma away from material walls for long enough that more power is produced than required to do the heating. An intense magnetic field can provide the required isolation, because there is no physical material that can withstand the high temperatures of a fusion plasma. Magnetic plasma containment is the basis of one approach to fusion power and is the focus of the following considerations. A key challenge in making fusion a viable electric power source is that it requires a large energy input, necessitating a larger energy output for viability.

Fusion is appealing as an energy source because fusion fuels are multifold and plentiful. The least difficult fuels to manage from a physics standpoint are the hydrogen isotopes of deuterium and tritium. Among the potentially attractive features of a deuterium-tritium (DT) fusion power plant is fuel abundance and its invulnerability to the type of runaway reaction that can occur in a nuclear fission accident. The challenge is to find a way to sustain a fusion reaction in a way that is economical, reliable, safe, and environmentally attractive.

The quest to make fusion power a viable generation option has turned out to be extraordinarily difficult. A great deal has been learned over more than 60 years of research, and a variety of approaches to fusion power have been and are being explored. However, decades ago the world fusion community decided that the most promising magnetic approach was the tokamak plasma confinement concept in which superconducting magnets are used to hold hot fusion plasma in a toroidal (donut) configuration.

Since a power-producing tokamak was understood to be very complex and expensive, a number of countries decided to develop a prototype together. It is called ITER and was initially supported by the United States, the Soviet Union, the European Union, and Japan. Later China and South Korea joined the project, and the 500 MW ITER was formally launched in 2007 to be built in France. ITER is a 30-meter tall device that will weigh over 20,000 tons and include roughly a million parts. The project has already encountered significant cost overruns and delays, and completion is now planned for 2027—about a decade later than the original target.

As this analysis will show, tokamak fusion power will almost certainly be a commercial failure, which is a tragedy in light of the time, funds, and effort so far expended. However, this particular failure does not mean that fusion power is a dead end. Research is under way on other technological approaches, which can benefit from the lessons learned from the tokamak experience. First we must understand where the tokamak approach went off the tracks.

Market realities

Electric utilities will almost certainly be the eventual adopters of fusion power systems aimed at producing electric power, so it is essential to view fusion technologies from their perspective. In 1994, sensing progress toward a potentially viable fusion power system, the Electric Power Research Institute (EPRI), the research arm of the U.S. utility industry, convened a panel of utility technologists to develop “Criteria for Practical Fusion Power Systems.” Noting that “Fusion power’s potential benefits to humanity and the environment are immense,” the report observed that “as the technology is developed and refined, a vision of fusion power plant buyer requirements is essential to providing a marketable product.” EPRI identified three major interrelated criteria for fusion power success:

Economics: “To compensate for the higher economic risk associated with new technologies, fusion plants must have lower life-cycle costs than competing proven technologies available at the time of (fusion) commercialization.”

Regulatory Simplicity: “Important directions and considerations include: Avoidance of any need for separating the plant from population centers …. Minimal need for engineered safety features …. Minimal waste generation …. Minimal occupational exposure to radiation in plant operation, maintenance, and waste handling activities.”

Tokamak fusion power will almost certainly be a commercial failure, which is a tragedy in light of the time, funds, and effort so far expended.

Public Acceptance: “A positive public perception can best be achieved by maximizing fusion power’s environmental attractiveness, economy of power production, and safety.”

Because the advent of fusion power was not imminent in 1994, EPRI noted, “It is not practical to assign values to these criteria for two reasons. First, because the world of tomorrow will be different—social, regulatory, and energy issues will pose moving targets. Second, there are potential tradeoffs among many of the factors.”

Fusion is sometimes promoted as an alternative to light water nuclear fission plants, so I use them as a reference point in assessing how well tokamak designs meet the EPRI criteria. This makes sense because the U.S. Nuclear Regulatory Commission (NRC), which is responsible for licensing and oversight of fission facilities, declared in 2009 that it has jurisdiction over fusion plants.

It is important to note that nuclear fission power’s acceptance in today’s world is mixed, a view that may or may not change in the future. Because of the current uneven acceptance of nuclear fission power, a conceptual fusion power system should clearly be more attractive, if it is to meet the EPRI criteria at some future date. A close look at the inherent characteristics of tokamak fusion reveals how poorly it compares with current fission reactors and with the EPRI criteria.

Economics

Both fission and DT fusion power plants are capital-intensive with low fuel costs, so I begin by considering reactor core capital costs, neglecting balance-of-plant considerations for the time being. For the purposes of a rough estimate, I use the general rule of thumb that a comparison of the relative masses of materials for systems of similar capabilities provides a rough proxy for their relative cost.

In 1994, technologists at the Lawrence Livermore National Laboratory (LLNL) compared the ITER core, as it then existed, with the core of the comparable power Westinghouse Advanced AP-600 nuclear reactor core. Considering the cores of the two systems was and is a reasonable basis for comparison, since the nuclear core is the heat source for a fission reactor power plant, and ITER is the prototype of the heat source for a tokamak power plant. LLNL calculated that the mass of the ITER tokamak was over 60 times that of the comparable fission reactor. Although the ultimate cost ratio will not be exactly the same, there can be no doubt that the tokamak core will be dramatically more expensive than the fission core. This large difference clearly indicated that tokamak power plant costs would likely be dramatically higher than fission power costs. In fact, the situation is worse when the balance-of-plant costs are considered, because ITER has vacuum, plasma heating, and cryogenic systems that the AP-600 does not.

The likelihood that a tokamak would be prohibitively expensive is supported by the experience of ITER thus far. The current estimate for the cost of the project is over $50 billion, about five times early estimates, and the project is still more than 10 years from expected completion. No one will be shocked if the actual cost is much higher. So on a cost basis, a utility faced with a choice between a fission plant and a tokamak would clearly prefer the fission plant.

Because the ITER central organization does not control the costs of the seven ITER partners, the actual cost of ITER is extremely difficult to determine. Each is committed to delivering certain pieces of hardware, but is under no obligation to publish their costs or convert their costs to dollars. Suffice to say that ITER costs have escalated dramatically in spite of various scope reductions.

The situation looks even worse when one considers the likely operation and maintenance (O&M) costs for a tokamak. The device is inherently large and complex, so that any disassembly and reassembly will be difficult and expensive. On top of that, virtually all reactor components will quickly become radioactive due to neutron activation and widespread tritium contamination, which will exist in abundance, since tritium tends to readily diffuse through most materials, particularly when they are hot. This means that most O&M will have to be conducted remotely, adding significantly to cost. The bottom line is that tokamak economics are inescapably very negative.

Regulation

The NRC will regulate fusion power plants. The NRC has public safety as its primary concern and must take into consideration even remote accident possibilities. The NRC requires all plants it oversees to be prepared for “A postulated accident that a nuclear facility must be designed and built to withstand without loss to the systems, structures, and components necessary to ensure public health and safety.”

Once potential accident scenarios have been identified, regulators require that proposed facilities provide safety in depth to ensure that there is no reasonable chance that even obscure failures will harm the public. Regulatory actions typically involve adding features to proposed designs to minimize and contain potential accidents within facility boundaries, often at considerable cost.

In the case of fission reactors, safety features are legion. Externally, the most noticeable safety feature is the massive building surrounding the reactor vessel, aimed at providing a layer of protection that can contain hazards created by internal system failures. According to the NRC, the nuclear reactor building is “a gas-tight shell or other enclosure around a nuclear reactor to confine fission products that otherwise might be released to the atmosphere in the event of an accident. Such enclosures are usually dome-shaped and made of steel-reinforced concrete.”

The NRC is not alone in its caution. The electric utilities themselves are keenly interested in preventing accidents because of the potentially serious human and economic costs.

The safety risks of a tokamak reactor have similarities and differences with fission reactors. Tokamak reactors will be far from risk-free. DT fusion reactions emit copious quantities of very energetic neutrons, which will damage materials near the plasma region and induce significant levels of radioactivity in adjacent structural materials. Accordingly, a tokamak power system will very quickly become highly radioactive and contaminated with tritium.

The levels of induced radioactivity will be influenced by the choice of reactor structural materials. Decades ago, 316 stainless steel (SS) was proposed but later abandoned in favor of materials in which induced radioactivity would be reduced. Of greatest current interest is reduced-activation ferritic/martensitic (RAFM) steel. Also mentioned are vanadium (V) and silicon carbide (SiC), both of which would require extensive materials development programs to establish their viability for fusion applications. Although induced radioactivity would be reduced with RAFM, V, or SiC, it would not be eliminated. However, their use would significantly increase plant costs, because these materials are more expensive than SS and have less industrial experience.

No matter what materials of construction are chosen, there will be large amounts of induced radioactivity and neutron-induced damage, particularly close to the plasma. Over time, radiation damage will render some system components structurally brittle, requiring replacement. Major component replacement in a tokamak fusion reactor will be very time-consuming, because of its complex geometry and the attendant long reactor downtimes, which will increase power costs.

Finally, it should be noted that there will be human-safety-concern levels of tritium throughout the core structure and the surrounding regions of a tokamak reactor, because tritium readily diffuses through most materials, particularly at the high temperatures that a tokamak reactor will operate.

Tokamak plasmas are not benign. As the European Fusion Network acknowledged, “Tokamaks operate within a limited parameter range. Outside this range sudden losses of energy confinement can occur. These events, known as disruptions, cause major thermal and mechanical stresses to the structure and walls.” Disruptions have been identified as a major problem to the design and operation of future tokamak reactors.

As reported at the 2011 Sherwood Conference, in the case of ITER, “…local thermal loads during plasma disruptions significantly (10 times!) exceed the melting threshold of divertor (waste dump) targets and FW (first wall) panels. A reliable Disruption Mitigations System (DMS) must be developed and installed in ITER prior to the full scale operation….” According to a 2013 ITER Newsline, “ITER, the world’s first reactor-scale fusion machine, will have a plasma volume more than 10 times that of the next largest (existing) tokamak, JET.”

Further, according to Columbia University researchers in 2011, “Disruptions are one of the most troublesome problems facing tokamaks today. In a large-scale experiment such as ITER, disruptions could cause catastrophic destruction to the vacuum vessel and plasma-facing components. There are two primary types of disruptions…which have different effects on the tokamak and need to be addressed individually.”

Although various mitigation options are under consideration, none can realistically be expected to be 100 percent foolproof. Accordingly, tokamak disruptions will clearly be of concern to both regulators and potential utility operators.

Another potential problem is the reliability of the magnets that contain the plasma. It is well known that superconducting (S/C) magnets can accidentally quench, which means suddenly “go normal” with a large release of stored energy. During a quench, a large S/C magnet can be damaged by high voltage, high temperature, and sudden large forces. Although magnets are designed to withstand an occasional accidental quench, repeated quenches can shorten their useful lives.

Small S/C magnets are widely used in magnetic resonance imaging machines, nuclear magnetic resonance equipment, and mass spectrometers. These systems are routinely stable and well behaved. Larger S/C magnets are used in particle accelerators, where difficulties have occurred and are considered a “fairly routine event,” according to a 2008 article in Fermilab’s Symmetry: Dimensions of Particle Physics. For example, a September 2008 magnet quench in the Large Hadron Collider occurred in about 100 bending magnets, led to a loss of roughly six tons of liquid helium coolant, which was vented and lost. The escaping vapor expanded with explosive force, damaging over 50 superconducting magnets and their mountings.

At the Fermilab particle accelerator, the Symmetry article reports, “a quench generates as much force as an exploding stick of dynamite. A magnet usually withstands this force and is operational again in a few hours after cooling back down. If repair is required, it takes valuable time to warm up, fix, and then cool down the magnet—days or weeks in which no particle beams can be circulated, and no science can be done.”

Events like these in accelerators are often caused by particle beams striking chamber walls, creating sudden, localized heating. Disruptions in tokamaks might provide similar triggers, but they are not the only events that can initiate quenching. To date, quenches have occurred on at least 17 occasions in tokamak experiments constructed with S/C magnets, due a number of factors including fast current variations, vacuum loss, subsystem failures, operator errors, and mechanical failure. Some failures can be avoided relatively easily, whereas others can require costly magnet and magnet casing replacements. With a structurally robust core containment vessel, such failures would not lead to danger to the public.

The ITER cryogenic system will be the largest concentrated cryogenic system in the world. ITER designers are mindful of quench potential, and in 2007 the ITER organization commented as follows:

Despite 23,000 tons of steel, the ITER machine won’t be a rigid, unmoving block. As the magnets are cooled down progressively, or as they are powered up according to ITER’s plasma scenarios, the machine will “breathe” and move. Quenches may occur as the result of mechanical movements that generate heat in one part of the magnet. Variations in magnetic flux or radiation coming from the plasma can also cause quenches, as well as issues in the magnet cryogenic coolant system.

During a quench, temperature, voltage, and mechanical stresses increase—not only on the coil itself, but also in the magnet feeders and the magnet structures. A quench that begins in one part of a superconducting coil can propagate, causing other areas to lose their superconductivity. As this phenomenon builds, it is essential to discharge the huge energy accumulated in the magnet to the exterior of the Tokamak Building. Magnet quenches aren’t expected often during the lifetime of ITER, but it is necessary to plan for them. “Quenches aren’t an accident, failure or defect—they are part of the life of a superconducting magnet and the latter must be designed to withstand them…”

Restarting a superconducting tokamak will be time consuming. In the case of the Chinese Experimental Advanced Superconducting Tokamak (EAST), it took about 18 days to cool all coils from room temperature to 4.5kelvin after a quench that occurred in December 2006. ITER and subsequent tokamak power reactors are much larger and will certainly take much longer to restart.

If a quench in ITER were to cause all of its magnets to go normal, the magnetic energy released would be over 40 gigajoules, the equivalent of toughly ten tons of TNT. How fast that energy is released depends on a number of factors, and regulators will require design features to minimize external damage.

Finally, and surprisingly, there is a potential fire hazard associated with an ultralow-temperature helium release. According to a University of Pittsburgh 2008 safety manual: “The cryogenic gases are not flammable; however, the extreme cold that exists during and immediately after a quench may cause air to condense and create liquefied oxygen on surfaces. Any liquid dripping from cold surfaces should be presumed to be enriched oxygen and treated as a potential fire hazard.” Although the chances of an associated fire hazard are likely small, they are not zero, so regulators will require related safeguards. On the basis of decades of experience with S/C magnets, the problem of quenching is not likely to ever be completely eliminated, so regulators will plan and regulate expecting their occurrence.

Because of the potential for significant explosive events in a tokamak power reactor based on an ITER-like core, regulators are virtually certain to require a major containment building to control the extremes of such events. Since a tokamak reactor would likely be tens of times larger than the containment building of a fission reactor of a comparable power level, such a building will be extremely expensive. Without a detailed design that would pass regulatory scrutiny, the cost of that tokamak reactor building cannot be easily estimated.

When imagining the hazards that regulators will anticipate, it is worth considering some of the guidance for nuclear fission reactors. Hazards that must be considered include, but are not limited to, the following: Loss of coolant accidents; failures in steam system piping; breaks in lines connected to the reactor coolant pressure boundary; internal missiles; internal fires; internal flooding; human origin hazards; an aircraft crash; explosion of a combustible fluid container; natural hazards; earthquakes; hurricanes; floods; tornados; impacts of an external missile; blizzards; terrorist attack; etc.

Of particular concern will be an aircraft collision with a tokamak fusion power plant. According to a 2014 report by the Congressional Research Service, “Nuclear power plant vulnerability to deliberate aircraft crashes has been a continuing issue. After much consideration, NRC published final rules on June 12, 2009, to require all new nuclear power plants to incorporate design features that would ensure that, in the event of a crash by a large commercial aircraft, the reactor core would remain cooled or the reactor containment would remain intact, and radioactive releases would not occur from spent fuel storage pools.” In light of the already noted sensitivities to plasma disruptions and S/C magnet disruptions, it is difficult to envision a tokamak fusion power plant not being significantly damaged by an aircraft collision. In fact, an aircraft smaller than a commercial airline may well be sufficient to lead to a series of events in which many of the S/C magnets would go normal, releasing stored energy, tritium, and induced radioactivity. The increased containment already described would have to be made dramatically stronger at major cost to have even a reasonable probability of meeting NRC standards.

It is beyond the scope of this analysis to estimate the cost of regulator-required building(s) to contain the most extreme but conceivable accidents, because a complete system redesign would be required to minimize its size. Although it is believed that a tokamak reactor containment structure will have to withstand a smaller maximum energy release than a fission reactor, it is reasonable to assume that such a building will be very expensive, because of its huge size. Related costs do not seem to have been factored into ITER planning, because a containment building has not been thus far required.

An essential element of ITER and tokamak power reactors is the divertor, a device at the bottom and/or top of the plasma chamber that collects waste particles and impurities while the reactor is operating. Divertors have been used in tokamak experiments for a long time but have not operated for extended periods with hot DT plasmas in which there is significant fusion energy production.

When DT fusion reactions occur, energetic helium nuclei are produced, which sooner or later will strike the divertor plate, where their energy is recovered and where the resulting helium gas can be readily pumped out of the system. Since the flux of plasma striking a divertor will be very energetic, divertors will operate at very high temperatures, so tungsten has been the usual material of choice.

Recent research at the University of Wisconsin indicates that no solid material, including tungsten, can operate under expected ITER conditions for a reasonable period of steady state operation. The problem is that energetic helium nuclei will become buried in the divertor material, causing surface morphology changes, including the formation of blisters. These surface changes have been found to lead to material loss values greatly exceeding previous estimates, resulting in an unacceptable amount of radioactive dust, which can quench the fusion plasma or act as a mobile source of radioactive tungsten dust. These recent results may not hinder ITER operation, because ITER is not expected to operate for long periods of time. However, it would definitely hinder a tokamak fusion reactor, where long-term operation is essential. Some researchers have proposed using a liquid metal instead of a solid, but related viability is yet to be established.

Another challenge is that many in the U.S. government have been troubled by the continuing escalation in ITER costs and its lengthening schedule. Recently, the Energy and Water Development Subcommittee of the Senate Appropriations Committee released a recommendation that the U.S. withdraw from the ITER project. This recommendation did not survive the full appropriations process, but it does not portend well for future ITER funding.

For over 50 years, the public and governments have been told very positive things about fusion power. Fusion is the fundamental source of energy in the universe, powering the sun and the stars, which is true. Fusion has been heralded as the ultimate solution to humankind’s energy needs, because of its essentially infinite fuel supply and its inherent cleanliness and safety.

Tokamak fusion, as envisioned by ITER and according to the foregoing, will not be close to being economic and has inherent safety and radioactivity problems. As ITER tokamak realities become more widely known, it is conceivable that the public will feel that it has been lied to by scientists and governments. Accordingly, a public backlash could result. Although understandable, it would be unfortunate, because there are other approaches to fusion power that may hold great hope for the future.

Lessons for future fusion research

The difficulties associated with the ITER-like tokamak approach to fusion power are significant, many would say overwhelming. Although pursuing this ultimately dead-end approach consumed significant resources, tokamak research and development experience can provide important lessons for researchers in their quest for other, more attractive approaches to fusion power. Development of a full list of lessons is beyond the scope of this analysis, but a few conclusions can be drawn.

First, the EPRI Criteria for Practical Fusion Power Systems should be mandatory reading and periodic discussion for all fusion research personnel and managers. There is no question that a viable fusion power concept must be economically viable, preferably superior to competitive electric power production options, e.g., renewable, nuclear, natural gas, and coal. Managerially, that requires a viable, continuing engineering design function that analyzes evolving physics concepts and challenges those whose reactor embodiments show potentially significant weaknesses.

Second, the inherently large size required in the tokamak approach is a significant disadvantage because of the time and resources required to attain important milestones. Concepts that are inherently small can progress more rapidly and at lower cost.

Third, plasma configurations that easily or inherently disrupt are not desirable.

Fourth, concepts that involve magnetic fields should avoid magnet systems that can easily quench. S/C magnet quenching is hazardous, disruptive, expensive, and time-consuming. If S/C magnets are to be used, configurations that are inherently more stable should be favored.

Fifth, although the preceding did not delve deeply into the multitude of the materials issues in ITER/tokamak power, the use of existing, industrial materials is always a positive. The fewer new technologies associated with the introduction of a basically new technology, the better.

I am reminded of the history of fission nuclear power. A number of interesting and exotic concepts were developed and pursued, many extensively. It took the pragmatic Admiral Hyman Rickover to recognize the many inherent challenges associated with emerging nuclear technology. He chose reactor configurations that were in many ways the least sophisticated. He succeeded for the Navy application, and his concepts won over almost all others for commercial electric power application. A fusion concept that initially simply boils water may not sound very exotic, but it may well facilitate the introduction of a new fusion technology. As the saying goes: “The best can be the enemy of the good.”

Finally, the concerns of likely regulators and potential utilities must be seriously considered relatively early in the development of any fusion concept. The longer those concerns are delayed, the more serious the potential upset.

Robert L. Hirsch ([email protected]) is senior energy advisor at Management Information Systems, Inc., in Washington, DC, and a consultant in energy, technology, and management. He headed the federal fusion program from 1972-1976.

Recommended reading

J. Kaslow, M. Brown, R. Hirsch, R. Izzo, J. McCann, D. McCloud, B. Muston, A Peterson, Jr., S. Rosen, T. Schneider, P. Skrgic, and B. Snow, “Criteria for Practical Fusion Power Systems: Report from the EPRI Fusion Panel,” Journal of Fusion Energy 13, nos. 2/3 (1994).

Stephen O. Dean, Search for the Ultimate Energy Source: A History of the U.S. Fusion Energy Program (New York, NY: Springer, 2013).

The Pauling-Teller Debate: A Tangle of Expertise and Values

This historic debate from the height of the Cold War provides a refreshing perspective on science and politics.

By 1958, Americans had been living under threat of nuclear attack for more than a decade. The United States and the Soviet Union were trading atomic weapons tests, battling for supremacy through displays of scientific and military might. Though the weapons were tested in remote areas, mangled shacks and burned farm animals near the blast sites revealed the destructive power of the bombs.

As the total number of global tests grew with each passing year, from 25 in 1955 to 55 in 1957 to nearly 120 in 1958, so too did concerns that the enemy would launch a nuclear attack. Children practiced scrambling under their desks upon seeing a flash of light in the sky. People built fallout shelters and stockpiled them with food, blankets, and first aid supplies, should an atomic bomb make their land unlivable.

Meanwhile, activists and politicians debated the merits of the tests, and the intensity of their concerns increased with the strength of weapons. Two lines of argument shaped the public conversation. Those who favored an end to nuclear weapons testing thought an international treaty was the only way to peace, while others supported continuing the tests to ensure freedom and national security.

On February 20, 1958, in the midst of the escalating nuclear tests, two scientists met in San Francisco for a live televised debate over nuclear weapons testing, fallout, and disarmament.

At the moderator’s right sat a staunch Linus Pauling, the 1954 Nobel Laureate in Chemistry and a compelling voice in the push for world peace through nuclear disarmament. To their left was physicist Edward Teller, looking comfortable and confident. Teller helped build the atomic bombs detonated over Hiroshima and Nagasaki and also helped develop the more powerful hydrogen bomb. He supported constructing increasingly powerful weapons to deter nuclear war with the Soviets.

Since that day nearly 60 years ago, the spectacle of scientists dueling in public over matters of political disagreement has become more and more commonplace. Experts line up on opposing sides of a widening array of policy debates around issues as diverse as climate change, genetically modified crops, food and nutrition, and K-12 education. The experts speak as scientists. But very often they also speak on behalf of one political position or another. As a result of such advocacy, the line between science and politics seems to be growing more and more blurry.

When the politics are divisive and the science is complicated and uncertain, what should the role of scientists be in helping the public come to terms with complex and difficult dilemmas? Today’s cacophony of science and politics makes it hard to see clearly how these two different worlds might interact to the benefit, rather than the detriment, of each. What might we learn, then, if we look back to a time when such debates were much less familiar, when scientists were mostly in the background of political processes, and the authority of science was much less wrapped up in its role in public controversies?

Scientists in black and white

On that night in 1958, the television camera first focused on the moderator sitting at a podium. Behind him in big block letters hung KQED, the call sign of San Francisco’s public television station. “We in the United States bear an enormous burden in the decisions which must be made,” he began, referring to society’s questions about how to handle our invention of nuclear weapons. Smartly dressed in a suit and bow tie, the strength and confidence in his voice matched his demeanor. “In an effort to sharpen the focus…two of the world’s leading scientists agreed to debate the issue of ‘Fallout and Disarmament.’ Each speaks from personal convictions based upon experience, thoughtful consideration, and a profound knowledge of the subtleties involved.”

Pauling, wearing a suit tailored to fit his thin frame, spoke first. A week shy of his 57th birthday, gray hair curled around his ears and at the nape of his neck. The top of his head was practically bald. Pauling began giving lectures about the science of atomic weapons after the United States used the bombs on Japan in 1945. By the end of the 1940s, he was studying international relations, international law, and the peace movement. Then he shifted to speaking about the dangers of atomic weapons, always keeping his presentations up to date with the latest scientific advances and political developments.

Placing both hands flatly on the table in front of him, Pauling leaned forward and looked straight into the television camera. “I am a scientist. I am interested in the world, this wonderful world we live in.” He seemed a bit uncomfortable and hesitated slightly. “And I am especially interested in human beings.” With this line, his eyes twinkled and his demeanor relaxed.

He launched into his political position and policy advice. “We must not have a nuclear war. We must begin to solve international disputes by the application of man’s power of reason in a way that is worthy of the dignity of man.” With each must Pauling’s voice got louder and his body language larger. “We must solve them by arbitration, negotiation, the development of international law, the making of international agreements that will do justice to all nations and to all people—will benefit all nations and all peoples. And now is the time to start.”

One month before this, Pauling and his wife Ava Helen presented a petition to the head of the United Nations while they were in New York. The day after their UN visit, the front page of The New York Times reported “9,000 Scientists of 43 Lands Ask Nuclear Bomb Tests Be Stopped.” It was the largest organized political movement among scientists in a decade. The scientists united to express their concerns about the potential health effects of radioactive particles called fallout, recently discovered drifting through the atmosphere after weapons tests.

But not all scientists, including Pauling’s debate opponent Teller, thought nuclear testing should be stopped. Teller and Albert L. Latter, also a nuclear weapons expert, challenged the petition through an article they published in Life magazine. The story’s subheading blared: “Father of H-Bomb and Colleague Answer Nine Thousand Scientists: Fallout Risk is Overrated.”

In their Life article, Teller and Latter agreed with the findings reported to policymakers by an independent panel of scientists charged with assessing the hazards of fallout. The scientists concluded that background radiation bombarding the planet from the Sun and x-rays from procedures at doctors’ offices were more dangerous than nuclear weapons tests. Teller and Latter used this information to claim that the chances of contracting leukemia or bone cancer from fallout were negligible.

Buried in the piles of notes strewn across Pauling’s podium was a copy of Teller’s Life article. “I should like to read a statement in this article,” Pauling said, putting on his glasses. He began reading: “‘Since the people are the sovereign power in a democracy, it is of the greatest importance that they should be honestly and completely informed about all the relevant facts.’” He read each word with deliberation, and then said: “They are not honestly informed or completely informed by this article.” Pauling then proceeded to read several passages of the article, many relating to the potential health impacts of radiation, that he deemed “not true” and “seriously misleading.”

Teller followed Pauling’s argument with his own copy of the article in front of him, holding a pencil poised for taking notes, even though quibbles over the article’s contents did not concern him. Ending weapons tests was a greater danger than fallout. If Pauling’s fame and influence were growing through his work on disarmament, Teller’s career was advancing by building weapons and advising politicians about them.

Pauling’s numbers

Pauling finished his presentation with some science of radiation that he hoped would help listeners understand the magnitude of the dangers from fallout. He recited memorized estimates that 15,000 children yearly would be affected by disease-causing genetic mutations should nuclear testing continue at the current rate.

“Also, there are serious effects on the health of human beings now living, according to the information that is now available.” His dark eyebrows rose in emphasis and he rarely turned his eyes away from the television camera. “This is the opinion that I and many of my scientific colleagues—a great many—have.” He smiled slightly and nodded in satisfaction as he reached the end of his opening statement.

Knowing that many individuals value their own good health and that of their loved ones, Pauling sought to connect the preservation of health to the halt of weapons testing. If a majority of people could be swayed by his argument, it would improve the chances of enacting a policy that stopped the detonation of nuclear weapons simply for the purpose of testing them. A policy banning nuclear tests was, in Pauling’s opinion, the first step toward peace.

Pauling had a personal stake in his position on weapons testing, as his own moral code about the ethical responsibilities of scientists drove him to speak out for peace. Though he was a pacifist, scientific evidence also informed his political position. Pauling wanted the debate to continue emphasizing the science.

Teller had a different strategy for his opening statement. He planned to talk politics through an emotional appeal, more than a factual one. He leaned on the table, his body turned slightly toward Pauling. “I would like to emphasize at the outset that there are many, many facts about which Dr. Pauling and I agree,” 50-year-old Teller stated in a thick Hungarian accent. The arcs of his widow’s peak matched the curves of his dark caterpillar eyebrows, and wrinkles in his suit jacket crept up toward his shoulders. His relaxed demeanor and slightly disheveled appearance made him appear more avuncular and approachable than Pauling. “Now, the first points about which I would like to agree very strongly with Dr. Pauling are his quest for peace and his great appreciation for human life.”

The camera cut to Pauling. Back straight, brow furrowed, and lips pursed, he stared at the camera acknowledging Teller’s statement with a slight nod. He seemed to be trying to figure out what Teller would say after this string of compliments.

Teller’s story

“We live in the same world with the Russians, whose leader has said that he ‘wants to bury us’—and he means it. Disarmament, the cessation of tests, will not automatically bring us closer to peace,” Teller argued. Disarmament stripped nations of their ability to retaliate. It had allowed Adolf Hitler and the Nazis to occupy Teller’s homeland.

Born to a Jewish family in Hungary and educated in Germany, Teller emigrated in 1934 to escape Nazi persecution. Despite leaving over 20 years ago, the feelings of harassment were still fresh, and anger rumbled in his raised voice. The belligerence of the Soviet Union made the country no more trustworthy than Nazi Germany had proven to be.

“We are playing for big stakes,” Teller continued, becoming solemn. “We are playing not only for our lives, we are playing for something more. We are playing for freedom, for our own freedom, for the freedom of our friends and allies.” Siding with the U.S. government’s nuclear policy of deterrence, he believed that force was the best way to maintain freedom and eventually achieve an international agreement. Placing freedom above peace allowed him to appeal to viewers’ fears of a Communist takeover.

“We must avoid war under all possible circumstances, except, in my opinion, one: when the freedom of human beings is at stake.” Teller’s head nodded and shook as his passion crescendoed with the points in his speech. “If we…let the Russians know, that we will defend ourselves, I think that is the best way to peace. But all this means that we must be prepared.” War was a last resort; developing and testing weapons deterred war.

Pauling tried to turn the debate back to what he felt was the central question that scientific information could address: the amount of genetic damage presently caused by test explosions. But Teller was savvy at politics. He had established himself with governmental and military personnel as an expert on weapons development and national security. He spent most of his public speeches appealing to people’s belief systems, but that did not mean he ignored the science.

When Pauling discussed the science of fallout, Teller turned it into an opportunity to talk about another side of nuclear science, a utopian future made possible by continued testing. He spoke of the development of clean explosives devoid of radioactive elements, of days when nonradioactive nuclear explosions could be used to crush rock for mining, dig canals, and possibly even increase oil production.

The camera cut to Pauling, who watched Teller closely and nodded politely. A slight smile barely hid his growing anger.

“Now let me tell you right here,” Teller stated earnestly, “this alleged damage which the small radioactivity is causing by producing cancer and leukemia has not been proved, to the best of my knowledge, by any kind of decent and clear statistics,” Teller continued stating each word slowly and clearly through his thick accent. “It is possible that there is damage. It is even possible, to my mind, that there is no damage. And there is the possibility, furthermore, that very small amounts of radioactivity are helpful.” Besides, Teller continued, scientific research showed that genetic mutations in sperm could be caused by something as simple as the clothes men wore. Why, then, worry about the effects of radioactivity?

Teller’s position on the scientific evidence for risks from fallout was clear: Too much was unknown. Researchers had yet to provide conclusive statistics about the damaging effects of radioactive fallout on the reproductive system. Without stronger scientific evidence, it was too early to take a radical action that could make the U. S. vulnerable to nuclear attack.

Pauling thought he was there to discuss science, and he repeatedly tried to engage Teller in a scientific discourse. But he recognized Teller’s tactical advantage as the debate progressed. Teller captured viewers with ardor and urgency that were sure to have them listening intently to his message about the specter of a catastrophic world war.

So Pauling switched his focus from fallout science to policy advice that might calm listeners’ concerns. “I do not believe that there is going to be a nuclear war. I believe that these great stockpiles of nuclear weapons are really deterrents, as President Eisenhower has described them. Deterrents that will prevent war.” The next step, he said, was instituting an international agreement to stop bomb tests. However, Pauling’s tempered statements and restrained demeanor undermined his effectiveness toward an emotional connection with listeners.

Nuclear weapons are deterrents, Teller agreed. But to cease tests was to give the world to the Russians. “Now, peace based on force is not as good as peace based on agreement, but in the terrible world in which we live—in the world where the Russians have enslaved many millions of human beings, in the world where they have killed men—I think for the time being the only peace that we can have is the peace based on force.” Agreements take time. Soviet ruthlessness left the United States no option but to stay strong.

The debate volleyed in this manner. Pauling and Teller dissected each other’s statements and cast doubt. They made emotional appeals and pushed political solutions. They stood their ground on the best approach to international policy. Teller conveyed his earnestness with body and voice. Pauling retreated into the comfort of academic arguments grounded in numbers, facts, and reason.

By the end of the debate, however, science held a supporting role, as each man emphasized his value-based position on an international policy issue.

Teller grabbed the advantage from the beginning and never let go. He had a better presence on camera. And although he discounted the science of fallout, his arguments resonated with viewers better than Pauling’s numbers, statistics, and bland delivery.

Pauling’s strongest statement came toward the end of the debate. He wondered when countries throughout Europe, Asia, and the Middle East would have nuclear weapons. “If testing continues and stockpiles of nuclear weapons get into the hands of a great many countries,” Pauling said, “there would be great danger of outbreak of a catastrophic world war.” Although the gravity of his message increased, Pauling remained calm.

Teller got the final word. He ended with a fire in his belly and an argument that he hoped would sway people’s thoughts on the matter. “I have to tell you that I am not talking about these things calmly,” he sneered, lurching his torso toward the camera. “I have feelings. I have strong feelings. Many people were killed in Hungary from where I came, and all people in Hungary lost their freedom.”

Striking the desk twice in rapid succession, he continued his political tirade. “This question of freedom is the most important question in my mind. I don’t want to kill anybody. I am passionately opposed to killing,” Teller spat out, “but I am also even more, more, more passionately fond of freedom.” His head bobbed vigorously. He condemned censorship. He rebuked totalitarianism. His fury was obvious. And with his rage at a boil, he concluded. “I am talking for my freedom, for his freedom,”—he gestured to Pauling—“and for the freedom for all of us.”

With that statement, the debate ended. The moderator sat perched on his stool between the two scientists. Looking at each scientist in turn through thickly framed glasses, he reminded viewers of their responsibility in what today might seem extraordinary terms.

“It is apparent that the issue has not been resolved, but I am sure that both of our guests would agree that its ultimate solution rests in our hands. That each of us bears the moral obligation to examine the evidence, draw conclusions from this evidence, and act upon our convictions.”

And the winner is…

To modern ears, what is refreshing about the Pauling-Teller debate comes through the moderator’s concluding acknowledgment that science alone could not provide a clear answer on the issue of regulating nuclear testing, and that democracy would have to be the arbiter of such difficult choices. This perspective was more famously echoed almost exactly three years later in the farewell speech from President Eisenhower, who warned of the “danger that public policy could itself become the captive of a scientific-technological elite.” Nonscientific factors, including personal experience, economics, religion, and political persuasion would inform voters’ and scientists’ positions. Now, more than half a century later, what seems especially remarkable about the debate is how overtly Pauling and Teller—preeminent experts both—connected their opposing scientific perspectives and policy preferences to their highly personal views of the world and of the best ways to manage the unprecedented specter of nuclear Armageddon.

Each scientist drew on his scientific expertise to argue his position. Pauling used his knowledge of quantum mechanics and organic chemistry to estimate the strength and detrimental effects of nuclear weapons. Teller used his knowledge of the weapons’ workings to envision improved, radiation-free versions of nuclear power.

By the end of the debate, however, science held a supporting role, as each man emphasized his value-based position on an international policy issue. Pauling remained stoic as he used statistics to urge peace through an international treaty banning nuclear testing. Teller made the topic personal by focusing on his family and others’ experiences with the totalitarianism of Nazi Germany and the Soviet Union to support the use of force to keep the peace.

The Pauling-Teller debate reminds us that there is an alternative, and arguably better, way to involve scientific experts in political controversies. Neither scientist tried to occupy a pedestal of detached objectivity in a world of momentous dilemmas and divisive politics. As the scientists argued, the audience could easily recognize their statements for what they were: informed perspectives influenced by personal values.

This doesn’t mean that science is unimportant or should be disregarded in political debate, but it does mean that experts need to be recognized as humans with biases, preferences, and always incomplete views of the difficult challenges facing democratic society. In the end, the question of whether expertise confers special wisdom about how best to resolve political controversies is a matter for the rest of us to decide. The final word was neither Teller’s nor Pauling’s, but that of the moderator: “That each of us bears the moral obligation to examine the evidence, draw conclusions from this evidence, and act upon our convictions.”

Melinda Gormley ([email protected]) is Assistant Director for Research at the John J. Reilly Center for Science, Technology, and Values at the University of Notre Dame. Melissae Fellet ([email protected]) is a freelance science writer whose work about chemistry and materials science has been published in New Scientist, Chemical & Engineering News, and Ars Technica.

Recommended reading

“Fallout and Disarmament: A Debate between Linus Pauling and Edward Teller,” Daedalus 87, no. 2, (Spring, 1958): 147-163. http://www.jstor.org/stable/20026443. 

For excerpts and photos from the televised debate, see: “Linus Pauling and the International Peace Movement: A Documentary History,” http://scarc.library.oregonstate.edu/coll/pauling/peace/index.html. 

Educating the Future Workforce

Work ain’t what is used to be, and in the future it won’t be what it is now. Standardization, mechanization, electrification, and now robotification and computerization have driven constant upheaval. At each stage observers have expressed alarm that worker dislocation will create a social nightmare of unemployment and financial ruin. The changes have been disruptive for many workers as jobs disappeared and skills became obsolete, and many communities suffered long-term decline when their dominant industries withered. But over time the economy adjusted, and new and often better-paying jobs were created. Still, many individuals and communities never recovered. The workforce moved from farm to factory to office to telecommuter. Productivity has increased, wealth has grown, many of the most arduous and dangerous jobs have disappeared, and many new and rewarding careers have thrived. The lesson that many draw is that change can be hard on some individuals, and even lead to significant social and economic disruption, but that it is beneficial to the society in the long-run. We can expect to see some people hurt by current and anticipated changes, but we should have faith that society will adapt to technological progress and that in the end society as a whole will be better off.

But is it true that nothing is different this time? It seems certain that technological progress will make the economy more productive, but is it also likely to lift all workers and enhance economic equity? And what about the pace of change? The transformation of agriculture took place over many decades, giving social systems time to adapt. It has become a truism that the pace of technological advance is accelerating. Has our ability to transform social systems also become more efficient? If not, the next stage in the evolution of work might prove for the displaced workers, and we might find it more difficult to train people for the new jobs that could be created.

MIT professors Erik Brynjolfsson and Andrew McAfee argue in The Second Machine Age that we are on the cusp of a powerful wave of technology-driven innovation and productivity growth that will create innumerable opportunities for exciting and well-paying work. George Mason University professor Tyler Cowen is less sanguine in his book Average Is Over: Powering America Beyond the Age of the Great Stagnation. He foresees marvelous benefits for the top 10-15% of high achievers and dire consequences for everyone else. French economist Thomas Piketty looks at the interplay of technological change and larger economic trends in Capital in the 21st Century. He sees advances in technology and improvements in education as forces that promote social equity, but he worries that they are too weak to offset deeper changes in the structure of the economy that are leading to greater concentration of wealth and income at the top.

MIT labor economist David Autor thinks that most commentators overestimate what robots and computers can do and shortchange the tacit knowledge and integrated skills that humans possess. He acknowledges that machines are ideal for routine tasks, but he finds that most jobs entail non-routine tasks at which humans are superior. He expects workers to enhance their productivity and value by enlisting the help of machines of various types to perform the routine aspects of their jobs, giving them more time to complete the non-routine tasks. Harvard University economist and former treasury secretary Lawrence Summers looks at what is currently happening in the labor market as a sign that trouble is already here. He says that as a student he learned and accepted the sanguine view that technology would boost productivity and ultimately benefit workers. But he found it easier to accept that view as a student when the unemployment rate of U.S. males between the ages of 25 and 54 was 6%. It is now 16% and seems likely to persist at that level. Summers observes that this significantly changes the bargaining power of workers and employers and reduces the likelihood that this large group of workers will see salary growth. He also wonders why U.S. productivity growth has been relatively slow in spite of this alleged revolution in workplace technology.

The most recent optimistic views come from Thomas H. Davenport and Julia Kirby’s article “Beyond Automation” in Harvard Business Review and a study by the McKinsey Global Institute, “A Labor Market That Works: Connecting Talent with Opportunity in the Digital Age.” Davenport and Kirby follow David Autor’s line of thinking in arguing that technology does not replace but enhances human labor, and they develop a variety of strategies by which people can position themselves to benefit from technological advances. Unfortunately, the examples they provide refer largely to the highly skilled and educated workers in the top 20% of the wage distribution. The McKinsey study makes a more practical point about how new technology will assist in social adaptation to change. Information technology will facilitate the process by which employers find workers with the right skills and workers learn what skills are needed in the new labor market. This could be important at all levels of employment.

And to generalize, generalization is ill-advised. The effects of change will differ among industries, across the nature and level of skill, and among demographic groups. You will not find a simple answer to what the future holds in the articles that follow. Instead, you will see snapshots that provide a perspective on specific aspects of the question. Margaret Hilton looks at the implications of changing employer needs for the type of basic education we should be providing. Can schools convey the broad mix of competencies that future workers will need? Mark Schneider explores the changing world of credentials that are becoming alternatives to a four-year college degree. Is a one-year certificate in a technical field a sound foundation for a successful career, or is a four-year degree becoming a prerequisite for middle class income? Donna Ginther examines the top rung of the education ladder: Ph.D.s in engineering and the physical, life, and social sciences. Their career paths have long been quite predictable, but are they now likely to experience the thrills of disruptive innovation?

Although the pessimists and optimists disagree on how well society will adjust to technology-driven changes in the workplace, they all agree that change is coming and adaptation will be needed. One key to successful adaptation will be attention to the specifics. What’s needed will differ between manufacturing and health services, between elementary school and high school, between middle-skill workers and highly educated professionals. And the results will be uneven, providing ample evidence for future optimists and pessimists to continue their debate.

Preparing Students for Life and Work

Employers, educational policymakers, and others are calling on schools and colleges to develop “21st century skills,” such as teamwork, problem-solving, and self-management that are seen as valuable for success in the workplace, citizenship, and family life. For example, 19 states are working with the Partnership for 21st Century Skills, a nonprofit association of education and business leaders, to infuse 21st century skills into their curricula, assessments, and teaching practices. On Capitol Hill, bipartisan sponsors in the House and Senate introduced the 21st Century Readiness Act, with the goal of including attention to 21st century skills in the pending reauthorization of the Elementary and Secondary Education Act. The bipartisan Congressional 21st Century Skills Caucus, formed by Rep. Thomas Petri (R-WI) and Rep. Dave Loebsack (D-IA) in the 112th Congress, provides a forum for discussions about the importance of 21st century skills in preparing all students for college, career, and life.

The Achilles heel of the growing movement for 21st century skills is the absence of agreement on what these skills are. The Partnership for 21st Century Skills framework includes four learning and innovation skills—critical thinking, communication, collaboration, and creativity—along with life and career skills, information, media, and technology skills, and core academic subjects. The Hewlett Foundation focuses on “deeper learning,” including mastery of core academic content, critical thinking and problem solving, collaboration, effective communication, self-directed learning, and an academic mindset. Other individuals and groups see information technology skills as most valuable for career success. To address this lack of a shared vision, the National Research Council (NRC) conducted a study of deeper learning and 21st century skills and published the report Education for Life and Work: Developing Transferable Knowledge and Skills in the 21st Century (National Academies Press, 2012).

To understand the importance of 21st century skills, including their relationship to learning of school subjects, the committee reviewed research not only from the cognitive sciences, but also in social psychology, child and adolescent development, economics, and human resource development. As a first step toward improved definitions, the committee clustered various lists of 21st century skills into three broad domains of competence:

• The cognitive domain, which involves reasoning and memory;
• The intrapersonal domain, which includes the capacity to manage one’s behavior and emotions to achieve one’s goals (including learning goals); and
• The interpersonal domain, which involves expressing ideas and interpreting and responding to messages from others.

To prepare for an uncertain 21st century economy, where workers can expect to frequently change jobs (whether as a result of layoffs or to explore new opportunities), students need to go beyond memorizing facts and taking multiple-choice tests. They need deeper learning, which the committee defined as the process through which a person becomes capable of taking what was learned in one situation and applying it to new situations—in other words, learning for transfer. Through the process of deeper learning, students develop 21st century competencies—transferable knowledge and skills. In contrast to a view of 21st century skills as general skills that can be applied across various civic, workplace, or family contexts, the committee views these competencies as aspects of expertise that are specific to—and intertwined with—knowledge of a particular discipline or topic area. The committee uses the broader term “competencies” rather than “skills” to include both knowledge and skills. In mathematics, for example, these competencies include content knowledge together with critical thinking, problem solving, constructing and evaluating evidence-based arguments, systems thinking, and complex communication.

Competency counts

The committee set out to identify the competencies that were most valuable for success at work, in education, and in other settings. It found that the research base is limited, based primarily on correlational rather than causal studies. Thus, the committee could draw only limited conclusions:

• More studies have focused on cognitive competencies than on interpersonal and intrapersonal competencies, showing consistent, positive correlations (of modest size) with desirable educational, career, and health outcomes. For example, many studies have found that higher levels of general cognitive ability are correlated with higher occupational levels and earnings.
• Among interpersonal and intrapersonal competencies, conscientiousness (a tendency to be organized, responsible, and hardworking) is most highly correlated with desirable educational, career, and health outcomes. Anti-social behavior, which has both intrapersonal and interpersonal dimensions, is negatively correlated with these outcomes.

In contrast to the limited evidence of the importance of cognitive, interpersonal, and intrapersonal competencies, the committee found much stronger evidence of a causal relationship between years of completed schooling and higher adult earnings, as well as better health and civic engagement. Moreover, individuals with higher levels of education appear to more readily learn new knowledge and skills on the job.

The strong relationship between increased years of schooling and higher adult earnings suggests that formal schooling helps develop a mixture of cognitive, interpersonal, and intrapersonal competencies that is not measured by current academic tests, but is valued by the labor market. Further research is needed to examine this hypothesis. This would entail longitudinal tracking of students with controls for differences in individuals’ family backgrounds and more studies using statistical methods that are designed to approximate experiments.

Many educators are well aware of the importance of nurturing broader competencies, as reflected in their development of the Common Core State Standards in mathematics and English language arts and the Next Generation Science Standards, based on the NRC Framework for K-12 Science Education. All three standards documents highlight the importance of a cluster of cognitive competencies including critical thinking and non-routine problem solving. For example, the mathematics standards and the NRC science framework include a “practices” dimension, calling for students to actively use their knowledge to tackle new problems, while the English language arts standards call on students to synthesize and apply evidence to create and effectively communicate an argument. Although all three documents expect students to develop the cognitive and interpersonal competencies needed to construct and evaluate an evidence-based argument, the disciplines differ in their views of what counts as evidence and what the rules of argumentation are.

The Common Core standards and the NRC framework represent each discipline’s desire to promote deeper learning and develop transferable knowledge and skills within that discipline. For example, the NRC framework aims to develop science knowledge that transfers beyond the classroom to everyday life, preparing high school graduates to engage in public discussions on science-related issues and to be critical consumers of scientific information. At a more basic level, deeper learning of a school subject over the course of a school year develops durable, transferable competencies within the subject that students can apply when continuing to learn about that subject in the following school year.

However, research is lacking on how to help learners transfer competencies learned in one discipline or topic area to another discipline or topic area or how to combine and integrate competencies across disciplines.

Research to date has identified a number of practices and principles that contribute to deeper learning and transfer within a discipline or topic area. Instruction for deeper learning begins with a focus on clearly delineated learning goals along with assessments to measure student progress toward and attainment of the goals. It requires the development of new curriculum and instructional programs that include research-based teaching methods, such as:

• Using multiple and varied representations of concepts and tasks, such as diagrams, numerical and mathematical representations, and simulations, combined with activities and guidance that support mapping across the varied representations.
• Encouraging elaboration, questioning, and explanation—for example, prompting students who are reading a history text to think about the author’s intent and/or to explain specific information and arguments as they read—either silently to themselves, or to others.
• Engaging learners in challenging tasks, while also supporting them with guidance, feedback, and encouragement to reflect on their own learning processes and the status of their understanding.
• Teaching with examples and cases, such as modeling step-by-step how students can carry out a procedure to solve a problem and using sets of worked examples.
• Priming student motivation by connecting topics to students’ personal lives and interests, engaging students in collaborative problem solving, and drawing attention to the knowledge and skills students are developing, rather than grades or scores.
• Using formative assessments to: make learning goals clear to students; continuously monitor, provide feedback, and respond to students’ learning progress; and involve students in self- and peer-assessment.

But will these same methods be effective in developing interpersonal and intrapersonal competencies, such as teamwork or self-regulation? It seems likely that they would, but the reality is that we don’t have the evidence to support this assumption. The research challenge is to first more clearly define and develop reliable methods for assessing students’ intrapersonal and interpersonal competencies in order to study and compare various approaches for developing them. A new NRC study of assessing intrapersonal and interpersonal competencies will begin to address this challenge.

The political environment creates additional barriers to the creation of an educational system that fosters deeper learning and transferable 21st century competencies. Many states are now pushing back against the Common Core standards that were initiated by a wide coalition of education and business leaders. Even in states that have embraced the new standards, the extent to which 21st century competencies will be taught and learned will depend on developments in educational assessment. Although research indicates that formative assessment by teachers supports deeper learning and development of transferable competencies, current educational policies focus on summative assessments that measure mastery of content. State and federal accountability systems often hold schools and districts accountable for improving student scores on such assessments, and teachers and school leaders respond by emphasizing what is included on these assessments. Traditionally, education leaders have favored the use of standardized, on-demand, end-of-year assessments. Composed largely of multiple-choice items, these tests are relatively cheap to develop, administer, and score; have sound psychometric properties; and provide easily quantifiable and comparable scores for assessing individuals and institutions. Yet, such standardized tests have not been conducive to measuring and supporting deeper learning in order to develop 21st century competencies. In the face of current fiscal constraints at the federal and state levels, policymakers may seek to minimize assessment costs by maintaining lower-cost, traditional test formats, rather than incorporating into their systems relatively more expensive, performance- and curriculum-based assessments that may better measure 21st century competencies.

Recent developments in assessment may help to address these challenges. Two large consortia of states, with support from the U.S. Department of Education, have developed new assessment frameworks and methods aligned with the Common Core State Standards in Mathematics and English Language Arts. These new assessment frameworks include some facets of 21st century competencies represented in the Common Core State Standards, providing a strong incentive for states, districts, schools, and teachers to emphasize these competencies as part of disciplinary instruction. Next Generation Science Standards have been developed based on the NRC framework, and assessments aligned with these standards are currently under development. If the new science assessments include facets of 21st century competencies, they will provide a similarly strong incentive for states, districts, schools, and teachers to emphasize those facets in classroom science instruction.

Next steps

Because 21st century competencies support deeper learning of school subjects, their widespread acquisition could potentially reduce disparities in educational attainment, preparing a broader swath of young people for successful adult outcomes at work and in other life arenas. However, important challenges remain. For educational interventions focused on developing transferable competencies to move beyond isolated promising examples and flourish more widely in K-12 and higher education, larger systemic issues and policies involving curriculum, instruction, assessment, and professional development will need to be addressed. As noted previously, new types of assessment systems, capable of accurately measuring and supporting acquisition of these competencies will be needed and this, in turn, will require a sustained program of research and development. In addition, it will be important for researchers and publishers to collaborate in developing new curricula that incorporate the research-based design principles and instructional methods we described previously. Finally, new approaches to teacher preparation and professional development will be needed to help current and prospective teachers understand how to support students’ deeper learning and development of 21st century competencies in the context of mastering core academic content. If teachers are to not only understand these ideas, but also translate them into their daily instructional practice, they will need support from school and district administrators, including time for learning, shared lesson planning and review, and reflection. States and school districts should implement these changes, while private foundations and federal agencies should invest in research on assessment and curriculum development to foster widespread deeper learning and development of 21st century competencies.

Margaret Hilton, a senior program officer of the Board on Science Education and the Board on Testing and Assessment at the National Research Council, was study director for the report Education for Life and Work: Developing Transferable Knowledge and Skills in the 21st Century.

From the Hill – Summer 2015

“From the Hill” is adapted from the e-newsletter Policy Alert, ­published by the Office of Government Relations of the American Association for the Advancement of Science (www.aaas.org) in Washington, DC.

House Appropriations smiles on NASA, trims NSF

In mid-May the House Appropriations Committee passed on a voice vote the FY2016 Commerce, Justice, Science, and Related Agencies (CJS) appropriations bill, which includes funding for the National Science Foundation (NSF), National Aeronautics and Space Administration (NASA), and the Department of Commerce, which houses the National Oceanic and Atmospheric Administration (NOAA) and the National Institute of Standards and Technology (NIST).

The overall bill would provide a small increase in research and development (R&D) funding from FY2015, but less than the administration requested, as House appropriators continue to abide by sequester-level spending caps mandated by the Budget Control Act. Whereas NASA R&D picked up slightly more than the president’s request, NSF fared less well compared to FY2015 levels:

• The total NSF budget would increase by 0.7%, which is 4.3% below the request.

• The total NASA budget would increase by 2.9%, the same level as the request.

• The total NIST budget would decrease by 1.0%, which is 23.6% below the request.

• The total NOAA budget would decrease by 5.2%, which is 13.6% below the request.

NSF. The committee fell short of the president’s request for NSF by $329 million, with appropriations below the request for research activities, education programs, and agency operations. The associated committee report specifically “directs NSF to ensure that Mathematical and Physical Sciences; Computer and Information Science and Engineering; Engineering; and Biological Sciences comprise no less than 70% of the funding within Research and Related Activities.” These accounts comprise what committee chair John Culberson (R-TX) has termed “core science,” meaning that geological and social and behavioral research would be significantly cut.

Additionally, the committee provided $146 million for neuroscience and cognitive science activities at NSF, including the BRAIN Initiative; this represents a $46 million increase above FY2015 and includes $3 million for the establishment of a National Brain Observatory working group. The committee also provided $176.6 million for NSF’s advanced manufacturing investments, matching the request and providing a slight increase above FY2015, and kept flat the Experimental Program to Stimulate Competitive Research (EPSCoR), rather than granting the increase sought by the administration.

An amendment offered by Rep. David Price (D-NC) sought to increase NSF funding to match the administration request. Although Price’s amendment failed, Culberson suggested during the proceedings that extra funding could be provided to NSF should a broader deal on discretionary spending be reached.

NASA. The committee granted an overall $519 million increase to NASA, thereby matching the president’s request and allowing the agency budget to keep pace with inflation. It would also keep NASA’s budget ahead of the overall spending curve, as the discretionary budget is slated to increase by only 0.2% in FY2016. However, spending would be reallocated among various agency programs to achieve the “balanced portfolio” sought by Republicans.

The Science Mission Directorate (SMD) remains a source of enduring tension, given claims that SMD’s budget has received a disproportionate increase and that it is taking on climate science programs better left to NOAA and U.S. Geological Survey. Under the committee’s CJS bill, the Earth Sciences program would be cut and funding shifted to Planetary Science, building on previous Republican efforts to increase funding for a robotic mission to Europa. Rep. Mike Honda (D-CA) offered and subsequently withdrew for lack of support an amendment to increase funding for NASA Earth Science to equal the president’s request.

The committee would also eliminate an increase sought for NASA’s Space Technology program, which contains funding for the administration’s controversial proposal for an Asteroid Redirect Mission. The Aeronautics Research Directorate would be cut, but not by as much as requested.

NASA’s human exploration activities, which include the Orion crew vehicle and Space Launch System (SLS) program, would receive a substantial increase from the president’s request, continuing the long-standing dispute between Congress and the administration over the importance of building SLS. The House appropriations bill does provide an increase for Commercial Spaceflight in FY2016, but 19.6% less than what the president had hoped for.

NIST and NOAA. Appropriations for the two major R&D agencies in the Department of Commerce fell far short of what the administration requested for next fiscal year.

NIST funding would remain 23.6% below the president’s request, and any increases would be limited to NIST’s laboratory programs, including those for cybersecurity and disaster resiliency. Funding for the Hollings Manufacturing Extension Partnership would stay flat, and the committee declined a requested increase for the National Network for Manufacturing Innovation, a multi-agency initiative to establish public-private manufacturing institutes across the country.

NOAA received considerably less than what the president requested. Where divergence occurs to a significant degree is within the Office of Oceanic and Atmospheric Research, which carries out climate research. All other accounts would be funded well below the request, and only the National Weather Service and the National Marine Fisheries Service would see any gains. Additionally, the committee granted funding increases for the Geostationary Operational Environmental Satellite R-Series Program (GOES-R) and the Joint Polar Satellite System (JPSS).

An amendment introduced by Rep. Sam Farr (D-CA), which was accepted during markup, will add $7.2 million for the NOAA Bay Watershed and Training education program, offset by a cut to the NOAA administrative account. Rep. Marcy Kaptur (D-OH) also offered and withdrew an amendment that would have boosted funding at NOAA.

Research replication. Included in the report language accompanying the appropriations bill is a requirement for NSF to develop guidelines to “ensure that research conducted by NSF grantees is replicable.” The FY2015 appropriations bill also included language regarding replication, but it required only that NSF report how it would “improve research methods, increase research transparency, and allow increased scientific replicability.” Under the new legislation, the agency must submit an implementation plan to Congress within 180 days of the bill’s enactment into law.

The full House approved the committee’s bill. On June 11 the Senate Appropriations Committee approved their FY 2016 Commerce, Justice, Science Appropriations bill, which includes funding for NASA, NIST, NOAA, and NSF. The committee did not release full details, but it indicated that it differs from the House bill in a few small ways. The increase, for NASA is slightly smaller; NIST receives a small increase whereas the House cut its budget; NOAA also receives a slight increase in contrast to the significant cut in the House bill; and NSF funding is kept constant, whereas it received a slight increase from the House.

In a move intended to force a deal on sequester-level spending, Senate Minority Leader Harry Reid (D-NV) said that Democrats plan to filibuster every spending bill in the Senate. The current spending caps, established by the Budget Control Act, remain unpopular with both parties, but Democrats are particularly eager to eliminate the caps before appropriations progress much further. The president has also issued a veto threat for every spending bill that abides by sequester-level spending so far.

Bipartisanship not dead

Despite the controversies surrounding much science legislation, in May the House of Representatives passed six science and technology bills that were reported out of the House Science, Space, and Technology Committee. Bills included: H.R. 1561, the Weather Research and Forecasting Innovation Act of 2015, introduced by Vice-Chairman Frank Lucas (R-OK) and Rep. Suzanne Bonamici (D-OR.); H.R. 1119, the Research and Development Efficiency Act, introduced by Research and Technology Subcommittee Chair Barbara Comstock (R-VA) and co-sponsored by ranking member Eddie Bernice Johnson (D-TX); H.R. 1156, the International Science and Technology Cooperation Act of 2015, introduced by Research and Technology Subcommittee ranking member Dan Lipinski (D-IL) and co-sponsored by Research and Technology Subcommittee Vice-Chairman John Moolenaar (R-MI); H.R. 1162, the Science Prize Competitions Act, introduced by Oversight Subcommittee ranking member Don Beyer (D-VA) and co-sponsored by Oversight Subcommittee Vice-Chairman Bill Johnson (R-OH); H.R. 1158, the Department of Energy Laboratory Modernization and Technology Transfer Act of 2015, introduced by Rep. Randy Hultgren (R-IL) and co-sponsored by Rep. Ed Perlmutter (D-CO); and H.R. 874, the American Super Computing Leadership Act, introduced by Rep. Randy Hultgren (R-IL) and co-sponsored by Rep. Eric Swalwell (D-CA).

Hill addendum

Energy Title of the COMPETES bill introduced

A bipartisan group of seven senators introduced an authorization bill for the Department of Energy’s Office of Science and its Advanced Research Projects Agency—Energy (ARPA-E). The bill (S. 1398) is a sharp contrast to the America COMPETES Reauthorization Act that passed the House of Representatives. The bipartisan proposal calls for 4% annual increases from current levels for the Office of Science and ARPA-E for FY2016–FY2020 and consolidates a small subset of programs from the original America COMPETES Acts that were never appropriated funds. The group of bipartisan co-sponsors, led by Sen. Lamar Alexander (R-TN), includes Sen. Lisa Murkowski (R-AK), the chair of the Senate Energy and Natural Resources Committee, as well as Sen. Cory Gardner (R-CO), Sen. Chris Coons (D-DE), Sen. Maria Cantwell (D-WA), Sen. Dianne Feinstein (D-CA) , and Sen. Martin Heinrich (D-NM).

House appropriations committee approves transportation funding

The House Appropriations Committee approved on a voice vote the FY2016 Transportation, Housing, and Urban Development appropriations bill. According to current American Association for the Advancement of Science (AAAS) estimates, the bill provides $858 million to the Department of Transportation for R&D activities in FY2016, which is 18.2% below the president’s request. Most individual science and technology programs received flat or reduced funding from FY2015 levels, though the Federal Aviation Administration’s NextGen program received $931 million, good for an 8.6% increase and only 2.6% short of the request. The bill now moves to the House floor.

House approves defense authorization bill

The House of Representatives voted to approve the FY2016 National Defense Authorization Act by a 269 to 151 vote. According to current AAAS estimates, the bill would authorize $69.8 billion in base research, development, test, and evaluation funding for the Department of Defense in FY2016, virtually matching the administration request and providing an increase of 9.5% above FY2015 levels. Science and technology spending would vary little from FY2015 levels. The bill has been criticized for using war funding as a means to sidestep the current defense spending caps, as laid out in the congressional budget resolution, and the White House has threatened a veto the bill for this reason. The Senate Armed Services Committee, meanwhile, also voted to mark up and approve its own bill in a closed session.

21st Century Cures Act advances

The 21st Century Cures Act, launched with the aim of advancing the discovery, development, and delivery of new medical interventions, passed out of subcommittee last week and will now advance to the full House Energy and Commerce Committee. The bipartisan bill covers a wide range of territory and includes several provisions relevant to the National Institutes of Health (NIH), including language seeking to boost the NIH budget.

Senate PATENT Act introduced

A bipartisan group of leaders on the Senate Judiciary Committee introduced the Protecting American Talent and Entrepreneurship Act (PATENT Act). Committee Chair Chuck Grassley (R-IA) and ranking member Patrick Leahy (D-VT), along with committee members John Cornyn (R-TX), Chuck Schumer (D-NY), Mike Lee (R-UT), Orrin Hatch (R-UT), and Amy Klobuchar (D-MN), introduced the bill to address abusive patent litigation. The new version of the bill includes changes regarding fee structures that elicited a moderately favorable response from the university community, but the higher education groups have not formally endorsed the measure.

OSTP releases draft National Space Weather Strategy

The White House Office of Science and Technology Policy (OSTP) has released a National Space Weather Strategy, which aims to set strategic goals for enhancing U.S. preparedness for space weather events. Space weather refers to the interactions between the sun and earth via the solar wind, and more dramatic flares and eruptions that occur intermittently. The intense radiation, particularly from the most violent events, has the capacity to disrupt essential infrastructure such as the telecommunications system and electrical grid.

NIH reaffirms stance on gene-editing of human embryos

NIH Director Francis Collins has released a statement reaffirming that “NIH will not fund any use of gene-editing technologies in human embryos.” This statement is in response to a recently published study in which Chinese scientists used CRISPR-Cas9 technology to genetically modify a nonviable human embryo.

NIH releases Alzheimer’s agenda

NIH released recommendations for a research agenda related to Alzheimer’s disease, a top priority for the administration. Overarching themes include the expansion of integrative, data-driven research approaches; the development of computational tools and infrastructure to enable large-scale analysis of patient data; and the use of wearable sensors and other mobile health technologies. The agenda also calls for engaging patients, caregivers, and citizens as equal partners in Alzheimer’s disease research.

Toxic substance bills moving forward

The House Energy and Commerce Committee marked up its version of the Toxic Substances Control Act (TSCA) Modernization Act of 2015 (H.R. 2576). The bipartisan bill unanimously passed the Subcommittee on Environment and the Economy in May and has support from the American Chemistry Council, among others. The House majority leader has already announced that he expects H.R. 2576 to reach the House floor before the Independence Day recess begins in the last week of June. The Senate Environment and Public Works Committee, meanwhile, passed its own bipartisan version at the end of April, though with some vocal dissent from Sens. Barbara Boxer (D-CA) and Ed Markey (D-MA).

Wiki-ki Yay? Not so Fast

For people who work with information, Wikipedia is endlessly fascinating because of its swift emergence as an everyday source of usually reliable facts and observations about people, places, and things. Yet despite the curious self-organizing, egalitarian, and noncommercial features of Wikipedia, and its vast popularity among students and professionals alike, there’s never been a scholarly book-length introduction to how the Web encyclopedia works.

Until now. In Common Knowledge? An Ethnography of Wikipedia, Dariusz Jemielniak, a Polish scholar of organizations and management, provides a revealing insider’s account of Wikipedia. It runs so counter to the general belief about the encyclopedia that the book might be titled “Everything You Think You Know about Wikipedia Is Wrong.” Contrary to the belief of fans of Wikipedia that the online encyclopedia is an openly editable agglomeration of the world’s published information—a democratic artifact containing the “wisdom” of a highly organized and intelligent “crowd”—the process of construction and reconstruction depends on a hierarchical bureaucracy, with relatively few contributions from novices and newcomers. The bulk of the editorial work, it seems, comes from a core group of veteran editors who keep close watch on one another through digital means.

Jemielniak, an associate professor of management at Kozminski University in Warsaw, wasn’t looking to challenge the received wisdom about Wikipedia when he joined as a volunteer editor in 2007. His book, the result of six years of study, is part scholarship and part memoir, the result of his decision to become a participant observer in what is arguably the most important collaborative community, not only in cyberspace, but anywhere in the world.

Print encyclopedias, of course, have a long history. Since the Enlightenment, they have played a crucial role in codifying and transmitting essential knowledge about the world. Diderot, the 18th-century Frenchman of letters, created the first Encyclopédie in the 1750s, describing in a subtitle his innovative work as “a Systematic Dictionary of the Sciences, Arts, and Crafts” (or so Wikipedia informs me).

Encyclopedias became a staple of intellectual and literary life. By the 20th century, encyclopedias were carefully controlled collective endeavors led by distinguished editors, in which the reputations of contributors were as important as what their entries conveyed. The Encyclopedia Britannica illustrated the apotheosis of the vast multivolume, multipurpose tome, offering an answer to virtually any question. With less fanfare, hundreds if not thousands of important encyclopedias also populated the reference sections of libraries and the homes of esoteric scholars and middle-class suburbanites alike.

The Web killed the encyclopedia. Call the death a consequence of creative destruction. In a monumental unintended consequence, the rise of the Web altered the way knowledge is stored, codified, and valued. If technological change were only about substitution, about replacing one system with another, the Web should have spawned an online encyclopedia run and written by experts, most likely scholars and scientists, probably based at universities. Those scholars and scientists would probably be paid an honorarium for their written contributions, which would carry their byline and perhaps even a brief bio. The very cost of updating entries would mean that the Web encyclopedia would be more rigid and static than a living document, but trivial corrections, of errors and misapprehensions, would be made quickly and often.

Or so Jimmy Wales believed. Yes, the founder of Wikipedia had a false start, which unfortunately Jemielniak doesn’t say much about. It seems that Wales, now legendary for his visionary understanding of how total strangers could be mobilized to create and update a living account of all aspects of civilization, at first launched an encyclopedia written by experts, built around a model very similar to print encyclopedias from long ago. The only signal difference would be that the encyclopedia Wales envisioned would exist online, available only on a screen rather than in a bound volume. In short, what Wales called “Nupedia” would be pure substitution.

To his surprise, Wales received little interest from experts whom he thought might altruistically share their knowledge in exchange for the notional appreciation of a better-informed society. After about a year of pushing his Nupedia, Wales shifted gears. In January 2001, he launched Wikipedia, conceived of as a Web encyclopedia for which anyone could write and edit. Wales embraced a real-world experiment in harvesting the best of the proverbial “wisdom of crowds,” thus deeming experts an unaffordable luxury—and dangerously antidemocratic and elitist to boot. Within a year, the new Wikipedia offered 20,000 original articles. In its second year, the community wrote and edited 100,000 more articles. Thus Wales, on his second try, had “an instant success,” Jemielniak notes.

In time, Wikipedia became unstoppable, the Web equivalent of a personal research assistant. Pranks and vandal attacks, while requiring Wikipedia to become less porous, also reinforced its growing significance. (Who, after all, sprays graffiti on walls no one sees?) In 2013, the vaunted Encyclopedia Britannica stopped publishing a print edition. And now, wholly dependent on the ease and speed of an online encyclopedia, knowledge workers and curiosity seekers from around the globe could only complain about what appeared to many to be the high wall that had come to surround the process of constructing and maintaining Wikipedia entries. Not only did a thicket of rules and norms prevent newcomers from readily contributing to the encyclopedia, the daily grind of reversing acts of vandalism, well-intended lapses, sly reputation enhancements, and sheer stupidity made Wikipedia less open and more rigid.

In recounting the rise of Wikipedia, Jemielniak justly celebrates the achievements of the open-collaborative movement of knowledge organization. But he questions the price. A “growing body of rules tends to increase the power of old-timers and deter newcomers from participating in Wikipedia,” Jemielniak writes. Trust in procedures trumps the real-world credentials of contributors, and “encourages non-experts to participate.” But “Wikipedians” find it “practically impossible,” Jemielniak says, to use their contributions to the encyclopedia to advance their public reputation or career. No articles are signed, after all, and edits can be made without approval or even review of the principal author. These practices alienate experts, and “Wikipedia already suffers from low expert retention,” Jemielniak notes.

Not only are professional credentials and established reputations irrelevant, even real identities matter little. “Editing with a consistent identity” seems more important than participating with an accurate identity, Jemielniak writes. “Users are allowed to introduce themselves any way they want,” which “provides a clean slate for all participants.” While seeking to remove barriers to engagement and provide a greater diversity of experience and input, anonymity creates the potential for mischief and fraud.

Jemielniak recounts a revealing episode in which an active contributor, who embellished his personal biography to enhance the appearance of the quality of his knowledge of religious subjects, was quoted in a prominent article about Wikipedia in The New Yorker. In the aftermath, the Wikipedian was unmasked, and the widespread practice of contributors telling fibs about themselves to others in the community came under scrutiny. Jemielniak recounts how Wales tried and failed to curtail misrepresentation by contributors in their behind-the-scenes dealings with other editors. The backlash from Wikipedians who wished to preserve the ability to mask their true identities overwhelmed Wales, and he relented, though only after the perpetrator named in The New Yorker unceremoniously departed from the Wikipedia ranks.

To be sure, there’s something amazing going on when “expertise [is] no longer embodied in a person but in a process,” and in “the wisdom of crowds,” as Jemielniak (and many others) insist. But this crowd isn’t representative of human diversity, unfortunately. What Jemielniak worryingly labels as Wikipedia’s “disregard for formal expertise” distressingly carries over to categories of race and gender. More than 90% of the community’s editors and writers are men. Female participation may be declining. So small are the numbers of nonwhite contributors that Wikipedia doesn’t even bother to publish a breakdown.

Whereas Wikipedia promotes a discourse of equality and openness, the community, because of its lack of diversity and patterns of centralized control, seems closed to newcomers.

These shortcomings are no mere artifact of political correctness. Whereas Wikipedia promotes a discourse of equality and openness, the community, because of its lack of diversity and patterns of centralized control, seems closed to newcomers, which is especially troubling because the Wikipedia community would seem to need an infusion of newcomers if it wishes to attract the talents of women and people of color. Fears of elitism and benign autocracy abound. Near the end of his study, Jemielniak openly worries that “the seemingly chaotic, anachronistic, and laissez-faire organization” of Wikipedia “is, in fact, susceptible to extremely tight control through observation and registration of all behavior.”

So tight is that control that Jemielniak repeatedly likens participating in Wikipedia to serving time in a high-security prison. “Wikipedia resembles a Panopticon…everybody is watched by everybody else, and all actions remain on the record forever,” he writes. According to Jemielniak, the coterie of active editors who maintain a close eye on each other and other contributors have, perhaps unintentionally, created a conservative climate where members worry—even obsess—about offending others in their tribe as much as they toil to maintain the quality of their entries. The implication is that an environment of hypersurveillance, while ensuring accountability and enabling members to quickly identify and undo errors, also limits the range and depth of topics on offer.

For all his strengths as a chronicler of Wikipedia, Jemielniak has a few blind spots beyond the stubborn questions around race and ethnicity that he neglects. As a participant as well as an observer, he is sometimes too close to fellow Wikipedians. Because he’s a heavyweight within the Polish-language Wiki-encyclopedia, he draws on many examples from his Warsaw crowd, often with brain-numbing detail. Similarly, although his command of Wikipedia’s sprawling internal procedures is impressive, even breathtaking, his engagement with esoteric internal debates between contributors is tedious and bewildering at times. Finally, because his personal biography—white male geek—tracks the dominant profile of Wikipedians, he does little more than identify homogeneity as a social problem but not as a threat to the character and quality of whatever knowledge Wikipedia provides beyond the quotidian, the immediately verifiable, and the statistical.

He’s also prone to unsupported leaps on the subject of whether “Wikipedia is just one example of a broader revolution in knowledge production.” Here Jemielniak commits a flagrant category error by failing to acknowledge and account for the crucial distinction between the codification of existing knowledge and the creation of new knowledge. Scholarship, after all, is never the mere assembly of what is known but always strives to expand the territory of the known, to help us look at the world anew.

By never establishing and exploring the differences between curation and construction of knowledge, Jemielniak commits a dangerous conflation; he wants to present Wikipedia, and its organizational innovations, as essential to future styles of knowledge production. Yet Jemielniak repeatedly highlights the existence of Wikipedia’s prohibition against introducing any original research into articles. Everything must be sourced and, essentially, presented as secondhand information.

Serving as a broker of knowledge is of course an important achievement for a group of volunteers who are spread across the globe and presenting material in many languages (the English Wikipedia remains by far the largest encyclopedia). But assembling and managing knowledge, however significant, differs substantially from creating new knowledge. In his timely and thorough account of a seminal sociotechnical movement, Jemielniak fails to persuasively argue that a nonhierarchal, anti-elitist organization, working with scant monetary or reputational rewards, can either mount or sustain an enterprise devoted to knowledge creation. For Wikipedia, as for the Internet as a technoscientific system, there remain limits.

G. Pascal Zachary, a professor of practice at Arizona State University, is the author of Show Stopper! The Breakneck Race to Create Windows NT and the Next Generation at Microsoft.

Archives – Summer 2015

Skeletal Reflections

Chico MacMurtrie’s Skeletal Reflections is an interactive robot sculpture that has stored in its memory a library of body postures from classic painting and sculpture. A camera/computer attached to the robot records and analyzes the posture of people viewing the sculpture. When the viewer strikes a pose such as that of Rodin’s The Thinker, the robot also assumes that posture.

MacMurtrie is the artistic director of Amorphic Robot Works (ARW, http://amorphicrobotworks.org), a collective of artists, scientists, and engineers. Currently operating out of Brooklyn, New York, ARW is dedicated to the study and creation of movement as it is expressed in anthropomorphic and abstract robotic forms.

Heirs of the Body

You can’t barf in a Cadwallader, Swaine & Taft conference room, definitely not when a client is due. Even when staring at photos of smiling octogenarian heads stitched to muscular, teenage bodies.

I took a deep breath of filtered air. There were lots of horrors in the world. Mom got blown up. My mentor, “Iron” Lilly, got brain cancer. Anencephalic clones got harvested so rich old men could live longer. The Rules of Professional Conduct still governed.

At least my client opposed transplanting her father’s head onto a clone he grew in China. When she arrived, I’d—

Applebaum, the grizzly bear of a litigator who dumped this case on me, stomped through the door leading a woman with body armor, a crew cut, and a hard-eyed stare.

The woman—bodyguard?—nodded curtly. “Please close the blinds.”

“Uh, pardon me?”

She was so fast that before I finished speaking she’d slid past my armchair, flipped the switch, and dropped hurricane shutters over the 57th-floor view of the harbor. I was a cross-country runner myself, but she’d make a hell of a sprinter.

As the translucent shutters fell, the green-shaded brass library lamps lit. Into the false evening strode another girl, this one dressed in bluejeans and a hooded ballistic vest reaching past her hips. She stalked past Applebaum, dropped her hood, and looked at me, pinning me to my seat with eyes blazing like some Egyptian cobra goddess.

I struggled to my feet anyway. Most Trusts and Estates Department clients were old money. Old money demanded polite, and it was a habit I couldn’t, and didn’t want, to break. “Uh, good afternoon, Ms. Astos. Lucas Pratt at your service.”

I didn’t add, “unwillingly.” Now that my mentor, “Iron” Lilly, was a corpsicle, it was crazy to dream that anybody in lowly Trusts and Estates could force Litigation to handle its own cases. Especially T&E’s last wisp of a partner, old Stiles.

Mara Astos was laughing at me, cobra goddess gone. Blue, blue eyes in a freckled face, long red hair carelessly tied back. Maybe my age, but the super-rich were hard to gauge. “Shoo, Applebaum,” she said, without turning.

He tried to object, probably wanting to estimate how many junior associates he could justify assigning to the case, but Speedy Bodyguard was already herding him out the door.

The client chuckled. “Don’t worry, I’ll do fine alone with your ‘bright, accommodating milksop.”

Milksop? I tried to accommodate my clients as much as possible. I mean, the goal of T&E is to give clients peace of mind, but milksop?

Ms. Astos dropped into the swivel chair opposite mine. “I presume you read the file?”

Every page. However much it turned my stomach. “Uh, what you have is a case of first impression, Ms. Astos, and—”

“Mara.”

“Mara.” Okay. “U.S. law clearly permits organ donation. Nothing on the books prohibits U.S. citizens from breeding a ‘reproductive’ clone in any jurisdiction where it’s lawful. The only law in our favor is the federal definition of ‘human being,’ a political compromise between the right-to-lifers and right-to-choosers. Anencephalic clones meet the definition of ’human being’, and if surgeons ‘kill’ them during a full-body transplant, which depends on—”

“Stop! I don’t care what the law is. You argue what I tell you to argue. I’ll find a judge to buy it.”

Uh. Well, she could just mean forum-shopping. “Sure, whatever you want, so long as it doesn’t violate the Rules of Professional Conduct.”

“You’ll do what I tell you to do.” The cobra goddess was back, scarier than Applebaum.

“Within the Rules?” It came out as a question, but it wasn’t. Really.

She rolled her eyes. “We don’t have time for this. If Daddy doesn’t get his transplant within thirty days, he’s dead. Just stall him. Can you do that?”

Maybe. But dead? “Uh, what exactly is your goal? Are you against using clones for parts,” something I’d be thrilled to work on, “or is it—”

“I want Daddy dead,” she said.

“Dead?”

“Nobody lies to me, ever again. He’s done as puppeteer. Thirty days without the transplant, and I inherit.”

Shit. “Ah, even if we get a preliminary injunction against your dad’s transplant, he could just preserve himself cryonically, right?”

She shrugged. “Not if we freeze his assets first.”

There was that. But, practically speaking, “Uh, doesn’t he have assets all over the world?” Even if we got lucky with a judge, we’d barely have time to freeze his U.S. assets.

She frowned, terrifyingly, at what was obviously a rhetorical question about billionaires who commissioned clones in China. I persevered.

“Uh, unless you catch your father outside of China, in a jurisdiction with the will to extradite, or you have more influence in China than he does, there’s no way we can block him from accessing assets he’s already moved to China.”

The cobra goddess hissed and reared.

“Uh, is your Dad already in China?”

She spat, “Oh, yes, Daddy’s dining with his clone. A week ago, he told me he wanted to see the Stone Forest and the real Shangri-La before he died. Typical half-truth, hiding lies. When he didn’t invite me along, I knew he was up to something. Once I started digging, it didn’t take long to discover what the Lijiang ‘Health Center’ really did. What Daddy really did.”

Crap. A preliminary injunction wouldn’t work. Daddy could transplant before it issued. Could we trick him back into the U.S. by threatening his assets here? Then we might convince a court to penalize whole-body clone transplants so severely that Daddy would prefer freezing to losing his empire. But no court would order Daddy to freeze himself after the transplant.

Another thought niggled. Father and daughter usually went on vacations together? Meaning the bad blood was new? Good T&E lawyers always advised their clients to give themselves time to cool off before disinheriting relatives for recent screw-ups. Shouldn’t that apply to eliminating?

“You usually vacation together?”

“Ever since Mom died. Bastard pretending to be heartbroken… How’s that relevant? Focus on one thing: STOP THE TRANSPLANT!”

“Uh,” I said, actually regretting Applebaum’s departure, “Being in China already kinda scuttles—”

“Fine,” interrupted Speedy. “She’ll accept corpsicle.”

Mara bounced angrily from her chair but didn’t contradict her. “Just erase the man from my life.”

I spent the rest of the afternoon brainstorming how to lure Daddy back onto U.S. soil.

But the real issues kept distracting me.

Why did Mara suddenly hate her father?

How could you not hate somebody who created a clone for parts? I mean, it was legal to gestate a child to create organs for a sick sibling or to get transfusions and even a kidney from your kids, but was it right?

Since Daddy needed the clone’s whole body, our strongest argument was that anencephalic clones met the federal definition of “human being.” Although death row proved that not all human beings had a right to life, it was pretty clear that one human being didn’t have the right to kill another in order to acquire organs.

Except doctors who took organs from probably–
unrevivable donors.

What bothered me most was intentionally breeding a brainless human, even though the courts refused to recognize a cause of action for “wrongful life” (declaring themselves incompetent to value the difference between nonexistence and life in an impaired state). And refused to interfere with deaf parents gene-selecting for deafness and dwarf parents selecting for dwarfism…

But the definition of “human being” meant we won. So long as the clone was gestated in a “mother” and not an artificial womb. So long as the clone “died” during the transplant.

But what if it didn’t “die”? Who knew the result of connecting Daddy’s brain to his anencephalic clone’s brain stem? Dead clone? Brainy clone? Or Siamese twins?

I was the wrong attorney for this case. I’d never win if I made up arguments for the other side. I had to think like a litigator. I needed to eat raw meat. Or at least raw fish.

I ordered (at the client’s expense) a deluxe bento box from Kobeyaki. The two block walk would clear my head.

Kobeyaki was crowded. Even though I’d ordered ahead, I had to stand in line in the dark, tempura-and-cherry-blossom–scented anteroom.

“Pardon me,” a melodious voice said behind me.

I half-turned. It was a pleasant-looking older Asian woman, dressed in a classic pinstripe skirt-suit.

“Ah, I was right!” she crowed delightedly, eyes crinkling. “Lucas Pratt, are you not?”

“Uh, yes,” I said. “I’m sorry, do I know you?”

“I went to Harvard Law School with your mother. I met you as a tiny child. You graduated from Harvard Law too, did you not?”

Words stuck in my throat. Did she know…?

Her smile dimmed. “My deepest condolences. It is almost a year since the accident, is it not?” She reached out to take my right hand in both of hers.

My chest loosened. Of course Mom’s classmates would have read about her death in the alumni magazine. As the lady squeezed my hand I thought…

“Please wake up, Mr. Pratt.”

My eyelids were glued shut, my hands heavier than feed-sacks. I struggled to rub my eyes.

“You remember me, do you not?”

The lady from Kobeyaki. But I was sitting—in an airplane?

I lunged to my feet, but my seatbelt stopped me.

“There is no reason for concern, Mr. Pratt. I am Ms. Gan.”

Ignoring her, I scrabbled at the belt.

“I truly am your mother’s classmate, though I cannot say I ever ‘hung out’ with her, as…”

The damn thing wouldn’t, let, go!

“…she spent all her free time with her family, did she not?”

This mattered how? “Where the fuck am I?”

“Ah, you resemble your mother more when you are frightened,” she said. “So I will answer you as straightforwardly as she would.”

Why couldn’t I get this off? Drugs. She drugged me. Was I even on a plane? Was this even a seatbelt? I tore and pounded at it anyway.

“You cannot unbelt until after we land at Lijiang Airport,” she said. “We provided IV and catheter support on the flight to ensure that you arrive well-rested, well-hydrated, and comfortable. The government-sponsored tour of the Lijiang Health Center will commence in one hour. Afterward, Mr. Astos will lunch with you. This schedule will enable you to return to your office by your usual Saturday arrival time, will it not?”

She was letting me go? Waves of panic subsided in a shiver. Wait, they catheterized me? No, not important. Mr. Astos? Suddenly, I was as hotly and coldly angry as ever my mother could be. “Mr. Astos had me kidnapped?”

“No, Mr. Pratt, my government. But Mr. Astos is a valued entrepreneur, customer, and resident of my country. Our interests coincide in the matter of his daughter’s litigation against his transplant.”

Stupid, stupid, stupid. I should have known this case would be bigger than billionaire v. billionaire. And not only the Chinese would have “interests” at stake. The minute I got home, I needed to chart out all the stakeholders.

“You prefer black coffee and orange juice in the morning, do you not?”

I took long, deep breaths. The opposition might be rougher than I was used to, but apparently the rules of professional courtesy still applied. “Uh, yes, thank you, Ms. Gan.”

She bowed and waved forward a white-jacketed steward.

When we landed and deplaned, I saw that the plane was ballistic. We’d been in space, and I’d missed it. Maybe they’d let me stay awake on the flight back?

Ms. Gan ushered me into the back seat of a limo and we drove away through undulating countryside, forest on our left and crops on our right. Beyond the forest and crops rose jagged cliffs.

“We will pass Lijiang City, capital of the Naxi ethnic minority,” Ms. Gan said. “After crossing Lijiang’s three rivers, we drive over the gorge…” And she kept up the travelogue about the spectacular foothills of Shangri-La until we arrived at Lijiang Health Center.

Driving under the central arch, we stopped in a white-graveled courtyard. The limo doors unlocked and Ms. Gan waved me out. A portcullis clanked shut behind us.

The sun made me squint, but my lungs expanded like they had never tasted air before.

“So, Mr. Pratt,” said Ms. Gan, “you need to see with your own eyes how the clones and surrogates are treated, do you not?” And she whisked me into the bowels of the beast—which was actually a bright, bracing space filled with plants, tantalizing aromas, and smiling faces.

Shy Naxi teenagers dressed in sheepskin capes crowded into a small interview room, competing for jobs as surrogates at the center. Assured Naxi women, speaking English as well as Ms. Gan, told me how surrogacy was their escape from poverty and paternalism. They boasted they spent their pregnancies learning English, Mandarin, and how to manage money. They were raring to try their skills when they turned twenty-six, the mandatory retirement age for surrogates.

“These are the wealthiest women in Yunnan province,” said Ms. Gan. “We place two-thirds of their salary into spendthrift trusts. Would you be interested in the details that prevent fathers and husbands from asserting control over the girls’ money?”

From Ms. Gan’s smug expression, the trusts obviously were her baby. Okay, so they took care of the surrogates. But “Don’t pretend the girls—uh, women—are never abused,” I said.

Ms. Gan shrugged. “Abuse happens in any system administered by humans, does it not? These girls can appeal to me. We greatly improve on reproductive industry conditions prevailing when I sold my own eggs for college expenses.”

She…? And I thought I had crappy college jobs?

I swallowed and let her sweep me to our next stop, where I started to drool. Islands of fruits, vegetables, soups, and yogurt stood among small tables of giggling pregnant ladies in white shirts and navy jumpers.

Ms. Gan led me into the kitchen behind, where sweating chefs yelled and laughed.

She unlocked a door in the far wall, and everything changed.

Quiet pandemonium of half-headed kids. Mostly Asian and white, but black and brown as well. Mostly male. All muscled and roving around in food-spattered white jumpers. Handlers in white scrubs. No laughs. No cries. No eyebrows.

Handlers fed the littler clones. Bigger clones grabbed stuff from a long counter themselves. There was no soup here, but built-in troughs of noodles, fruit, vegetables, yogurt, and fish. The clones swirled in a silence of soft slippers, grotesque Helen Kellers before she met Anne Sullivan.

Ms. Gan was talking. “…so our geneticists enhance the typical anencephalic brainstem with neural structures derived from native trout. This enables the clones to control their movements sufficiently to walk and grasp objects, helping develop their muscles and lung capacity, and, as you see, feed. For control, we add olfactory structures that attract the clones to certain scents.”

Well, I didn’t see any bruises. And though my drool had dried up, their food did smell as good as the food next door. But to live without sensation except smell. No pain, no pleasure, no memory…

“Mr. Pratt?”

I jumped. “Sorry, yes?”

Ms. Gan shook her head. “I said, Mr. Astos is waiting in the outdoor colonnade. Unless you wish to interview more staff who speak English?”

A half-headed toddler swerved toward us, handler in pursuit. Ms. Gan calmly diverted their vector with a shove. I stared at the flat, skin-colored plastic cap sloping from empty eyes to neck. Not Helen Keller. I shuddered. Not even a fish. But from the back, looking so much like children.

“Mr. Pratt?”

Suddenly I wanted to meet that bastard Astos. “Let’s go,” I said.

Astos’s table stood half in bright sunlight and half in deep shade. Daddy himself lounged in a wheelchair on the dividing line.

Was this some bullshit symbolic statement about nothing being black or white? I chose a chair completely in shadow. I wasn’t conceding Astos owned even half the moral high ground.

“Mr. Pratt,” he said, “my condolences on the death of your mother.”

WTF? “Uh, thank you.”

“I met her in negotiations settling the SpaceGas litigation,” he said. “She had Delmonico’s send bowls of fruit salad, four-foot subs, and cheesecakes. Told me straight-out that sharing food raises oxytocin levels and encourages cooperation. So,” he concluded as a chef materialized bearing a huge platter of finger foods surrounding a bowl of yogurt, “I’m following her lead. Please join me.”

The chef placed the platter in the middle of the round table, hot hors d’oeuvres in the sun, cold in the shade. Oh.

Astos dipped a fried something into the yogurt. I tried a tiny shish-kabob of steaming meat and vegetables. Delicious.

“Are you enjoying the yak?”

I nodded, mouth full of spicy wonderfulness. Yak. How cool was that?

“So you have no moral qualms about eating fellow mammals?”

I swallowed. “Uh, no qualms, so long as they’re raised and killed humanely.” I wasn’t an animal rights nut, but animal welfare champion? Definitely. Of course, the line between animal and person had been getting blurrier with discoveries that elephants, dolphins, and certain birds not only understood themselves as identities with pasts and futures, but understood “theory of mind.” Being the cautious sort, I advocated treating those species like Homo sapiens of “diminished capacity.” I certainly wasn’t going to eat or wear anything that worried I was raising it for slaughter.

Of course, anencephalic clones had neither worries nor minds, much less theory of mind. Which meant Astos would ask…

“So how are anencephalic Homo sapiens different?”

I put down my literal yak and dug in my figurative heels. “For lots of people, the difference is the soul. Homo sapiens are supposed to have souls, while other species don’t.”

“Do you believe that?”

“Irrelevant. We need to respect those who do.” I was going to ignore the fact that Hindus and Buddhists believed all species had souls.

“To the exclusion of helping mistreated ethnic minorities like the Naxi, who we all agree are thinking, feeling people? To the exclusion of saving lives of people we all agree have hearts and minds and hopes?”

“Okay, okay,” I said. “There has to be a balance.”

“So how is my balance wrong?”

The man was a fiend. He was making me ask and answer my own questions. I could say that intentionally depriving a fetus of its potential for mindfulness was prima facie wrong. But if it didn’t have a soul, why was it wrong? How many human organs did you have to grow in one sack before it was wrong to harvest them?

Where organs were grown couldn’t be the touchstone. I mean, except for sects believing test-tube babies lacked souls. The center’s surrogates were too well treated to argue about. And artificial wombs were coming….

Was anencephalic cloning wrong because only a fortunate few could afford to grow new bodies? Or if it wasn’t limited to a fortunate few, wrong because it would exacerbate overpopulation? But didn’t a fringe argue against all medical advances on that basis?

Or was the real question more basic: What, in this day and age, was a politically sustainable allocation of scarce resources among stakeholders?

In emergency rooms, we followed the time-hallowed practice of triage, which in that setting beat out the generally more popular “first come, first served,” “might makes right,” and “he who pays the piper calls the tune” traditions. For organ donation, though, the official preference was closer to “he who will make best use of the organ” wins it.

But for whole-body transplants, wouldn’t that usually favor the old? Wouldn’t that violate the rights of the young to their fair share of life, liberty, and the pursuit of property? The Constitution never imagined “human beings” having the right to eternal life, liberty, and property on Earth. But if not eternal, how long?

Astos ate his lunch and watched me debate myself, silent. My head was going to explode. It was worse than debating with Mom. And the hot food was getting cold.

But this wasn’t a family dinner. And Astos wasn’t my father.

It wasn’t my job to judge between Daddy and his clone. It was my job to use all lawful means to pursue his daughter’s objectives.

“Respectfully, sir, it doesn’t matter what I think. What matters is what your daughter thinks. And if you can’t convince her, then what matters is whether I can convince a bunch of judges that your actions violate current law, policy, and the public interest.”

Astos dropped his chop sticks and shook his head. “Damn law school brainwashing. I’d hoped for better from you. Please, enjoy your lunch.” And he powered his wheelchair backward, turned away from the table, and purred down the dark colonnade.

But then he stopped. “How was Mara when you met with her?”

“Uh, furious?”

He bowed his head. “Of course. Please tell her I’m sorry. Tell her it wasn’t just for myself.”

“What wasn’t—“

“Tell her.” He purred away.

I forced myself to eat another shish kabob. He wanted me to convey personal messages? He thought I should let my personal values, whatever they were here, compromise my actions as an attorney? Well, screw him. And screw section 8 of the Preamble to the New York Rules of Professional Conduct.

Back in the limo beside Ms. Gan, we rolled down mile after mile of forest to the river valley. We passed Lijiang City before Ms. Gan broke the silence.

“Your response to Mr. Astos was correct, Lucas. Your loyalty is to Ms. Astos. But in all family quarrels it is best to encourage settlement before litigation, is it not?”

I knew that. What about this case kept making me forget it? “I’ll contact Ms. Astos as soon as I reach my office,” I said. “Any chance I could stay awake for the flight?”

“My regrets, Mr. Pratt. Security does not permit.”

I woke up Saturday morning in my apartment, dressed only in running shorts. It was 10 o’clock. Plenty of time for my usual run to the office. I’d wait until I was sitting at my desk in One Chase before deciding whether the China trip was a hallucination.

I had hit my stride, lungs sucking in the air filtered through my nose plugs, missing Lijiang’s fresher air, when a long-legged black guy in a “Free the Enhanced®” t-shirt overtook me and slowed to my pace.

“IRS,” he said, flashing me a holo badge from under his shirt. “Any ill effects from your trip?”

I groaned and slowed.

“No, don’t break pace,” the IRS guy said. “The Chinese still have you under surveillance.”

“What’s the IRS interest?” I asked. Maybe I needed a new route to One Chase. But this one passed under the oldest trees planted downtown.

“Please, Mr. Pratt, the one percent. Astos dies, we get a nice chunk. One-percenters start living forever, we run out of money before Congress grows the balls to change the law.”

True. I really needed to finish my stakeholders chart, yesterday.

“So, the Chinese turn you?”

I stopped dead. “Fuck off,” I said. “My client is Mara Astos.”

Mr. IRS jogged backwards a couple of strides and grinned. “All I wanted to hear,” he said. And disappeared faster than my best sprint.

I badly needed to talk to somebody, and Lilly was gone. Mom was gone. I showered, changed clothes, and knocked on Old Stiles’ half-open office door.

“Come.”

His rumpled gray hair barely showed above the stacks of papers on his desk. I edged between stacks strewn around the carpet and perched on the one empty chair. A lot of the files on Stiles’ desk were Lilly’s.

“Well?”

“Uh, sir, this case from Applebaum—”

“How can I help?” He waved at his desk. “In five minutes or less?”

Five minutes? My heart instantly accelerated past 100 bpm.

“Four minutes,” said Stiles. “Stakeholder summary? Just the major players.”

Right. “Mara wants her dad out of her life and control of the family business. Dad wants to transplant his head onto the body of his anencephalic clone in China so he won’t die in a month. And wants Mara in his life. U.S. voters who believe in souls want everything they think is a “living human being” to be off limits for transplants. The U.S.-IRS wants estate taxes. The Chinese want the revenue from the clone and transplant business. The Naxi minority, ditto. I have no idea what anencephalic clones want.”

Stiles didn’t even blink, just smoothed his gray hair. “So what’s the hang-up?”

What’s the hang-up? Did I mention the Chinese kidnapped me? No, and I couldn’t if I didn’t want him to think I was crazy. “Um, there’s no way to get an injunction before Dad gets the transplant. And afterwards, all the legal and practical cards are stacked against Mara.”

“Injunction? Are you a zero-sum litigator who needs to prove he’s right and everybody else is wrong, regardless of the cost to the client?”

My mouth dropped open. All that came out was “Applebaum?”

“Forget Applebaum. Unless you want to switch to Litigation.”

“Uh, no?”

“No? Then act like a T&E attorney.”

Act like a—?

Stiles sighed and shook his head. “Lilly was desperate, but it was wrong of her to let you litigate her case. Granted, your ‘Schrodinger’s Cat Trust’ brilliantly balanced cryonics stakeholder interests, but did litigating ruin you, Pratt?”

Lilly was wrong?

“Don’t look so stricken, boy. Think. What’s T&E’s superpower?

“We’re counselors, Pratt. Advisers. Not hired guns. We help clients find peace of mind. Take a breath and do it.” And he disappeared behind his stacks.

Back in my own office, I pondered peace of mind. For that, a negotiated agreement was always better than litigation.

Mara said she’d accept corpsicle Dad and control of the family assets outside China. But Dad would never agree to delay the transplant, and if that was successful, no court would require him to risk cryonic preservation. And then Dad would fight for control of all the family assets.

So what was our leverage against Dad? And what, short of cryonic preservation and complete control of assets outside China, would give Mara peace of mind? And not force the other stakeholders to challenge the settlement?

I charted the stakeholders and their interests, excluding Applebaum’s. I stared at the chart. And smiled.

The Cadwallader long-distance conferencing room was state of the art. You could smell the Lijiang clinic.

So it was like we were all sitting in the same room, except nobody in New York could shoot anybody dead in China. Which was good, given Mara’s glare.

In Lijiang, Mr. Astos sat at a small bamboo conference table, Ms. Gan beside him. Astos’s wheelchair bristled with IV bags. Chinese in scrubs hovered, adjusting whatever, walking in and out of sensor range.

At Cadwallader, I sat at the head of the glass table. Mara fulminated to my right, Speedy grim behind her armchair.

On my left, IRS Man fiddled while Applebaum burned. But Old Stiles sat solidly on a chair against the wall, “guarding your back since Lilly can’t.”

Whatever their reservations, everybody but the principals already endorsed my settlement proposal.

“Going for the sympathy bid?” asked Mara, waving at her father’s med-tech festooned wheelchair.

“No, just showing you the truth, for once, as you keep demanding,” said Mr. Astos.

“Oh, now you’re saying you did it to protect me?”

“Yes,” said Daddy. “Look.”

He lifted his chin imperiously and a handler led his white-clad clone into view. “This is my clone, made with your Aunt Lynn’s eggs.” Then another handler led a second clone into view. A female clone.

I gagged.

“So no, I did not ‘steal’ your eggs for myself, whatever your security reports. I took them to clone you. So I wouldn’t lose you like your mother.”

“YOU HAD NO RIGHT! YOU LIED! ‘STD-prevention contraceptive implants’ so I COULD ‘CONTROL MY BODY’ WHILE YOU WERE TAKING MY EGGS!”

Holy crow. Holy—

Stiles was out of his chair, arms around sobbing Mara. “Wrong actions, right reasons,” he muttered soothingly. “Awful. Unforgivable were he anyone but your father, stupid with grief.”

It was falling apart. Like Mom. Like Lilly. Again.

Mara pushed Stiles away. “NO ONE controls me, ever again. I’ll—”

NO! My fist smashed onto the table. It cracked. Everybody winced. “Ah, uh, listen! How about you control him instead! Without freezing him.”

Mr. Astos grabbed Ms. Gan’s arm. Guess she hadn’t told him anything besides we were talking settlement. But if Mara agreed to what the Chinese already accepted, for practical purposes, it didn’t matter.

Speedy was whispering fiercely in Mara’s ear. “Fine. I’ll listen,” Mara said.

I fixed my best cobra stare on her. Stiles harrumphed. I rearranged my face into what Mom called my puppy eyes. “Uh, how would you feel about a younger brother?”

Mara shrank back from me like I’d cracked.

“Really, it’s not crazy. What if your father acknowledges his clone as his son? Then donates his head to him? Daddy’s declared legally dead, and the clone becomes your fifteen-year-old brother and ward. You’re executrix of Daddy’s estate and you control everything until your new ‘brother’ turns twenty-one. Then he gets half.”

I looked back and forth between Mara and her father. “Get it? There’s something for everyone. Dad gets the transplant without legal penalties and without losing Mara. For six years, Mara gets control of everything, including Dad’s moral reeducation. After that, she still keeps half, plus a brother.”

Nobody said no. Applebaum actually looked the unhappiest, contemplating the loss of epic litigation fees.

“The U.S. gets estate taxes and doesn’t interfere with citizens booking the Lijiang Health Center. No changes to existing law, just an IRS opinion letter providing clones the status of ‘heirs of the body’.”

I waved my hands. “Everyone can keep debating when death occurs, what collections of organs grown in what conditions have a soul, and the ethics of designing disabilities into embryos.”

Daddy released Ms. Gan’s arm and snorted. Mara covered her face with her hands. But neither of them said no.

T&E ruled.

Claudia Casser ([email protected]), a graduate of Harvard Law School, worked as an antitrust litigator and a corporate in-house counsel before retiring to write and raise her children.

Climate Clubs to Overcome Free-Riding

Climate clubs are a policy option that will put pressure on countries to participate in global agreements—or pay a price.

Much progress has been made by scientists and economists in understanding the science, technologies, and policies involved in climate change and reducing emissions. Notwithstanding this progress, it has up to now proven difficult to induce countries to join in an international agreement with significant reductions in emissions.

The Kyoto Protocol was an ambitious attempt to construct an international climate change agreement to harmonize the policies of different countries. High-income countries agreed to limit their emissions to 5% below 1990 levels for the 2008-2012 budget period. Under the protocol, important institutional features were established, such as reporting requirements and methods for calculating the relative importance of different greenhouse gases. The most important innovation was an international cap-and-trade system for emissions as a means of harmonizing policies among countries through equalizing the market price of carbon dioxide (CO2) emissions.

But countries did not find the Kyoto Protocol economically attractive. The United States withdrew in 2001. The protocol did not attract any new participants from middle-income and developing countries. As a result, there was significant attrition in the coverage of emissions under the protocol. Also, emissions grew more rapidly in non-covered countries, particularly developing countries such as China. The protocol as first designed would have covered 63% of global emissions in 1990, but the actual scope in 2012 was barely one-fifth of world emissions. Analyses showed that the Kyoto reductions, even if indefinitely extended, would have a limited impact on future climate change. It died a quiet death, largely unnoticed and mourned by few, on December 31, 2012.

The Kyoto Protocol ran aground because of the tendency of countries to free-ride on the efforts of others for global public goods. This tendency is rooted in international law, but nations have overcome free-riding in other areas. Because climate change is an extreme example of a global public good, it poses unique challenges. I propose a “club” model as the most fruitful approach to overcoming free-riding. The current approaches, starting with the Kyoto Protocol, have little chance of success unless they adopt some of the strategies associated with the club model of international agreements.

The nature of global public goods

Most of economic life involves the voluntary exchange of private goods such as bread or blue jeans. These are commodities consumed by one person that directly benefit no one else. However, many activities involve spillovers or externalities among producers or consumers. An extreme case of an externality is a public good. Public goods are commodities for which the cost of extending the benefits to an additional person is zero and where it is impossible or expensive to exclude individuals from enjoying the benefits.

More precisely, public goods have the two key properties—non-rivalry and non-excludability. Non-rivalry denotes that the consumption of the public good by one person does not reduce the quantity available for consumption by another person. Take global positioning systems as an example. These are used for hiking, missile guidance, and to find a restaurant. These are public goods because people who use them are not reducing the value of signals for others. The second feature of a pure public good is non-excludability. This means that no person can be excluded from benefiting from or being affected by the public good (or can only be excluded at a very high exclusion cost). In the case of smallpox eradication, once smallpox was eradicated, no person could be excluded from the benefits. Herd immunity from vaccines is an important and little-understood public good that is one of the important reasons for mandatory vaccination.

Efficient production of public goods requires collective action to overcome the inability of private agents to capture the benefits.

The critical economic point about public goods is that private markets do not guarantee efficient production. In this respect, production of public goods such as GPS signals or herd immunity differs from production of bread. Efficient production of public goods requires collective action to overcome the inability of private agents to capture the benefits.

The inefficiencies are the greatest for global public goods, whose benefits are spread most widely across space and time. Consider issues as different as greenhouse warming and ozone depletion, terrorism and money laundering, the discovery of antibiotics and the control of nuclear weapons. These are global public goods because their benefits are indivisibly spread around the entire globe. These are not new phenomena. However, they are becoming more important in today’s world, because of rapid technological change and of the sharp decline in transportation and communication costs.

The Westphalian dilemma and global public goods

Although global public goods raise no new analytical issues, they do encounter a unique political hurdle because of the structure of international law. Whenever we encounter a social, economic, or political problem, one of the first questions concerns the level at which the problem should be addressed. We expect households to deal with children’s homework assignments and taking out the trash; we expect local or regional governments to organize schools and collect the trash; we expect national governments to defend their borders and manage their currencies.

For the case of global public goods, there exists today no workable market or governmental mechanism that is appropriate for the problems. There is no way that global citizens can make binding collective decisions to slow global warming, to curb overfishing of the oceans, to efficiently combat Ebola, to form a world army to combat dangerous tyrants, or to rein in dangerous nuclear technologies.

The decision-making difficulties of global public goods raise what might be called the Westphalian dilemma. National governments have the actual power and legal authority to establish laws and institutions within their territories; this includes the right to internalize externalities within their boundaries and provide for national public goods. Under the governing mechanisms of individual countries, whether they are acts of democratic legislatures or despotic decrees, steps can be taken to raise taxes or armies and command citizens to clean their air and water.

By contrast, under international law as it has evolved in the West and then the world, there is no legal means by which disinterested majorities, or supermajorities short of unanimities, can coerce reluctant, free-riding countries into mechanisms that provide for global public goods. Participants of the Treaty of Westphalia recognized in 1648 the Staatensystem, or system of sovereign states, each of which was a political sovereign with power to govern its territory. As the system of sovereign states evolved, it led to the current system of international law under which international obligations may be imposed on a sovereign state only with its consent.

Because nations, particularly the United States, are deeply attached to their sovereignty, the Westphalian system leads to severe problems for global public goods. The requirement for unanimity is in reality a recipe for inaction. Particularly where there are strong asymmetries in the costs and benefits (as is the case for nuclear non-proliferation or global warming), the requirement of reaching unanimity means that it is extremely difficult to reach universal, binding, and effective international agreements. Whether bargaining can lead to such treaties is examined shortly.

To the extent that global public goods are increasingly important in the decades ahead, one of our major challenges is to devise mechanisms that overcome the bias toward the status quo and the voluntary nature of current international law in life- or civilization-threatening issues. Just as national laws recognize that consumer sovereignty does not apply to children, criminals, and lunatics, international law must come to grips with the fact that nations acting under the Westphalian system cannot deal effectively with critical global public goods.

Free-riding as an obstacle to international agreements

As we look at climate change, the dilemmas raised by their global nature take a particular form. Slowing climate change requires expensive national investments in reducing CO2 and other greenhouse gas emissions. But the benefits are diffuse in space and time. Emissions reduced anywhere benefit people everywhere, and most of the benefits come to generations in the future, perhaps the distant future.

The concentrated costs and dispersed benefits provide strong incentives for free-riding in current international climate agreements. Free-riding occurs when a party receives the benefits of a public good without contributing to the costs. In the case of the international climate change policy, countries have an incentive to rely on the emissions reductions of others without taking proportionate domestic abatement. The failure of the Kyoto Protocol, and the difficulties of forging effective follow-up regimes, is largely due to free-riding.

As suggested by the earlier discussion, whereas free-riding is pervasive and is particularly difficult to overcome for global public goods. Arrangements to secure an international climate treaty are hampered by the lack of ability to induce reluctant nations to join international agreements. In essence, all international agreements are essentially voluntary.

Clubs as a mechanism to overcome free-riding

In light of the failure of the Kyoto Protocol, it is easy to conclude that international cooperation is doomed to failure. This is the wrong conclusion. In spite of the obstacles of international law, nations have in fact overcome many transnational conflicts and spillovers through international agreements. There are over 200,000 United Nations (UN)-registered treaties and actions, which are presumptive attempts to improve the participants’ welfare. Countries enter into agreements because joint action can take into account the spillover effects among the participants. Two interesting cases are the decline of war and free trade.

Each of these has its fascinating history, and I will first consider the case of the emergence of a free and open trading system. For most of recorded history, trade was dominated by barriers: quotas, tariffs, blockades, and other obstacles. The United States had an average tariff rate of close to 20% in the early 1930s, and this was typical of other countries. Since that time, several rounds of multilateral trade negotiations have led to a situation that is today close to free trade for the United States. This trend has spread around the world in the last two decades. The rapid growth in Latin America, China, and India is testimony to the power of international competition and technological openness. One important part of the success is that the World Trade Organization (WTO) has a club structure in which countries have both rights and obligations, and one of the important obligations is low tariffs.

A second success of the current international system is the decline in organized military violence around the world. This trend is described in a magnificent book on the subject, Angels of Our Better Nature, by Steven Pinker. Because of the vivid imagery of television and the Internet, the fall in war deaths is sometimes underappreciated. There are many sources of the decline of the lethality of war. Research by political scientists John Oneal and Bruce Russett suggests that the combination of growing democracy, expanding trade linkages, the role of alliances, and the growth of international organizations are important contributors to the declining frequency and lethality of war. The North Atlantic Treaty Organization (NATO) is another club model, where countries have dues (obligations on their defense spending and cooperation) and enjoy the security benefits.

These two achievements are a reminder that patient efforts to improve relations among nations are not a fruitless task. In these and other cases, the tendency toward free-riding associated with the Westphalian system has been overcome through the mechanism of clubs.

So what is a club? Although most of us belong to clubs, we seldom consider their structure. A club is a voluntary group deriving mutual benefits from sharing the costs of producing a shared good or service. The gains from a successful club are sufficiently large that members will pay dues and adhere to club rules to gain the benefits of membership.

The theory of clubs is a little-known but important corner of the social sciences. The major conditions for a successful club include the following: that there is a public-good-type resource that can be shared (whether the benefits from a military alliance or the enjoyment of a golf course); that the cooperative arrangement, including the dues, is beneficial for each of the members; that non-members can be excluded or penalized at relatively low cost to members; and that the membership is stable in the sense that no one wants to leave.

The basic idea that is suggested here is that we can make progress in international climate agreements if we adopt the club model rather than the current voluntary model. The idea of a climate club should be viewed as an idealized solution to the free-riding problem. Like free trade or physics in a vacuum, the climate club described here will never exist in its pure form. Rather, it is a blueprint that can be used to understand the basic forces at work and sketch a system that can overcome free-riding.

In brief, the club is an agreement by participating countries to undertake harmonized emissions reductions. The agreement envisioned here centers on an “international target carbon price” that is the focal provision of an international agreement. For example, countries might agree that each country will implement policies that produce a minimum domestic carbon price of $25 per ton of CO2. Countries could meet the international target price requirement using whatever mechanism they choose—carbon tax, cap-and-trade, or a hybrid.

A key part of the club mechanism (and the major difference from all current proposals) is that non-participants are penalized. The penalty suggested here is uniform percentage tariffs on the imports of non-participants into the club region. Calculations suggest that a relatively low penalty tariff rate will induce widespread participation among countries as long as the target carbon price is less than $50 per ton.

Game theory in international bargaining

An important aspect of the climate club, and a major difference from current proposals, is that it creates a strategic situation in which countries acting in their self-interest will choose to enter the club and undertake high levels of emissions reductions because of the structure of the incentives. To understand the nature of the incentives and strategies, I discuss the application of game theory to international environmental treaties.

There is a large body of literature on the strategic aspects of international environmental agreements, including those focused on climate change. One important strand is the analytical work on global public goods. The clear message is that without special features the outcome will be a prisoners’ dilemma or tragedy of the commons in which there is too little abatement.

This analysis usually takes place in the framework of non-cooperative (NC) game theory. In the NC framework, countries act in their national self-interest. So when a country designs its environmental or macroeconomic or labor-market policies, it considers the impacts on its own citizens and largely ignores the impacts on other countries. Although the idea of countries acting in their self-interest may seem narrow-minded or parochial, it is actually the foundation of democratic theory. Most of the world’s ills (think particularly of wars) arise because countries, or more often their leaders, do not act in their countries’ national self-interest. For national public goods with minimal cross-border spillovers, the world’s welfare is appropriately optimized when countries act in their self-interest. The problems we consider here arise for global public goods, where the NC approach leads to inefficient outcomes.

In light of the failure of the Kyoto Protocol, it is easy to conclude that international cooperation is doomed to failure. This is the wrong conclusion.

Analysis of NC agreements (either one-shot or repeated) leads to three major conclusions for climate change. First, the overall level of abatement in the NC equilibrium will be much lower than in the efficient (cooperative) strategy. A second and less evident point is that countries will have strong incentives to free-ride by not participating in strong climate-change agreements. Finally, the difficulty of escaping from a low-level, NC equilibrium is amplified by the intertemporal trade-off because the current generation pays for the abatement while future generations are the beneficiaries of lower damages. To a first approximation, international climate policy as of 2015 looks like a NC equilibrium.

Elements of treaties

Non-cooperative outcomes assume that countries never bargain to improve the outcomes. Might coalitions of countries form cooperative arrangements or treaties that improve on NC arrangements? This question has been extensively studied analytically using game theory, through modeling, and by examination of history.

Theoretical and empirical studies indicate that coalitions concerned with global public goods tend to be fragile and unstable. More precisely, these studies find virtually universally that coalitions tend to be either small or shallow, a result I will call it the “small-coalition paradox.”

Here is the background. Suppose that countries can form treaties to provide global public goods, whether for climate change or public health or financial regulation or whatever. A successful agreement would require the participation of most countries. However, to be stable, each country must determine that participation—which requires investments with large national costs but diffuse benefits, has a higher payoff than non-participation. The problem is that stable coalitions tend to have few members; therefore, as the number of countries rises, the fraction of global emissions covered by the agreement declines. Studies by Scott Barrett have found, based on a comprehensive review of existing environmental treaties, that there are very few treaties for global public goods that succeed in inducing countries to increase their investments significantly above the NC levels. Moreover, the ones that do succeed include external penalties.

This point was foreseen more than three centuries ago in a discussion by David Hume on collective action and free-riding:

Two neighbors may agree to drain a meadow, which they possess in common; because ‘tis easy for them to know each other’s mind; and each must perceive, that the immediate consequence of his failing in his part, is, the abandoning the whole project. But ‘tis very difficult, and indeed impossible, that a thousand persons shou’d agree in any such action; it being difficult for them to concert so complicated a design, and still more difficult for them to execute it; while each seeks a pretext to free himself of the trouble and expence, and wou’d lay the whole burden on others. (Hume, A Treatise of Human Nature, Section VII, 1739)

How can we understand the small-coalition paradox? Here is the intuition for climate change: Clearly, two countries can improve their welfare by combining and raising their abatement (or carbon price) to the level that would maximize their joint welfare. Just as with Hume’s neighbors, either country is worse off by dropping out. The 2014 agreement between China and the United States to join forces in climate policy might be interpreted as an example of a small, bottom-up coalition.

Does it follow that, by increasing the number of countries in the treaty, this process would accumulate into a grand coalition of all countries with efficient abatement? That conclusion is generally wrong. The problem arises because, as more countries join, the level of abatement, and its costs, becomes ever higher, and ever further from the NC level. The discrepancy gives incentives for individual countries to defect. When a country defects from an agreement with many countries, the remainder coalition (of many-minus-one countries) would reoptimize its levels of abatement. The revised levels of abatement would still be well above the NC levels for the remainder coalition, while the defector free-rides on the abatement of the remainder coalition. The exact size of the stable coalitions would depend on the cost and damage structure as well as the number of countries, but for most analyses using realistic numbers, stable coalitions are small and perform only slightly better than the NC equilibrium.

As noted above, the syndrome of free-riding along with the international norm of voluntary participation appears to doom international climate agreements such as the Kyoto Protocol. The suggestion here is that a club structure, where external sanctions are imposed on non-members, will be necessary to induce effective agreements.

Crafting effective sanctions

Although it is easy to design potential international climate agreements, the reality is that it is difficult to construct ones that are effective and stable. Effective means abatement that is close to the level that passes a global cost-benefit test. The concept of stability used here is that a coalition is stable if no group (sub-coalition) among the countries can improve its welfare by changing its participation status. The small coalition paradox motivates the current approach. The goal here is to find a structure that is stable and has a large number of participants for a wide variety of country preferences, technologies, and strategies.

Both theory and history suggest that some form of sanction on non-participants is required to induce countries to participate in agreements with high levels of abatement. A sanction is a governmental withdrawal, or threat of withdrawal, of customary trade or financial relationships. A key aspect of the sanctions analyzed here is that they benefit senders and harm receivers. This pattern contrasts with most cases, where sanctions impose costs on senders as well as receivers and thereby raise issues of incentive-compatibility.

The major potential instrument is sanctions on international trade. Two approaches to trade sanctions might be considered. A first approach, and one that has been widely advocated and examined, is called carbon duties and would put tariffs on the imports of non-participants in relation to the carbon content of these imports. For technical reasons, I do not suggest this route. A second approach, called uniform penalty tariffs, would apply the same tariff rate to all imports from non-participating countries. Under this approach, participating countries would levy a tariff (perhaps 2%) on all imports from non-participants. This mechanism has the advantage of simplicity and transparency, although it does not relate the tariff specifically to the carbon content of the import.

A major feature of tariff-sanctions is that they are incentive-compatible. Many sanctions have the disadvantage that they penalize the penalyzer. For example, if Europe puts sanctions on Russian energy companies, this is likely to raise energy prices in Europe, hurt European consumers, and therefore impose costs on Europe as well as Russia. The tariff-sanction mechanism analyzed here imposes costs on the non-participating country but benefits participants that levy the penalty tariffs. Moreover, because tariffs apply bilaterally, they can support an efficient equilibrium for global public goods for a large number of countries.

Modeling a climate club

To understand how a climate club would operate, it is necessary to move beyond description to analytical and numerical modeling of the incentives and behavior of regions with realistic economic and geophysical structures. The challenge of analyzing and modeling the science and policy associated with global warming is particularly difficult because it spans many disciplines and parts of society. An important approach to bringing the different fields together has been the development of integrated assessment models (IAMs). These pull together in a single model a wide variety of geophysical, economic, and political relationships so that projections, analyses, and decisions can consider simultaneously all important endogenous variables at work. IAMs generally do not aspire to have the most detailed and complex representation of each of its components. Rather, they aspire to have at a first level of approximation the most important relationships and ones that can operate simultaneously and with reasonable accuracy.

In the major study on which this article is based, I describe an integrated-assessment model (the Coalition-DICE or C-DICE model) of economics, tariffs, and climate change that examines the effects of different potential climate clubs. The model has modules for output, emissions, damages, trade, and tariffs. It operates for 15 regions of the world (such as the United States, the European Union, China, India, Russia, and Brazil). It is a relatively compact model that is based on more comprehensive economic models of trade, emissions, and impacts. In the C-DICE model, countries first decide whether or not to participate in the climate club. Then, they choose either a NC/low-abatement policy of no participation; or choose a cooperative/high-abatement policy with participation according to club rules. Countries that are in the climate club impose penalty tariffs on the imports of non-participants into the club.

The key question for countries is whether to join the club. If they are in the club, they must pay the dues in terms of expensive abatement (represented by the abatement associated with a high domestic carbon price). If they are out of the club, they incur minimal abatement costs but must face penalty tariffs from members of the club.

The C-DICE model is designed to find whether or not countries join a coalition of high-abatement countries, and to find stable coalitions. It examines 44 different “regimes,” where a regime is defined as an international target carbon price and penalty tariff rate. The assumed target prices are $12.5, $25, $50, and $100 per ton CO2, and uniform penalty tariffs range from 0percent to 10%. For reference purposes, the U.S. government estimates the global social cost of carbon (or the damage imposed by an additional ton of CO2 emissions) to be around $35 per ton of CO2. In most models, a carbon tax of this magnitude would lead to emissions reduced 15 – 20% relative to a business-as-usual path.

Note that countries continue to act in their self-interest. But their self-interest must now take into account the costs and benefits of being in the coalition of participating regions. I note that modeling endogenous coalition formation is a computation problem of high complexity for which no efficient algorithms exist; it can generally be solved for only a small number of regions.

Some illustrative results

I close by highlighting some of the conclusions of the modeling studies of a climate club. The first major result is to confirm in the C-DICE model that a regime without trade sanctions will dissipate to the low-abatement, NC equilibrium. This is true starting from a random selection of participating countries. More interestingly, starting from the Kyoto coalition (Annex I countries as defined by the Kyoto Treaty) with no sanctions, the coalition always degenerates to the NC structure with minimal abatement.

A second surprising result is that, when trade sanctions are imposed, the climate club structure generates stable coalitions for virtually all sets of parameters.

A next set of results concerns the impact of different climate club parameters on the participation structure. Figure 1 shows the number of participating regions for different carbon prices and tariff rates. For the lowest target carbon prices ($12.5 and $25 per ton of CO2), full participation and efficient abatement are achieved with relatively low tariffs (2% or more). However, as the target carbon price rises, it becomes increasingly difficult to achieve full participation. For a $50 per ton target carbon price, the club can attain 90+% efficiency with a tariff rate of 5% or more. However, for a target carbon price of $100 per ton, it is difficult to induce more than the NC level of abatement.

Figure 2 shows the globally averaged carbon prices associated with different regimes. Again, note that for the two lower carbon prices, the actual price is at the target for very low tariffs. However, with the high target carbon price, the participation rate is low and the actual global carbon price and emissions control rates are hardly above the NC levels.

What is the pattern of gains and losses? The benefits of a climate club are widely distributed among countries. A few regions have losses in some regimes. However, the losses are small relative to gains for other regions. There are no regimes with aggregate losses.

A paradoxical result is that all regions would prefer a climate club regime with penalties and modest carbon prices to a regime with no penalties. This is the case even for countries that do not participate. The reason is that the gains from strong mitigation measures of participants outweigh the losses from the tariffs for non-participants—as long as the tariff rate is not too high. This powerful result indicates that a regime with sanctions should be attractive to most regions.

The analysis shows how an international climate treaty that combines target carbon pricing and trade sanctions can induce substantial abatement. The modeling results indicate that modest trade penalties on non-participants can induce a coalition that approaches the optimal level of abatement as long as the target carbon prices are not too high. The attractiveness of a climate club must be judged relative to the current approaches, where international climate treaties are essentially voluntary and have little prospect of forging agreements that can effectively slow climate change.

William Nordhaus ([email protected]) is Sterling professor of Economics at Yale University. This article is based on his Henry and Bryna David Lecture at the National Academy of Sciences on October 2, 2014, as well as on “Climate Clubs” in the recommended reading.
Recommended reading

William Nordhaus, The Climate Casino (New Haven, CT: Yale University Press, 2013).

William Nordhaus, “Climate Clubs: Overcoming Free-Riding in International Climate Policy,” Presidential Address to the American Economic Association, published in American Economic Review 5, no. 4 (2015): 1339–1370, available at http://dx.doi.org/10.1257/aer.15000001.

William Nordhaus, “Paul Samuelson and Global Public Goods,” in Michael Szenberg, Lall Ramrattan, and Aron Gottesman, eds., Samuelsonian Economics (Oxford, UK: Oxford University Press, 2006), 88-98.

Paul Samuelson, “The Pure Theory of Public Expenditure,” The Review of Economics and Statistics 36, no. 4 (1954): 387-389.

Todd Sandler and John T. Tschirhart, “The Economic Theory of Clubs: An Evaluative Survey,” Journal of Economic Literature 18, no. 4 (1980): 1481-1521.

Forum – Summer 2015

Whither universities?

In “A New Model for the American Research University” (Issues, Spring 2015), Michael M. Crow and William B. Dabars argue that public and private research universities are stuck in a pattern of incremental change, when the times call for radical reform. Research universities, long the gold standard of higher education in the United States, must be scaled up and freed from current design constraints that hamper their ability to produce the kind and quantity of education and research the nation needs at this moment in its history. The new model they describe advocates a dramatic expansion of enrollment at research universities to encompass the top 25% of the nation’s most academically talented students instead of the 5 to 6% they educate now. While noting research universities’ contributions to the knowledge economy, Crow and Dabars criticize the research enterprise in general for being “carried out largely in isolation from the socioeconomic challenges faced by most Americans.” Thus, their model organizes research—more of which they feel should be cross-disciplinary—around societal problems rather than the traditional disciplines. Perhaps the most serious design flaw they see in today’s research universities is the academic department, which, they maintain, impedes the flow of interdisciplinary collaboration within and beyond the university’s walls.

Their recent book from which this article is drawn, Designing the New American University, comes at a time when the nation’s research universities are searching for new models adequate to the realities they face. This is one of its appealing aspects: The authors offer a bold prescription for change, buttressed with a historical perspective on the evolution of the research university; a strong defense of the role of the arts, humanities, and social sciences; and recent theorizing about knowledge and knowledge institutions. They also provide a valuable real-life example of their model, reflected in the changes that Crow has orchestrated as president of Arizona State University (ASU) over the past decade or so. Anyone interested in alternative futures for the research university will want to follow this ongoing experiment in institutional redesign.

It is clear that Crow and Dabars’ model is tailored to what they regard as the nation’s 100 or so principal research universities. What is not entirely clear is whether they intend their model to be for a few of those institutions or for all of them. Although they write that restructuring initiatives are “necessarily sui generis because at bottom there should be nothing generic about institutional design,” their title and much of the book suggest that their model has wide applicability. But there are at least two reasons for caution.

First, the overwhelming majority of public research universities are not, as the authors argue, deliberately curtailing enrollment as a strategy for ensuring their elite standing in national and international rankings. The University of California and public research universities like it are prepared to grow in order to meet student demand and national needs. Yet scaling up the proportion of students they enroll to 25%—an enormous increase—would serve neither students nor institutions. Students can choose from a wide mix of excellent colleges and universities, including ones that offer opportunities for undergraduate research; there is no reason to believe that research universities are the only avenue to a 21st-century education. The costs of expansion would be enormous, at a time when the moderating of the Great Recession has done little to ease the fiscal struggles of higher education nationwide. Per-student funding in the states is still 27% below what it was in 2008. (The University of California system now receives the same level of support from the state that it did in 1999, even though it educates 83,000 more students and 42% of its undergraduates are low-income Pell Grant recipients.) If current national budget trends continue, according to the Pell Institute for the Study of Opportunity in Higher Education, in 10 years there will be states in which higher education receives no funding at all. Innovations and adaptations—massive online open courses, or MOOCs, for instance—have a role in addressing this fundamental problem, but a real solution requires significant new investments of money. It is not just a question of organization and will.

Second, although the university research enterprise can always be improved, it does not need to be reinvented. Cutting-edge, cross-disciplinary work is thriving as never before at U.S. universities, and so are partnerships with governments, regions, and private industry. Further, a reorientation away from basic research and toward more attention to broad societal challenges or specific local needs is an idea with profound implications that should be carefully considered. Since the federal government’s decision at the end of World War II to make universities the center of the nation’s research enterprise, the United States has come to rely almost exclusively on these institutions for the fundamental discoveries on which the flow of new knowledge and new applications depends. Moving toward a strongly problem-solving approach could diminish that role, which has yielded spectacular dividends for society.

Crow and Dabars offer many ideas for change that are stimulating and useful. But we should also keep in mind how inventive and resourceful research universities have been in overcoming the obstacles that strew the path to innovation. They still are.

Richard C. Atkinson

President Emeritus

University of California

Patricia A. Pelfrey

Senior Research Associate, Center for Studies in Higher Education

University of California, Berkeley

The public research university in its post–World War II form needs reinventing, and no other university leader has set about this with the ambition and focus of Michael Crow, in the company of his colleague William Dabars. They have finished work on one of three parts of this reinvention. But there are two unfinished parts that are still causing problems.

The finished piece is a new version of open admissions. The New American University (NAU), modeled on the authors’ home institution, ASU, offers a place to all “academically qualified students,” where “qualified” is defined with democratic expansiveness. One expression of this policy is that ASU accepts 80.2% of its applicants and is proud of it. Another is ASU’s extensive use of online education, signaled recently by a controversial partnership with edX to offer General Education courses for ASU credit to students who have not actually been admitted to ASU. Crow and Dabars’ underlying principle is that “intelligence is distributed throughout the population” and will take forms to which standard admissions procedures are blind.

On the level of economic pragmatism, they argue that their type of neo–open admissions is the only way that the United States can reverse its descent into the world’s richest “undereducated” society. On the level of social ethics, they break with the university’s dysfunctional attachment to selectivity, in which a university’s greatness is measured by the proportion of people it excludes from the start. Public university flagships have become as exclusive as the Ivy League a generation ago, while the Ivy League schools, now rejecting 90 to 95% of applicants, have become floating islands of educational wealth with little resemblance to the rest of the sector. Crow and Dabars associate this exclusion not with quality, but with scarcity: “scarcity is the brand that our elite universities are selling.” The country desperately needs the end of scarcity—and of tokenistic diversity—in high-quality higher learning, and few people see that as clearly as the authors.

The second part of the reinvention is moving from factory-style throughput to mass “higher learning” (Thorstein Veblen’s term, not theirs). The social value of commodity skills has dropped, but what in the NAU model offers intensive, individualized, creative learning to students who experienced weak learning opportunities during their earliest years, to say nothing of their mixed K-12 experiences, and who exactly are the underserved students that selective public universities reject? The NAU lets them in, and then what? Crow and Debars offer quantitative metrics, but these could merely reflect reduced program requirements and lowered cognitive demands in individual courses at the historical moment when these need to be raised. ASU deserves its reputation for the creative use of technology, and yet instructional technology’s record is weakest with the entry-level and at-risk students that the NAU accepts.

Inclusive education is meaningful only if it offers high intellectual standards, and these cannot be achieved in the traditional manner of postwar expansions: on the cheap. The NAU must offer mass quality and not just mass credentialing. In reality, this will require generous public funding based on enrollments and aimed at intensive learning, and that is precisely what states are decreasingly willing to fund. Crow and Dabars dodge the issue of public funding, which means dodging the question of funding unglamorous undergraduate instructional quality that offers none of the private returns or bankable impacts that attract investors and donors. If Crow won’t shout from the rooftops, “Top quality via full funding for all students,” what educational leader will?

The third aspect of NAU reinvention must be a new freedom in the relation between teaching and research, and on this point Crow and Dabars don’t admit that there is a problem. Entry-level students—most undergraduates, in fact—are not educationally equipped to share in or contribute to research, and this is certainly true at the wonderfully inclusive NAU, where many students will need long-term skill development. There is always a cognitive divide at research universities that 100 years ago induced the economist and sociologist Veblen to recommend a protective barrier between the “college,” focused on acquiring and using existing knowledge, and the “university,” supporting the unadministrable agonies of advanced research that necessarily engage the hardest possible problems with the most arcane expertise in the unwelcoming twilight of the knowledge frontier.

There is also a budgetary conflict of interest between the undergraduate teaching and research functions. The latter has long depended on using a share of enrollment revenues to cover unreimbursed costs. During the period when enrollments and per-student funding always increased, tuition and state funds could be used to cross-subsidize shortfalls in cost recovery. This is why public universities with low tuition and small endowments have been able to compete with the Yales and MITs in research. But now, after years of state cuts and, increasingly, caps on tuition hikes, public research universities are struggling to pay for instruction, much less cover indirect cost shortfalls for cutting-edge research. Crow and Dabars boast of ASU’s ever-growing research expenditures, but of the $405 million it spent on research in fiscal year 2013, almost $150 million came from its own institutional funds. How can the NAU maintain that level of research subsidy (37% of total funds at ASU, 19 to 20% nationally), protect its cutting edge from the “college,” and yet serve the college’s needs for ever-better education for ever-more comingled levels of undergraduate skill?

Public university research and teaching funding are both in trouble. The NAU model envisions fully democratic higher education. But getting there will be not only a matter of design, but of fighting for public resources in a way that universities have long preferred to avoid.

Christopher Newfield

Department of English

University of California, Santa Barbara

Crow and Dabars argue passionately for the need for an institutional university model that combines pedagogy and research, broad student access, and commitment to societal impact. These ideals in fact define the land grant university, as it evolved from the 1862 Morrill Act, which provided federal land to states to establish universities to provide liberal and practical education to what the bill called “the industrial classes.” Many of the nation’s great public universities took their origins from this act. But their three goals—broad access, research excellence tied to instruction, and public service—do not always sit easily with one another, and state reductions in the funding of public universities have exacerbated the tensions among them.

Crow and Dabars advocate most strongly for access. Indeed, under Crow’s presidency, ASU has grown to be the largest public university in the United States, offering admission to all qualified students who wish it. Crow has also led ASU through an extraordinary period of growth in research; the two, the authors argue, are complementary, with the research enterprise providing the basis to educate students in ways that uniquely qualify them to meet the challenges of tomorrow’s world.

This is a claim that many observers believe, although actual evidence—of the percent of students in large public research universities who engage in research, and of the greater effectiveness of education in such institutions—is harder to come by. It may be comforting to believe in this synergy, but it takes more than assertion to make it so. Many kinds of postsecondary institutions seek to engage students in research, and the sheer scale of many public universities limits the use of high-impact practices such as independent research. Relatively little is known, with any precision, about the value of a broad and deep research program for undergraduate education.

The authors direct much of their criticism to admissions practices that exclude the majority of applicants, but here they play somewhat fast and loose with figures. The numbers they quote for rejected applicants from Ivy League universities, for example, are not unduplicated individuals, nor are the numbers from University of California campuses.

The fact that the new model for the U.S. research university is not as new as Crow and Dabars claim does not diminish the accomplishments of ASU, nor does it undermine the argument they make for the urgent need of greater enrollment capacity in public educational institutions. The nation’s democracy depends on social mobility—and public education, as the Morrill Act envisioned, is its most powerful engine.

Carol Christ

Director, Center for Studies in Higher Education

University of California, Berkeley

Crow and Dabars are on the right track with the new enrollment policy at ASU. As research-class universities have become more selective in applicant admissions, the diversity of their students has contracted. Too often, when diversity in academic programs is discussed, what is mentioned most is difference in skin color. Oftentimes, skin color and experiential diversity are highly correlated. However, for some of the most selective educational institutions, skin color and the experiential backgrounds of student applicants are not related to a large degree. For example, a colleague and I in a study more than a decade ago of applicants to the University of Maryland found that no matter what their skin color, all had strongly supportive families, computer expertise, email addresses, and similar high-school records. If skin color had not been known, there would have been little to distinguish one applicant from another.

When these highly selected students attend classes, they do not bring the desired experiential diversity to enrich class discussions and assigned project submissions. True diversity of backgrounds can cause student groups to consider ideas different from those that have been tried before. Indeed, this has happened in my classes when they have included students who represented dissimilar backgrounds.

Studies have shown that diversity promotes hard work, creativity, and consideration of more alternatives than would be the case in a more homogeneous environment. Diverse students expose other students to different viewpoints than they would have otherwise had. I once had a student who, surprisingly to me, had never before had the opportunity to work closely with a person of a different skin color. That student confessed to me that working in groups with students of different skin color and cultural backgrounds had opened her eyes to new worlds of ideas. True diversity in the classroom, when accepted without bias, promotes an atmosphere of openness, when anyone can ask any question or contribute any idea, no matter how weird it might seem to those with different experiences.

The experience of George Church, a professor of genetics at Harvard Medical School, testifies to this result. Rather than seeking homogeneity in his laboratory personnel, he recruits a very diverse group of assistants and researchers. “The image for me is of poking deep holes all over the place, in the fabric of science and engineering,” he said recently in Popular Science. “As we probe each of these points, we get cross talk.” The result is one of Harvard’s most productive labs.

A university can enrich student diversity, as ASU has done it, by expanding enrollment so as to reduce applicant selectivity, or a university could institute a program of individual admissions, similar to the way that athletes or talented music or other performance arts majors are admitted. In this way, criteria other than strict academic records could be used as the basis for admission. In this case, some metric could be used to admit those who serve the diversification needs of the university without compromising the selective process by which most students are accepted for admission.

So ASU should not only experience a greater diversity of students, but offer more creative and vibrant classroom experiences as well. This should lead to enhanced capabilities of graduates, as well as to benefits for the research mission of the university as the enriched academic milieu cultivates innovative and ingenious research discussions.

Arthur T. Johnson

Professor Emeritus, Fischell Department of Bioengineering

University of Maryland

Climate model worries

“Climate Models as Economic Guides: Scientific Challenge or Quixotic Quest?” (Issues, Spring 2015) provides an interesting, entertaining, yet sobering critique of the use of climate models for policymaking. The authors—Andrea Saltelli, Philip B. Stark, William Becker, and Pawel Stano—go as far as to question the scientific value of climate model research. The basis of their argument is that by failing to account for all of the important uncertainties in the models, current climate change predictions based on climate models can be seriously misleading. These unrealistic predictions can then be used by policymakers to mislead the citizens in either direction: to promptly develop or to postpone climate policymaking. This ambiguity ends up polarizing the public, and the chosen course of action usually benefits wealthier countries and powerful corporations.

The uncertainties associated with climate models are themselves uncertain because researchers just do not have all of the information required to account for all sources of uncertainty; we are not even able to properly account for all of the uncertainties of which we are aware. As the authors state, “…estimates of uncertainty are themselves almost entirely uncertain.” Does this mean that attempts to develop climate models and to quantify their uncertainties are futile? I do not believe so.

Trying to understand and explain physical phenomena is a fundamental part of human nature. Researchers will continue trying to model and predict climate, as important scientific insight may be gained in the attempts to explain or predict climate change. Also, uncertainties associated with climate models have to be studied even if it is just to realize that the uncertainties are too large, and model predictions may be useless. Unfortunately, because greed and delusion are also part of human nature, regardless of the looming uncertainties, some scientists invested in climate models may be too eager to put a high value on their predictions, and corporations and governments may support climate policies that promote their own self-interests. Society needs to assess the uncertainties even if it is for self-defense, to protect from unsubstantiated claims meant to advance unwise policies.

Many researchers agree, as I do, on the danger of using climate model predictions to guide policy decisions. However, the authors do not suggest any other course of action, and to be paralyzed into inaction is also unwise. Society should at least request from scientists that uncertainty quantification be done with full disclosure of what can and cannot be assessed. It will not be possible to focus on developing fast and efficient methods for uncertainty quantification without actually questioning what the uncertainties really mean and whether or not they are realistic. It is also necessary to focus on educating the public to think critically about science, so that no scientific predictions are taken at face value without questioning. As Crow has written in “None Dare Call It Hubris: The Limits of Knowledge” (Issues, Winter 2007), “We all operate out of self-interest, which is entirely rational.” But in today’s complex society, each entity’s actions affect others. Flexible policies that encourage individual innovation and are mindful of large-scale consequences are required.

Luis Tenorio and Amanda Hering

Department of Applied Mathematics and Statistics

Colorado School of Mines

This quartet of authors argues convincingly that it is foolhardy to use climate models as detailed economic guides. But failed quests for detail do not cast doubt on the underlying science. Insights from basic science stand regardless of researchers’ inability to produce high-fidelity simulations. Even while we cannot simulate future details of Earth’s atmospheric circulation, we know that increasing concentrations of carbon dioxide risk exciting climate feedbacks, the effects of which we cannot foresee. Think of a train traveling at speed toward an obstacle known to lie somewhere on the track ahead. If the obstacle is sufficiently large, it is straightforward to conclude that the train is likely to be derailed. It is far more difficult to determine (probability distributions of) exactly where individual carriages will come to rest, the damage to the contents of each, and personal injuries suffered at a given seat. Incomplete knowledge need not stifle action in the face of such risks.

Science is never “unequivocal.” Science never provides “facts” about the future. And given that it is impossible to obtain “tested physical theory” on planetary scales, under conditions that have never (yet) happened, requiring such tests ensures a policy of “no action.” All that said, the science underpinning the insight that increasing greenhouse gases will lead to warming is “as-good-as-it-gets” science. And as-good-as-it-gets science is often found on the backs of envelopes. We can calculate the Moon’s surface temperature with surprising ease and accuracy. Although estimating Earth’s is significantly more complicated, we have had clear, quantitative insight into the effect of greenhouse gases since Syukuro Manabe of the Environmental Science Services Administration’s Geophysical Fluid Dynamics Laboratory published computations in the 1960s. Those basic insights stand. The same cannot be said for simulations of Earth’s general circulation. There are well-understood phenomena that current models do not simulate realistically due to purely technological constraints. For example, we know how to represent rock in a global climate model rather well, yet the Andes are two kilometers too short in workhorse models used in what is called the Coupled Model Intercomparison Project Phase 5, or CMIP5. Such shortcomings yield visible imperfections in simulations of current climate and ponderable obstructions to researchers’ ability to realistically simulate feedbacks and the climate change they drive.

Model-based climate projections are incomplete without an estimate of the probability of a big surprise: the probability that structural model inadequacy, for instance, renders them scientifically misinformative. A model used by the Intergovernmental Panel on Climate Change (IPCC), called AR5 SPM, comes laudably close, saying that there is a 10 to 34% chance that the change in global mean temperature over the final 20 years of this century will fall outside “the ranges derived from the concentration-driven CMIP5 model simulations.” Should this happen, the strategy derived from a tool called UK Climate Projections 2009 (UKCP09), developed here in the United Kingdom, will collapse, a point not always reflected clearly in its worked examples. Are UKCP09’s probability distributions for rainfall in the quad of my Oxford College on the wettest day in 2095 informative? Although grand-sounding justifications applicable to the earliest global climate models (or easily adopted by the marketers of perpetual motion machines) abound, there is still little public scientific debate of the limits beyond which high-resolution simulations should not be used in guiding development and policy.

The combination of clarifying what we cannot simulate and refusing to showcase “best available” numbers that are neither robust nor adequate for the purpose is simply basic scientific good practice. One danger of overselling our insight into the details is that it may well cast doubt on the as-good-as-it-gets scientific evidence that there is a clear and present risk of significant negative impact.

Leonard A. Smith

Professor in Statistics (Research)

Director of the Centre for the Analysis of Time Series

London School of Economics

I generally agree with the ideas expressed in this article, but I find that the authors’ distinction between “policy simulation” and “policy justification” is not very convincing. For if one believes, as I do, that the results of economic models used to attempt to quantify the net costs and benefits of mitigating climate change over the long run are unscientific, in part because of the uncertainties inherent in the models and their assumptions, then these models can be used neither to simulate policies nor to justify policies to any reasonable level of accuracy. Thus, I more strongly support Saltelli et al. when they question whether many model-based “facts” are scientific at all.

That issue aside, the article has other rather profound implications, some of which I do not believe that the authors sufficiently stress. One implication is that the peer-review process for research papers published on physical climate modeling, as well as on economic modeling of climate change, is clearly broken. After all, given the article’s claim that uncertainty is not usually accounted for properly, many if not most of the papers should have been rejected. This is certainly true when it comes to the economic modeling done by integrated assessment models, which is what underpins certain critical sections of the IPCC Working Group III report on mitigation.

The peer-review process should also have led to the rejection of many research papers in these fields, because the basic logic of many conclusions drawn from “inter-model comparison studies” is often totally flawed. For example, many intermodel comparison studies ask the valid question at the beginning, namely, to what extent are the differences in results from different models for the “same” scenario due to differences in model structure versus differences in input assumptions? The studies then claim to proceed to provide an answer. But they never do, because they never have each model run with the same values of key input assumptions, to the extent allowed by the different model structures.

Another problem noted by the authors is that the use of the term “probability” in the IPCC reports as applied to likely temperature increases due to climate change is really quite fallacious. They basically say this explicitly, but the point needs to be emphasized. Because it is not possible to know anything about the probability distributions of even a single key input parameter for the physical climate models, it certainly is not possible to know the likely probability of the resulting temperature increases for any given level of radiative forcing over time. Yet, the “Summaries for Policy Makers” of the IPCC reports are replete not only with the term “probability,” as Saltelli et al. described, but with actual numerical values for the relevant probabilities.

Richard A. Rosen

Tellus Institute

Boston, Massachusetts

The authors provide a frank and incisive review of discussions and scientific analysis on climate change. They warn of the uncertainties in the predictions of global warming models. Climate models are designed to produce information. But I suggest reading the article from a perspective of information quality, or what I and a colleague, Galit Shmueli, have called InfoQ. InfoQ ties together the goal, data, analysis, and utility of an empirical study. It is deconstructed in eight dimensions: data resolution, data structure, data integration, temporal relevance, generalizability, chronology of data and goal, operationalization, and communication. To assess InfoQ, these eight dimensions must be evaluated in the context of specific goals and objectives.

Saltelli et al. focus on the lack of generalizability and limitations in several of the global warming publications, if one is interested in formulating policies, which affect the economic scene. They state that “ensembles” are not in any sense representative of the range of possible (and plausible) models that fit the data, which implies a lack of generalizability. They also state that the sensitivity analysis varies only a subset of the assumptions and only one at a time. But this precludes interactions among the uncertain inputs, which may be highly relevant to climate projections. It also indicates poor generalizability. In terms of operationalization, the authors distinguish policy simulation from policy justification. The operationalization of the climate model in terms of justification is the problematic part the authors want to emphasize. An InfoQ assessment of the various studies cited can help further elucidate the difference between scientific insight and evidence for policymaking.

The authors’ underlying approach is scientific. The assumption is that the correct view of an issue such as climate change should be evidence-based. Unfortunately, many forces are now participating in this controversial field, with apparent collateral damage. See for example the blog on how the education system in the United Kingdom is affected by such discussions: https://tthomas061.wordpress.com/2014/04/09/climate-catastrophism-for-kiddies/.

If the aim is to be “evidence-based” and “scientific,” then Saltelli et al. have provided an excellent perspective. To help focus the discussion, one might want to bring in the perspective of information quality that combines generalization and operationalization, two critical aspects of the global warming debate. Even without that, the authors should be gratefully thanked for insightful contributions.

Ron S. Kenett

Research Professor, University of Turin, Italy

Visiting Professor, Institute for Drug Research, Hebrew University Faculty of Medicine, Israel

International Professor, New York University Center for Risk Engineering

Chairman and CEO, The KPA Group, Israel

The authors of this thoughtful and measured article deserve to be commended for their calm and reasonable tone in a subject area that they note from the outset is “polarized” and “fraught.” The core of their well-argued case is at least partly captured by these three statements: One, “Given the economic and societal ramifications of climate change, it is not surprising that several disciplines claim to provide certainties and solutions. Among these, computer modeling is perhaps the most visible, pervasive, and opaque.” Two, “…models share common errors whose magnitudes are simply not known.” And three, “…[a danger] is that, with excessive confidence in our ability to model the future, we will commit to policies that reduce, rather than expand, available options and thus our ability to cope with the unknown unknowns of our future.”

There seems little doubt that laypeople can be unduly impressed by computer outputs. The remarkable impact of the Club of Rome and its report The Limits to Growth, issued in 1972, is testimony to that. The foolishness of such trust has been revealed by the world unfolding in the intervening decades in a dramatically different way from that report’s vivid auguries of doom and disaster.

In our time, the computer models of climate have been elevated some way beyond their deserved status by campaigners agitated by the possible effects of humans’ carbon dioxide emissions on climate. In a study published in 2013 by the Heartland Institute, Global Climate Models and Their Limitations, Climate Change Reconsidered II: Physical Science, Anthony Lupo and William Kininmonth have presented a detailed and more technical analysis of the many limitations of such models, not least in areas where model output can be compared with observations, and their work provides useful background and reinforcement for the present article.

John Shade

Inverness, Scotland

The policy debate with respect to anthropogenic climate change, addressed by Saltelli and colleagues, typically revolves around the accuracy of models. People who contend that models make accurate predictions argue for specific policies to stem the foreseen damaging effects; those who doubt their accuracy cite a lack of reliable evidence of harm to warrant policy action.

These two alternatives are not exhaustive. One can sidestep the “skepticism” of those who question existing climate models, by framing risk in the most straightforward possible terms, at the global scale. That is, we should ask, what would the correct policy be if we had no reliable models?

Humans have only one planet. This fact radically constrains the kinds of risks that are appropriate to take at a large scale. Even a risk with a very low probability becomes unacceptable when it affects all of us—there is no reversing mistakes of that magnitude.

Without any precise models, we can still reason that polluting or altering the environment significantly could put us in uncharted territory, with no statistical track record and potentially large consequences. It is at the core of both scientific decisionmaking and ancestral wisdom to take seriously the absence of evidence when the consequences of an action can be large. And it is standard textbook decision theory that a policy should depend at least as much on uncertainty concerning the adverse consequences as it does on the known effects.

Further, it has been shown that in any system fraught with opacity, harm is in the dose rather than in the nature of the offending substance: Harm increases nonlinearly to the quantities at stake. Everything fragile has such a property. Although some amount of pollution is inevitable, high quantities of any pollutant rapidly increase the risk of destabilizing the climate, a system that is integral to the biosphere. Ergo, we should reduce carbon dioxide emissions, even regardless of what climate models say.

This leads to the following asymmetry in climate policy. The scale of the effect must be demonstrated to be large enough to have impact. Once this is shown, and it has been, the burden of proof of absence of harm is on those who would deny it.

It is the degree of opacity and uncertainty in a system, as well as asymmetry in effect, rather than specific model predictions, that should drive precautionary measures. Push a complex system too far and it will not come back. The popular belief that uncertainty undermines the case for taking seriously the “climate crisis” that scientists say we face is the opposite of the truth. Properly understood, as driving the case for precaution, uncertainty radically underscores that case, and may even constitute it.

Joseph Norman

Yaneer Bar-Yam

New England Complex Systems Institute

Rupert Read

School of Philosophy, University of East Anglia

Nassim Nicholas Taleb

School of Engineering, New York University

Good behavior

In “Informing Public Policy with Social and Behavioral Science” (Issues, Spring 2015) Brian Baird lays out five recommendations to bridge the gap between academics—specifically in the social and behavioral sciences (SBS)—and policymakers. But there are three important observations he misses that have implications for the type of institutional development that should take place.

First, the strength of SBS is in its theoretical and methodological diversity. Baird recommends a “collaborative, consensus process to identify robust scientific methods and findings that are of potential interest to policymakers.” This is not achievable in SBS, however, at least not in the sense laid out by Thomas Kuhn, an influential U.S. physicist, historian, and philosopher of science. Economists, sociologists, psychologists, and researchers in other SBS disciplines appropriately develop and test their own theories, at a variety of different levels of analysis, using a wide range of analytic methods, to address vastly different research questions. This is not because SBS researchers are unaware of one another’s research, but rather because of the extraordinarily complex nature of the key units of observation for SBS: individual people and groups thereof (e.g., organizations, communities, jurisdictions), both with innumerable and intangible “moving parts” that are inordinately more difficult to observe (much less predict and explain) than, say, biological or engineering systems.

Second, there is no shortfall of institutional mechanisms for translating and communicating SBS research to policymakers. Most of Baird’s recommendations are akin to similar calls for technology transfer from the “hard” academic science and engineering fields to industry. I agree with Baird that one should not presume trickle-down from SBS to policymakers, and that institutional development for translating what SBS academics know to policymakers in a language that the latter can understand and apply is a good idea. However, institutions of this kind have existed in SBS for some time. There are upwards of 300 schools of public affairs in the United States, and many of these are much more than professional schools focused on teaching basic skills such as policy analysis to graduate students. Within many of these schools are multidisciplinary policy research centers explicitly designed to translate SBS research findings for decisionmakers in particular areas of public policy, using many of the approaches that Baird recommends. For example, Georgia Tech, Arizona State, Harvard, and Ohio State have centers focused on science and technology policy.

Third, the real problem is that policymakers lack absorptive capacity. The institutional gap between academic research and policymakers as characterized by Baird is already being bridged in numerous policy areas and in the ways he suggests, at least for SBS. (In contrast, most bridging institutions for the sciences and engineering focus on industry, not government.) If new types of institutions connecting academics to policymaking are to be developed, they should not focus on the translation of research findings (from SBS and otherwise), but rather on developing the absorptive capacity of policy decisionmakers to distinguish scientifically derived information from other sorts of information. In other words: translation is not enough. Policymakers should possess the basic skills that any graduate student possesses after completing his or her first year in a public affairs program. And many of the modes of communication and teaching recommended by Baird would be very useful for accomplishing this task.

Craig Boardman

Associate Director, Battelle Center for Science & Technology Policy

Ohio State University

Biomedical overbuilding?

“Have Universities Overbuilt Biomedical Research Facilities?” (Issues, Spring 2015) admixes a narrow focus and questionable statistics with a broader, valid concern that care be taken in the consideration of proposals to eliminate government reimbursement for university construction of research facilities. The authors—Arthur Bienenstock, Ann M. Arvin, and David Korn—set their sights on the expansive critique and set of recommendations that Bruce Alberts has made for rescuing U.S biomedical research from its current plight. (Alberts has made this case in several venues, but Bienenstock et al. focus in particular on an editorial published in 2010 in Science magazine.) The authors, however, home in on only one of the recommendations: “full reimbursement to amortize loans for new buildings.” Moreover, Alberts offered that recommendation toward the close of a trenchant analysis of the systemic propensities toward mismatches between the supply and demand for biomedical researchers, a dynamic propelled in part by “perverse incentives” in research funding that “encourage grantee institutions to grow without making sufficient investments in their own faculty and facilities.”

The authors’ primary counterargument is that the quantity of academic biomedical research space per million dollars of support from the National Institutes of Health (NIH) fell from its 1987–1995 level through 2003, and only afterward began to rise, reaching a level in 2011 below the base period. They present these data as evidence that there was a “significant” shortage of academic research space in the late 1990s. They thereby contend that “Given the absence of evidence for systematic overbuilding, there is no apparent justification for altering federal reimbursement policies related to the construction of research facilities.”

The data they present finesse rather straightforward considerations that adding researchers, staffs, and students attendant on increased research funding (from NIH and elsewhere) takes less time than constructing buildings, so that (short-term) space squeezes are predictable whenever expansion occurs. More importantly, their focus on this measure alone leads them to quickly pass over what in effect is the central thesis of Alberts’s argument; namely, as they themselves note, “some institutions or classes of institutions may have overbuilt.” Reflecting deep-rooted institutional imperatives and aspirations, fueled by congressional policies to foster geographic and institutional dispersion, U.S. universities have their own field of dreams, believing that if they build it, it (funding) will come. This is the behavioral syndrome that Alberts’s proposals are designed to cure.

But Bienenstock et al. raise a deeper concern that I share. The closing recommendation in Alberts’s essay comes across as an unbounded call for a reexamination of policies (e.g., payment of indirect costs or support of faculty salaries) that are foundational elements in the social contract binding together the federal government and universities. If indeed undertaken, any such reexamination must be driven and shaped by more than the admittedly troubled setting of the academic biomedical sciences. Thus, to attend only to the matter of research space, academic research space devoted to the biological and biomedical sciences constituted the largest share of all such space, but this share represented only 27% of the total, according to a report by Michael Gibbons, Research Space at Academic Institutions Increased 4.7% between FY2011 and FY2013, issued as an InfoBrief by the National Science Foundation’s National Center for Science and Engineering Statics in March 2015. Enlarging upon the Bienenstock et al. argument, it would be a mistake to attempt to correct the systemic flaws in the biomedical sciences without considering the impacts of any proposed policy changes—including but not limited to federal reimbursement policies for construction of research facilities—on other fields of research or disciplines, or on research universities in general.

Irwin Feller

Visiting Scientist, American Association for the Advancement of Science

Professor Emeritus of Economics, Pennsylvania State University

Regulating Genetic Engineering: The Limits and Politics of Knowledge

For many people based in the United Kingdom, as we are, memories of bovine spongiform encephalopathy (BSE), commonly known as mad cow disease, remain vivid. We recall, in particular, that during the decade after the identification of the disease in 1986, the British government and representatives of the cattle industry asserted that BSE was, in effect, substantially equivalent to the familiar disease of sheep and goats called scrapie, which was then widely assumed to be harmless to humans. Although some control measures were taken, BSE infectivity was allowed to remain in our food supply. And as we tragically learned, BSE could be transmitted to humans, in a brain-wasting form called variant Creutzfeldt-Jakob disease. According to government statistics, 177 Britons died of this lingering disease through June 2014.

We have also subsequently learned that if adequate precautionary measures had been taken in time, and the BSE pathogen had been eradicated from cattle and their feed chain, such measures would have cost about £20 million. (Given the exchange rate in 1990 as a mid-range value, that amount would have equaled approximately $33 million in U.S. currency.) But lacking such preventive efforts, the eventual costs to the UK government of this regulatory failure exceeded £20 billion, not to mention the massive commercial losses that occurred. The loss of life, of course, overshadows all.

Moreover, we know that if the BSE pathogen had been eradicated during this period, evidence to show that the expenditure of £20 million had been prudent and had provided a thousandfold return on the investment, would never have emerged. It is in the light of this knowledge, and other examples of a similar kind, that we approach the current assaults on critics of genetic engineering (GE), such as the broadside by Drew L. Kershen and Henry I. Miller in their article, “Give Genetic Engineering Some Breathing Room,” in the Winter 2015 Issues in Science and Technology.

As typified in their article, charges against critics of GE often take four general forms. But all of them, we argue, are unsupported by facts. First, scientific and policy debates are not, as claimed, polarized in black and white, divided simply into two contending camps. Second, there is no genuine consensus within the scientific community about the safety and acceptability of innovations produced using GE. Third, allegations of costly overregulation presuppose that there is reliable and complete foreknowledge of benefits as well as any and all possible risks, but such scientific hubris should never be treated as an adequate substitute for systematic investigations. Fourth, common representations of GE as an incremental, innocuous innovation that poses no special risks and requires no special regulation is inconsistent with the biotechnology corporations’ insistence that GE is a radical innovation that deserves special protection and incentives.

One pivotal error underpins most misrepresentations. It is often implied that policy judgments about, for example, the regulation of GE can and should be based on, and only on, scientific considerations. This ignores a longstanding body of analysis that argues that science on its own can never determine policy decisions. Mountains of evidence show that regulatory policies have never been based solely on science. Nor could they be; as analytic philosophers like to say, you cannot derive an “ought” from an “is.”

Supporters of GE repeatedly characterize the challenges presented by GE as “risk.” This implies that it is always possible to confidently assign probabilities for all potential problems and benefits of GE. Yet even if this were the case, Nobel prize–winning work on rational choice theory, which underlies risk assessment, has established that problems involved in comparing the “apples and pears” of differently viewed impacts and benefits mean that there can be no single, definitive, overall ordering of risks from the point of view of society as a whole. GE proponents, however, seldom acknowledge the more intractable state of uncertainty, in which there exists no confident basis for estimating probabilities. For their part, Kershen and Miller mentioned this possibility only once. But this they applied to corporate complaints about the regulatory process, not to potential safety concerns or ecological impacts. This failure to acknowledge the problematic status of relevant knowledge demonstrates the partisan nature of analyses by GE supporters—and their departure from scientific balance.

This is not to suggest that facts about the world are irrelevant to policy. It is, however, important to recognize that facts, even if known for certain, can never on their own settle normative policy questions. Political and normative considerations are not just second-order supplements to science that are required only when significant uncertainties are evident. Values and interests are inseparably constitutive of the judgments that frame the choices scientists make about which questions to ask and their assumptions about what data are relevant and how they are to be interpreted. This is no less true of the three of us than it is of those who wholeheartedly support GE. The difference is that while we acknowledge our normative commitments, they pretend to a disinterested fact-focused neutrality.

Let’s take the typical arguments one by one:

Polarization. The scientific and policy debates about GE do not take the form of a binary polarization. In reality, there is a broad, diverse spectrum of views on a wide range of pertinent issues. Just because some GE supporters choose to locate themselves at one extreme end of an axis does not justify their classification of anybody who raises questions about GE as if they all belonged together at the opposite end.

As one of us (Stirling) has recently argued, there are too many protagonists in these debates who behave as if the only positions available are simply to be “for” or “against” a single family of innovations; as if GE can be interpreted only as either absolutely indispensable or uniquely unacceptable. But modern biotechnology offers diverse innovation pathways and it is possible to adopt reasonable political perspectives on their respective pros and cons. Alternative approaches to a given breeding problem, such as transgenics, cisgenics, apomixis, gene editing, and genomic and marker-assisted selection, could each create different patterns of benefits and risks (social, political, economic, and cultural, as well as biophysical and ecological), depending on how and where they might be applied.

Consensus. Kershen and Miller asserted that “The seminal question about the basis for regulation of genetic engineering in the 1970s was whether there were unique risks associated with the use of recombinant DNA techniques. Numerous national and international scientific organizations have repeatedly addressed this question, and their conclusions have been congruent: There are no unique risks from the use of molecular techniques of genetic engineering.” The plausibility of this narrative rests on the assertion that there is a consensus in the scientific community around this position, but that is a misrepresentation.

We envisage several conditions under which GE technology could potentially contribute to global food security, environmental sustainability, and other valuable public outcomes.

For example, the European Network of Scientists for Social and Environmental Responsibility gathered more than 300 signatures from independent researchers endorsing a statement rejecting the claim that there is a consensus on the safety of genetically modified organisms (GMOs). The statement held that “the claimed consensus is shown to be an artificial construct that has been falsely perpetuated through diverse fora. … [T]he scarcity and contradictory nature of the scientific evidence published to date prevents conclusive claims of safety, or of lack of safety, of GMOs. Claims of consensus on the safety of GMOs are not supported by an objective analysis of the refereed literature.”

Although it may be easy to gather supportive narratives from selected organizations and individuals, that does not constitute a consensus across the scientific community. Moreover, given the incompleteness, equivocality, and uncertainties in the evidential base, it would be disingenuous to claim to be able to definitively judge the safety of particular products of GE, or of GE technologies, as a uniform taxonomic category.

Overregulated. Kershen and Miller asserted that: “…the most comprehensive and unequivocal analysis, the 1989 National Research Council report, Field Testing of Genetically Modified Organisms, on the risks posed by genetically engineered plants and microorganisms, concluded that ‘…modern molecular techniques are more precise, circumscribed, and predictable than other methods. …With organisms modified by molecular methods, we are in a better, if not perfect, position to predict the phenotypic expression’ ” (emphasis added).

This casual piece of reasoning implies that the knowledge now available to scientists approaches perfection, being almost complete and entirely reliable; sufficient, at any rate, to confidently pass judgment on the safety not only of the GE products that have already been marketed but also of any and all GE products that might be developed at some time in the future. This claim is then interpreted as if it implies that the safety of GE products should not be tested. That line of argument aspires to automatically rule out entire ranges of investigations; such studies are supposedly unnecessary because it is already known what the results will show.

In this way, the essentially antiscientific quality of this argument is exposed. Scientific hypotheses are supposed to be testable and tested, not excuses for insisting that no tests should be conducted. The safety or risk profiles, or both, of particular products of GE can be established only empirically; to claim perfect or even sufficient foreknowledge for any or all products, in any or all contexts, constitutes a profoundly unscientific and antiscientific perspective.

As well as claiming that the products of GE can pose no novel or unanticipated risks, some GE advocates also insist that the benefits will be substantial, and assume that those benefits will be widely available and shared. Given those assumptions, they insist that almost all regulatory institutions adopt approaches that are, in Kershen and Miller’s words, “not ‘fit for purpose’…they are unscientific [and] anti-innovative…” They repeatedly allege that GE is subject to costly overregulation, not only in the United States, but also in other countries. They suggest that the key question to ask is: “What will be the regulatory costs, time, and energy required to capture the public benefits of the new technologies?”, but they do not pause to reveal who will be doing the capturing or what it is that will be captured.

They insist that regulatory policies are just “inhibiting innovation,” and they do so by ignoring the fact that regulations can influence the direction of technological trajectories, toward, for example, providing safer, more useful, and more sustainable products and processes. Such influencing is the essence of precaution, which is not about being hostile to technology or innovation, but is about being serious about scientific uncertainties and conscientious about social choices. Unblinking GE proponents similarly fail to acknowledge that it may be important also to ask: What will be the biophysical, ecological, social, and economic costs of failing to regulate innovative novelties adequately?

Values and interests are inseparably constitutive of the judgments that frame the choices scientists make about which questions to ask and their assumptions about what data are relevant and how they are to be interpreted.

Incremental and innocuous. Proponents of GE insist that all innovative GE products and processes constitute incremental rather than radical changes in technology, and that in respect of issues of risk and safety they are entirely innocuous. They insist that, as Kershen and Miller declared: “…the newest techniques of genetic modification are essentially an extension, or refinement, of older, less precise, and less predictable ones…”

Such insistence that GE provides only incremental rather than radical innovations is very difficult to reconcile with corporations’ insistence that they require or deserve special protection for their “intellectual property.” Corporations active in GE have long insisted collectively that their products must be covered by patents, rather than by, for example, traditional forms of protection, such as those provided to plant breeders by the International Union for the Protection of New Varieties of Plants under the so-called UPOV Convention.

In this way, the corporations active in the GE field try to have it both ways. With respect to innovativeness, GE is radically different from traditional methods in R&D, necessitating special protection of intellectual property. With respect to safety, harm, or risks, the companies insist that GE is not remotely special or distinctive. They cannot maintain such an inconsistent perspective, which is essentially unscientific.

The case for special protection for intellectual property was premised on claims that their R&D costs would be particularly high, and without patent rights, commercial returns could not reasonably be anticipated. Strangely, however, Kershen and Miller insisted that modern GE-based methods are “…more precise and versatile than ever…,” opining that “…the use of the newest genetic engineering techniques actually lowers the already minimal risk associated with field testing.” If those statements are true, then the R&D costs should have fallen, not risen. In other words, such claims about the technological superiority of GE techniques and the corporate argument for patent rights over transgenic organisms are mutually inconsistent.

So where are we left? Sadly, the polarizing effects of these various kinds of arguments have resulted in an unpromising state of public debate about GE and its regulation. As a coda, we are not suggesting that GE is invariably unsafe or unacceptable. On the contrary, we envisage several conditions under which GE technology could potentially contribute to global food security, environmental sustainability, and other valuable public outcomes. This is even more true of wider (relatively neglected) applications of advanced biotechnology. However, we are critical of the corporate strategies of some of the large firms that, motivated by the particular private benefits they anticipate, have invested heavily but selectively in GE trajectories.

Genetic engineering does not need “breathing room,” but thoughtful reevaluation and careful redirection toward important public goods, such as improved food security and environmental sustainability. We find it ironic that while Kershen and Miller, along with many other GE proponents, insist that regulatory and policy judgments about GE should be based on science alone, their arguments are typically articulated with exaggerated emotional intensity.

We do not pretend to be value-neutral; rather, we acknowledge our concerns to prioritize the needs of poor and hungry communities over those of corporations that have invested heavily in GE. We also maintain that helping those communities means directing the application of available and innovative technologies, as well as socioeconomic institutions and policies, toward the sustainable reduction of poverty. We certainly should not be unquestionably promoting anything that risks aggravating socioeconomic inequalities and inflicting great harm on those who are most vulnerable.

Erik Millstone and Andy Stirling are professors in the Science Policy Research Unit and Dominic Glover is a research fellow in the Institute for Development Studies at the University of Sussex in the United Kingdom.

Storm Clouds on the Career Horizon for Ph.D.s

When I was about to graduate from college in the late 1980s, I went to the office of my favorite economics professor to ask about the job prospects for Ph.D.s in economics. My professor told me that there would be increasing demand for faculty, because substantial numbers of professors were expected to retire in the coming decade. He encouraged me to go to graduate school, and I did so because academic jobs would be plentiful. When I became a faculty member, I was asked the same question. Unfortunately, I cannot share an optimistic outlook for academic jobs with today’s students. In 1994, mandatory retirement for faculty was eliminated, reducing the retirement of tenure-track faculty. And when professors finally did retire, universities often replaced them with adjuncts at low salaries. These employment practices significantly changed academic employment prospects. An uncertain funding environment, driven by a reduction in state support for public higher-education institutions and falling federal investments in science, compounds these problems.

When researchers and policymakers discuss academic science, they typically combine all the fields of science, technology, engineering, and mathematics (STEM) into a single category. Yet this degree of aggregation masks important variation across academic disciplines in market structure. In the research I have done with Shulamit Kahn on women’s scientific careers, we have argued that each scientific discipline constitutes a separate labor market. Merging all these fields under the single rubric of STEM provides an inaccurate picture of academic science and muddies the policy discussion, because the issues faced in one market are not the same as those confronting another.

Disaggregated data are available from NSF’s Survey of Earned Doctorates (SED), which collects information each year from those just completing a Ph.D., and its Survey of Doctorate Recipients (SDR), a biennial longitudinal survey of a sample of U.S.-trained Ph.D.s. For the purposes of this article, I separated STEM into four broad disciplines: life sciences, which include biomedical, agricultural, and environmental sciences; physical sciences, which include chemistry, physics, geoscience, mathematics, and computer science; social science, which includes psychology and social sciences; and engineering. I used the SED to examine Ph.D. production and repeated cross-sections of the SDR surveys to examine academic and nonacademic employment, and tenure-track and non–tenure-track employment, within the four broad academic disciplines.

U.S. universities granted 23,823 Ph.D.s in 1990 and 36,654 in 2011. As Figure 1 illustrates, growth was not consistent across disciplines and not steady within disciplines. Figure 2 shows that the differences among the fields are even greater when one looks at career paths.

The majority of engineering Ph.D.s hold nonacademic jobs. The number in tenured or tenure-track positions has remained relatively constant, while the non-track sector has expanded. In 1991, there were 3.6 tenure-track faculty for each non-track engineering Ph.D.; in 2010 that ratio had dropped to 2.0.

In the life sciences, academic and nonacademic employment is roughly equal, but the balance is shifting steadily toward nonacademic jobs. In the universities, the movement is from tenure-track to non-track positions. The ratio of tenure-track to non-track jobs has declined from 1.8 in 1990 to 1.1 in 2011.

In the physical sciences, there are about 1.5 nonacademic jobs for each academic position. The ratio of tenure-track to non-track positions in academia has fluctuated between 2.5 and 2.0 in the past two decades.

The academic/nonacademic split is roughly even in the social sciences, and the ratio of tenure-track to non-track positions has declined from 3.7 in 1990 to 2.2 in 2011.

The growth rate in the number of tenure-track academic positions between 1990 and 2010 is consistent across the disciplines, ranging between 20% in engineering and 27% in the life and social sciences. In contrast, the growth rate in Ph.D. production differs considerably: 75% in the life sciences, 64% in engineering, 49% in the physical sciences, and 30% in the social sciences. Only in the social sciences is the rate of growth in academic positions close to the rate of growth in Ph.D. production. All other fields have Ph.D. production outstripping tenure-track employment growth. Where do these excess scientists end up?

They become employed in either non-track academic jobs or the nonacademic sectors. Non-track academic jobs have increased by 50% in the physical sciences and doubled or more in the rest of the disciplines. The nonacademic sector has shown the fastest employment growth for Ph.D. recipients, growing by 75% for physical science, 260% in engineering and social science, and 320% in life science fields.

Some of the expansion in non-track academic employment has been driven by the increase in postdoctoral appointments. The National Academies’ recent report The Postdoctoral Experience Revisited has found that the number of postdoctoral researchers increased by 150% between 2000 and 2012. Postdoctoral training is most common in the life sciences and least common in the social sciences and engineering, but the rate of growth is highest in the latter two fields.

Postdoctoral training is a problematic practice that seems impervious to repeated calls for reform. Since 1969, the National Academies has produced reports calling for reforms to the postdoctoral system, and many of these reports repeat the same recommendations of increasing pay, providing benefits, and limiting the term of training. Some progress for postdocs is finally being made. I was part of the Advisory Committee to the Director of the National Institutes of Health (NIH) Working Group on the Biomedical Workforce. Our report reviewed the postdoctoral system for biomedical doctorates and recommended reforms that NIH has begun to implement. These include increasing postdoctoral stipends, increasing the number of early-independence research awards, and modifying training programs to expand career opportunities. Many of these changes were adopted only in 2014, and it remains to be seen whether they will have a significant impact on the postdoctoral experience.

Taken together, these employment trends have important implications for doctoral students and their advisers. Faculty often encounter students who want to be just like them: tenure-track academics. Faculty oblige by preparing students for these increasingly elusive tenure-track jobs. Although unemployment rates for individuals with STEM discipline Ph.D.s are very low (2.6% in 2010), Figure 2 illustrates that academia is not a growth industry, and tenure-track academia is stagnating relative to non-track academia and Ph.D. production. Shualmit Kahn and I found that among biomedical Ph.D.s who graduated in 2000, only 20% ended up in tenured or tenure-track academic positions within 10 years of the Ph.D. These are not encouraging results, and students need to know that the majority of doctorates in their graduating class will be employed in either non-track academic jobs or the nonacademic sector.

Even those who find a tenure-track position will discover that their future is uncertain. According to an article in the Proceedings of the National Academies of Science by Johns Hopkins University President Ronald Daniels, the young NIH investigator who was lucky enough to land one of the coveted tenure-track academic jobs will face even stiffer odds in landing an independent R01 research grant. The average age of the first R01 award, which has been creeping up for decades, finally seems to have stabilized—but at the relatively advanced age of 42. NIH was so concerned about the increasing age of first R01s grants and the low funding rates for young investigators that in 2008 it initiated the Early Investigator awards, which essentially fund early investigators near but below the payline. Daniels argues that these policies are not enough and that we risk losing a generation of scientists. Concerns about the aging NIH workforce has led Rep. Andy Harris, a former biomedical researcher, to propose legislation calling for a reduction in the median age of NIH investigators from 42 to 38 by the year 2025.

Since the end of World War II, the federal government has steadily increased its support for academic science. U.S. research universities have responded by co-producing scientific discoveries and increasing numbers of Ph.D. scientists. This process has been remarkably successful, but researchers such as Paula Stephan and Michael Teitelbaum have argued that our current system is on the brink of collapsing under its own weight. I agree with this assessment if we view science as beginning and ending with the university. My data show that tenure-track academic science is growing slowly and not absorbing the increasing numbers of doctorates produced.

However, in most STEM fields, doctorates in science work outside of academe. The nonacademic sector employs many well-trained scientists and provides a release valve for the increasing numbers of STEM Ph.D.s. Given the realities of scientific labor markets and funding uncertainties in higher education, political and academic leaders face a number of pressing questions: What policies should be enacted to ensure better outcomes for students? What public policies will further the scientific enterprise? What should we say to the prospective student who is contemplating a doctorate and an academic science career?

Policy changes may pave the way for changes in scientific training. Programs such as NIH’s recently created Broadening Experiences in Scientific Training (BEST) training grants, which prepare students for careers besides academic research, promise to better align Ph.D. production with the realities of the labor market. It remains to be seen whether the BEST grants fulfill their promise.

Furthermore, the Council of Graduate Schools (CGS) recommends professional development for all graduate students to prepare them for a broader range of careers outside of academia. Likewise, the CGS recommends tracking career outcomes of graduates by institution in order to provide better information to prospective graduate students. These policies are best practices and should be adopted widely by graduate programs.

Given the stark realities, how should we advise our prospective students? I would first be honest: Academic science is facing stiff headwinds and a turbulent funding environment. Tenure-track academia is stagnating despite increasing numbers of undergraduate and graduate students. The causes are multifaceted, ranging from the end of mandatory retirement to the increasing reliance of universities on the reserve army of underemployed adjunct professors. The likelihood of one of our students obtaining tenure-track academic employment has dropped considerably compared to when we were in graduate school. We are doing our students a disservice by training them to fit within the narrow and elusive confines of academia, when for most fields the majority of jobs are in the nonacademic sector. Students should know before they go to graduate school that their chances of becoming a tenured academic are very low. The decision about what to do is ultimately theirs, but it is our responsibility to ensure that they can make an informed decision.

Donna K. Ginther ([email protected]) is a professor of economics and the director of the Center for Science, Technology and Economic Policy at the Institute for Policy and Social Research at the University of Kansas.

Recommended reading

R. J. Daniels, “A Generation at Risk: Young Investigators and the Future of the Biomedical Workforce,” Proceedings of the National Academy of Sciences 112, no. 2 (2015): 313–318.

D. K. Ginther and S. Kahn, “Women’s Careers in Academic Social Science: Progress, Pitfalls and Plateaus” in The Economics of Economists, A. Lanteri and J. Vromen, eds. (Cambridge, UK: Cambridge University Press, 2014).

D. K. Ginther and S. Kahn, “Does Science Promote Women? Evidence from Academia 1973-2001,” in NBER Working Paper W12691. Science and Engineering Careers in the United States, R. B. Freeman and D. F. Goroff, eds. (Chicago, IL: University of Chicago Press for NBER Science Engineering Workforce Project, 2009).

National Academy of Sciences, National Academy of Engineering, Institute of Medicine, Committee to Review the State of Postdoctoral Experience in Scientists and Engineers, The Postdoctoral Experience Revisited (Washington, DC: National Academy Press, 2014).

Paula E. Stephan, How Economics Shapes Science (Cambridge, MA: Harvard University Press, 2012).

Michael S. Teitelbaum, Falling Behind? Boom, Bust, and the Global Race for Scientific Talent (Princeton, NJ: Princeton University Press, 2014).

Science Fiction? Yes!

In the Spring 2014 Issues, we published our first science fiction story. Physicist Gregory Benford’s story “Eagle” explored how radical environmentalists might respond to the launch of a geoengineering project to limit climate change. The success of that story opened our eyes to the potential of science fiction writers to provide a useful perspective on the policy questions discussed in our standard analytic articles. We decided to stage a contest with prizes for science fiction stories—appropriate for policy audiences.

The first step in the contest called for prospective writers to submit a 250-word description of the story they wanted to submit. In our optimistic moments we dreamed of receiving a few dozen proposals. Wrong. We found ourselves buried in 130 submissions that promised a dizzying array of approaches to a rich mix of topics. We struggled to whittle the list down to the 14 semifinalists that we asked to submit full stories.

When the stories arrived, we were surprised again. Writing an intriguing proposal is much easier than producing a well-written and engaging story. We thought we would be lucky to find one or two publishable pieces, but the quality of the writing was consistently first-rate. If anything, the stories were better than the proposals. After reading all the entries, Jason Lloyd, Dan Sarewitz, and I realized that picking winners would not be easy. We read them all again determined to identify our favorites. There was no consensus. No single story emerged as a favorite, and our individual top-five lists had little overlap. Almost every semifinalist made it onto at least one list.

After considerable discussion, we arrived at a list of five stories that we agreed we had to publish, plus two honorable mentions that could have ended up in the top five on a different day. The five stories that will appear in successive editions of Issues are:

• Claudia Casser, “Heirs of the Body”
• Kelle Dhein, “The Fictional Age”
• Kristen Koopman, “You’re a Mile Away and You Have Their Shoes”
• Chris Merchant, “Mapo Tofu with Spicy Cucumber Side”
• Josh Trapani, “Pythia of Science”

The honorable mentions, which we will post on our website, are:

• Mike Di Paola, “Who Are We?”
• M. Richard Eley, “Hot Dogs and Corn Flakes”

The winners will each receive $1,500, and the honorable mentions $250. We were not able to rank the five winners, so they will appear in random order. In this issue you will find Josh Trapani’s “Pythia of Science” batting lead-off for the winners.

We did not know the identities of the authors when we were judging the articles, and what we learned we did finally unmask them also surprised and pleased us. Yes, there were some professional fiction writers, but also a journalist, a scientist, a policy wonk, and a long-time corporate lawyer.

I know from my conversations with Issues readers that many of you have long been science fiction fans and will welcome these stories with open arms. But many of you severe left-brainers are shaking your heads at the waste of pages that could be devoted to clear, cold reasoned argument. I mean, really. The art was bad enough, but at least much of it is immediately pleasing to the eye. To reassure you, I confess that I have never been a science fiction fan. Over the years I have ignored the readers who have suggested publishing science fiction. Now I see that I was wrong. I’ve been surprised by how much I’ve enjoyed these stories, and I think you will be too if you give them a chance.

A better-informed case for the virtues of scifi has been made by two MIT Media Lab researchers Dan Novy and Sophia Brueckner, who developed a course entitled “Science Fiction to Science Fabrication,” which the students have renamed “Pulp to Prototype.” In a September 2013 email interview with Rebecca J. Rosen in The Atlantic, they cite examples of how scifi has played a role in inspiring in ways small (the inventor of the taser traces its source back to Thomas A. Swift’s Electric Rifle) and large (Winston Churchill’s scifi-stimulated wish for a death ray led indirectly to the development of radar, which might have been more useful).

They cite work at MIT in biomechatronics, tangible media, and fluid interfaces that mirrors popular themes in scifi, and find the precursors of immersive environments in the work of Ray Bradbury and Neal Stephenson. Philip K. Dick’s Do Androids Dream of Electric Sheep? apparently includes enough gadget ideas to provide student projects for an entire engineering school—in addition to providing the basis for the film Blade Runner.

But for Novy and Brueckner the most important contribution is not to provide project ideas but to encourage technologists to think more deeply about the implications of these technologies. Novy describes Mary Shelley’s Frankenstein as a “Gothic biopunk cautionary tale about the repercussions of man using technology and science to ‘play God’.” Although he believes that people sometimes use the potential dark side of new technology as a rationale for opposing all new developments, he nevertheless thinks that technologists need to keep these possibilities in mind and to follow development paths intended to minimize possible dangers. Science fiction can serve as an inexpensive product launch that enables us to see how a technology will be used by a variety of people and institutions.

Brueckner adds that the scifi thought experiment makes it possible to redirect a technology before it’s too late. As she says, “Once any sort of technology has users, it becomes extremely difficult to change it—even if you know it should or must be changed.” When she worked in software development in Silicon Valley, she found that her colleagues rarely asked themselves critical questions about how their work might be used. From her perspective, “reading science fiction is like an ethics class for inventors, and engineers and designers should be trying to think like science fiction authors when they approach their own work.”

But you shouldn’t read science fiction because it’s nutritious. Read it because it’s delicious. It’s fiction, an act of imagination. Appreciate the individual characters, the structure of scenes, the way that dialogue can reveal more than exposition. Get lost in it. Enjoy yourself.

Forum – Spring 2015

Demonstrable energy

In “Closing the Energy-Demonstration Gap” (Issues, Winter 2015), Richard Lester and David Hart have reinvigorated the national debate about how we can fund and build large-scale energy demonstration projects. The general gridlock in Washington and the resulting problems in maintaining a reliable source of federal funds dedicated to such projects have made it clear that our traditional approach is not working. In their article, the authors describe a new and innovative way in which projects might be funded.

They propose the establishment of a network of Regional Innovation Demonstration Funds. The revenue for these funds would come primarily from surcharges on electricity imposed by states either as public benefit charges, which many states have already established, or charges implemented by states to reduce greenhouse gas emissions. Some additional funds would come from the federal government on a matching basis. They also call for establishing a new federal agency, the Energy Innovation Board, to serve as a “gatekeeper.” To be eligible for support from the Regional Innovation Demonstration Funds, projects would have to be shown to the federal gatekeeper that they have the potential to lead to significant reductions in carbon emissions “at a declining unit cost over time.”

As the authors acknowledge, this proposal will have to overcome several hurdles to be adopted and implemented. Among them is the challenge of persuading states to raise the funds from consumers of electricity within their borders. This will be doubly difficult since these regional funds would often be supporting projects located in other states.

In spite of the recognized obstacles, this proposal is a significant addition to the debate about how to fund the technology development the nation will need to effectively address the challenge of climate change. The authors deserve thanks for their thoughtful proposal and the proposal deserves serious consideration.

Richard Lester and David Hart have made a welcome contribution to the national discussion on energy innovation. Theirs is a refreshing take on a topic that has been the subject of much debate and research.

For large-scale, capital-intensive projects with the potential to contribute to important societal goals well beyond the benefits accruing to the companies involved—e.g., through knowledge spillovers or future mitigation of environmental externalities—there is a strong case for the sharing of costs and risks between the public and private sectors. In their article, Lester and Hart build on previous suggestions from the President’s Council of Advisors on Science and Technology regarding, for example, the need to generate off-budget funding through power system charges or regional cap-and-trade programs, making the point that states already impose charges on electricity for public benefits funds. The authors propose creating regional organizations to manage such funds professionally. Its regional focus and organization is the main novelty in the proposal, which does retain some federal-level involvement through the use of a federal board to approve projects and through the use of co-financing from the Department of Energy.

The idea of creating a decentralized system of energy technology demonstrations has important merits, particularly in the current political environment, in which garnering federal appropriations for the large sums of funds needed for demonstrations is difficult. The regional focus also allows rate payers to contribute directly to developments and investments in their area. In terms of drawbacks, the decentralized approach will require time and effort to set up several new organizations mentioned by the authors. It may also increase burdens for those trying to propose projects, since they would need to get federal certification and then go through the competition process in one or more Regional Innovation Demonstration Funds (RDIFs), incurring transaction costs each time. Nonetheless, given that alternative proposals over the past decade have gone nowhere, RDIFs are worth exploring.

There are important policy principles that could guide organizations supporting technology demonstrations, or “debugging projects,” some of which go beyond those mentioned in passing in the article. These include (1) creating a long-term policy, such as some form of price on carbon, to more effectively motivate private sector investment; (2) selecting technologies with the potential to have a material impact on major policy goals; (3) absorbing risk that is difficult for the private sector to finance alone, and, in particular, providing support for unproven technologies even when there is a risk that they may not prove to be competitive; (4) facilitating the dissemination of information to others who could benefit from it, to maximize public benefit; (5) outlining a clear exit strategy, which involves setting criteria for when projects would be stopped if they do not perform, to avoid large losses; and (6) pursuing a portfolio approach to ensure a diversity of paths.

A key challenge to a demonstration effort that has yet to be discussed will be to engage the A-game of investors and technology companies, particularly in areas in which there is uncertainty regarding the future market of the technologies, such as carbon capture and storage. With all its difficulties, this is an important policy issue that needs fresh thinking such as that provided by the authors.

Abdulla and Morgan make a compelling case for new ways to enable the entry of promising technologies into the marketplace. I agree that a regional approach to demonstration projects, with vetting by state trustees, oversight by an energy innovation board, and financing with matching federal funds, would be a judicious mechanism to boost not just new energy technologies, but, indeed, many novel ideas that are in the proof-of-concept stage.

I applaud their suggestions and believe their ideas, while focused on energy, have relevance to a more general problem: namely, that of the so called “valley of death,” where many technologies languish because of the significant barriers they must overcome to get to the other side of the chasm.

Therefore, it behooves policy makers to recognize that beyond the financial resources required, there are many other “disconnects” within the innovation ecosystem needing intervention, assistance, and improved interaction. For example, one often finds that a technology that is proprietary in one field of application is not made available for other potential applications due to a lack of understanding of the intellectual property regimes that can protect a proprietary interest in one area while enabling its use in another. Also, it is not uncommon to find that a technical solution lies outside of a given company’s core area of expertise (or that a company’s focus keeps it from seeing new developments in adjacent fields). Indeed, “open innovation” and “prize-driven innovation” have now brought forward countless examples of unexpected sources of technological solutions, fruitful connections, and new applications.

Likewise, industry and universities are rarely sufficiently well-connected to make for successful exchanges. For example, industry funds about two-thirds of all research and development (R&D) in the United States, but it is telling that of all university research, only five percent is sponsored by industry. Federal incentives to encourage more investment by industry in partnership with universities would help bridge the gap between fundamental and applied research. There are good examples of how close collaborations speed the time from discovery to innovation, but imagine the additional boost to the economy if this was more common, as might happen with making permanent the R&D tax credit or markedly expanding the opportunities made possible via Cooperative Research and Development Agreements (CRADAs).

Of course, collaboration also requires the kind of rapprochement that is seldom seen between companies and universities, or even among companies themselves. All too many universities remain cloistered in the “Ivory Tower,” believing that working with industry is a prohibited endeavor. And too many companies have deep misunderstandings of intellectual property and assume that what universities develop should be available without an exchange of comparable value—be it financial compensation, research collaboration, or some other recognition that acknowledges an exchange for mutual gain.

The authors have brought us a useful framework, and I would welcome their exploring these additional nuances of the innovation ecosystem.

It is disturbing to read Lester and Hart’s recommendations for “closing the energy-demonstration gap.” How can the public hold on to what works when inexplicably favored experts want to “ramp up” their better ways? Here in New Mexico, under the influence of Portfolio Standards, we have given up inexpensive, traditional daylighting with skylights and windows for expensive photovoltaic power plants connected to the grid. This has been done in silence. Other recently neglected uses of the sun are passive heating and drying clothes on clotheslines. Such traditional non-electric uses of the sun are abandoned. Read Christine Lakatos’s Green Corruption website to understand the opportunity for kickbacks and crony capitalism possible with electricity and utilities, but not with clotheslines and passive heating. She has exposed far more than Solyndra.

Case for small nukes

In “Nuclear Power for the Developing World” (Issues, Winter 2015), Ahmed Abdulla and M. Granger Morgan provide a thoughtful look at the potential of small modular reactors. As they correctly note, there would be significant advantages to be able to manufacture such reactors in a factory and transport a fueled and operable reactor to a location where power is needed. The smaller size also helps in terms of managing decay heat in the event of an unplanned shutdown or malfunction. And a small modular approach is consistent with the fact that in many developing countries, the power grid cannot easily absorb a power plant of perhaps 1,000 megawatts of electrical output, typical of large conventional nuclear power reactors, nor is the capital needed for such a plant available.

The article notes that “Estimates of the capital cost per megawatt of first-generation light water SMRs [small modular reactors] lie a factor of two or three above that of conventional reactors.” And conventional reactors are having trouble competing in the United States now. The comparative economics of small nuclear reactors versus alternative electricity sources was not discussed, and this is not easily addressed in a general article such as this, in comparison with a site-specific study. Depending on the location, solar and wind electric-generating sources, perhaps with storage, may be competitive without requiring management of nuclear power technology, liabilities and accident response capability, nuclear proliferation, and waste management.

The discussion of insurance and liabilities for accidents is clear and provides useful information about approaches used elsewhere to increase coverage above what is available from private markets or what a government can commit to cover. And as the authors note, developing a pool of liability insurance does not ensure adequate emergency response.

The discussion of proliferation is sound, but waiting for improved proliferation risk models is not likely to be a good strategy. Models reviewed in the National Research Council study cited by the authors looked only at the technical characteristics of a system; the specific interest a host country may have in proliferating or acquiring relevant expertise was not considered. A related point concerns what countries would be suitable for such reactors based on political stability and the likelihood of internal conflicts or terrorism. Just as a small reactor could be used as a source of materials for nuclear weapons proliferation or a dirty bomb, it also could be an attractive target for terrorists.

The authors do not discuss radioactive waste management at length and treat it as something that would-be modular reactor vendors should provide as an integrated service with reactor sales and replacement when refueling is needed. This misses a major point on waste management. Of the reactor suppliers, as far as I know, only Russia offers fuel take-back. The decision to lease fuel and take it back after use in a reactor is not an option a vendor in the United States or Western Europe could offer, given the policies in those countries. This is not to be confused with U.S. efforts to have spent fuel from research reactors returned to the United States; this is a nonproliferation program that addresses highly enriched uranium control and would not apply to low-enriched uranium that might be used in a small modular reactor.

Controversial conservation

As presented by Keith Kloor in “The Battle for the Soul of Conservation Science” (Issues, Winter 2015), the characterization of a “fight” between “new conservation” and “traditional conservation” regarding “whether conservation should be for nature’s sake or equally for human benefit” is inappropriate, sensationalist, and largely based on a simplistic characterization of the history and values of the conservation movement.

There is no “new conservation.” Consideration of utilitarian values of nature dates back throughout—and indeed long before—the conservation movement. Plato wrote of the negative consequences of deforestation and soil erosion, although societies through history have protected refuges to ensure the sustainable harvest of wildlife.

Similarly, even though conservation focused on the intrinsic values of nature does, indeed, date back for millennia (consider, for example, the inclusion of nature in the Chinese moral systems of Laozi and Zhuangzi, and the protection of sacred groves and species safeguarded by indigenous people around the world), it remains the major motivation for a large proportion of the conservation community to this day.

The author is right to note that founders of modern conservation such as Theodore Roosevelt and Aldo Leopold viewed both intrinsic and utilitarian perspectives as important, and did not see a contradiction in believing and promoting both. Combined values remain dominant throughout conservation. For example, both the Convention on Biological Diversity (which entered into force in 1993 and now has 194 government parties) and the 2011–2020 Strategic Plan for Biodiversity and its 20 Aichi Targets are based on both intrinsic and utilitarian values.

The International Union for Conservation of Nature (IUCN) was established in 1948 and now has a membership of nearly 200 governments and government agencies, along with more than 1,000 nongovernmental organizations. The IUCN’s entire history is characterized by its cherishing and drawing together of the intrinsic and the utilitarian values of nature, as is well demonstrated in Martin Holdgate’s The Green Web, published in 1999.

Indeed, the IUCN’s vision of “a just world that values and conserves nature” is founded on respect for and belief in the intrinsic values of both nature and people. The chair of IUCN’s Species Survival Commission, Simon Stuart, writing in Biophilia, published in 2014 by the conservation foundation Synchronicity Earth, has called for “a society and a global economy which makes the rights of people and nature unnegotiable.”

As for the author’s notion of “Embracing the Anthropocene,” the IUCN sees neither the ongoing loss of global biodiversity through genetic erosion, species extinction, and ecosystem conversion, nor the homogenization of local biodiversity through the spread of invasive species, as inevitable.

With proactive biosecurity, eradication, and control, the negative impacts of invasive species can be minimized, as demanded by number nine of the Aichi Targets. The IUCN’s Invasive Species Specialist Group provides extensive resources to support such actions.

Meanwhile, number 12 of the Aichi Targets calls for the prevention of extinction of threatened species. Although the trends in extinction risk documented by The IUCN Red List of Threatened Species are negative, an analysis published in 2010 by Mike Hoffmann and colleagues in Science shows that the slide of bird and mammal species toward extinction would have been 20 percent faster in the absence of conservation efforts over the past three decades.

In sum: conservation works, both for people and nature—but we need much more of it. And we need to put a stop to simplistic and divisive arguments about whether conservation is designed to benefit nature or people: it has to do both.

This essay touches on many aspects of the current conservation debate, but my response addresses a single important fault line between the camps. It concerns the relationship between humanity and the natural world: Are humans part of, or separate from, nature? The new conservation perspective (represented by Peter Kareiva and advocated by a broader platform calling itself post-environmentalism or eco-pragmatism) claims that humans are part of the natural world and that their interventions are natural. According to wilderness defenders (represented by Michael Soulé and the rewilding movement more widely), human beings have separated themselves from the natural world and treat it primarily as a resource base. This difference is so fundamental as to inform most of the particulars of the “battle.”

New conservationists argue that like other species, human beings alter and disturb their environments; in response to disturbance, life adapts, rebounds, or markedly changes. Nothing in nature is ever static anyway, and human-driven modification is an expression of such perennial change. This idea that humanity is simply authoring another chapter of Earth’s environmental history naturalizes human activities as well as the human impact overall. Wilderness defenders, on the other hand, do not tend to see the human impact as “natural,” but as undergirded by an anthropocentric worldview that frames our perception of nature and guides our activities. Were humanity to create an alternative civilization of restraint, respect, and inclusiveness toward nonhuman nature, then our relationship with Earth would be entirely different. Far from naturalizing the human juggernaut, the pro-wilderness platform politicizes it. Humans approach nature equipped with the ideologies, language, and tools of a colonizer; although humanity has come to reject such a colonial stance with respect to people, the same stance toward nature continues to appear normal.

The mistake of naturalizing humanity’s activities is illustrated by the article’s implicit comparison of a volcanic and human-driven disturbance. Peter Kareiva reportedly saw the environs of Mount St. Helens burst with life in a handful of years after the eruption. The lesson he drew is that nature is not fragile, as environmentalists so often intone. It is undoubtedly true that life is powerful, proliferative, and rebounds after natural disturbances. Life has also recovered from mass extinction episodes, proving to be resilient in the long haul and wondrously creative on time scales of millions of years.

But the human impact should not be conflated with natural disturbances that have episodic, intermittent, and (barring catastrophic events) regional effects. In contrast, the effects of humanity are cumulative, mounting, and global. The dominant social pattern exhibited by civilized humanity is to invade natural areas; extinguish or displace native species; convert entire biomes for human purposes; fragment continental landscapes with settlements, agricultural monocultures, roads, and other developments; and use and manage most remaining natural places. Compared with a volcanic eruption, human-driven disturbance is relentless and relatively permanent. It is also intentional and driven by an attitude of dominion and entitlement. On a positive note, though, this adversarial-to-nature human identity is not inborn. Humans can change: We can choose to scale down the human enterprise instead of accepting or trying to “green” its expansionism.

Looking on the bright side today has value, but not at the price of one-sided information. The author cites Kareiva’s optimism regarding the reshuffling of ecologies: “If you live to be 50,” he is quoted as saying, “one out of two species you saw in your back woodlot will have been swapped out for a different species—but the number of species would not have declined.” In a world headed toward 10 billion people who all want prosperity, if you live to be 50, your back woodlot may well no longer be there. In many places, if you do have a back woodlot, it would have been a forest when you first saw it. Should business as usual prevail, if you live to be 50, the planet’s overall diversity of species will be far lower than when you first played in the woodlot. And the species in that woodlot are likely to overlap a good deal with those in other woodlots around the world. If instead of changing itself, humanity continues changing the world, a toddler today who lives to be 50 will be alive in a world well on the way to the Homogocene, as some prefer to call the coming age of Man.

The new conservation (and eco-pragmatist) platform seeks to adjust to civilization’s expansionist trends rather than confront them. It does not challenge the concurrent rise of the global population and overconsumption, or what this twined tide bodes for the planet. It appears willing to concede the option of geoengineering the climate and to accept that “the price of progress” could be a mass extinction. Importantly, it refuses to consider that humanity’s wiping out wild species, subspecies, and populations—and potentially causing a mass extinction—poses profound ethical ramifications.

Given our predicament, the other major player cited in the article, Michael Soulé, is glum about conservation prospects—an understandable position. But the author says that Kareiva is “neither pessimist nor sunny about the state of the world. To him, it just is what it is.” Would we say “it just is what it is” about injustice or genocide perpetrated against fellow humans? That would be unthinkable. And yet, regarding what poet Robert Frost called “the general mowing” of nonhuman nature, such an attitude appears okay. But for many conservationists and for the rewilding movement, “it is what it is” amounts to a nonstarter. We can agitate and act for the natural world’s ecological restoration and for awakening the human desire for a different way of being within the biosphere.

By using “conservation science” rather than “conservation biology,” Kloor’s article demonstrates one way that perspectives on conservation have changed in the three or four decades since it emerged as a field of scientific study. Proponents and practitioners came to realize that efforts at conservation could not rely solely on biology to provide solutions, and that fields such as economics, policy, and other social sciences had to be incorporated to craft successful programs.

Among other differences between biological sciences in general and conservation science in particular, there is often a sense of urgency as species of conservation concern decline or disappear, controlled experimental studies are often impossible, and researchers are often called on to help guide policy decisions before they have collected information they might want for an informed decision. Conservation is also unique because there is so much room for one’s philosophical biases and idiosyncrasies to influence conclusions about whether and how to conserve biodiversity. Personal experiences that contribute to one’s weltanschauung are likely to affect conclusions about how best to solve the dilemmas raised by the synergistic confluence of the growing human population, growing expectations about standards of living, and the increased demand on natural resources they generate. There is no single best way to pursue conservation.

Given the philosophical nature of such issues, it is not surprising that there is a spectrum of conclusions about the best approach to such difficult problems. Ecology contrasts with other sciences in the lack of absolutes, and conservation science is a prime example of this. In one ecosystem, removal of predators is seen as the solution, while in another, it is the re-introduction of predators. Invasive species cause extinctions in some ecosystems, and seem benign in others.

The differing perspectives of Soulé and Kareiva, highlighted in the article, are an inevitable outcome of the growth of a relatively young field of science that incorporates so much from the realm of philosophy. What remains to be seen is how the broader, and in particular the younger, community of conservation scientists and practitioners responds and develops after having these ends of a spectrum of perspectives highlighted. It will also be interesting to see how nongovernmental organizations and their donors respond. One possibility is that the differences among existing organizations (e.g., The Nature Conservancy, Conservation International, World Wildlife Fund, Wildlands Network) that result from their having different focuses and philosophies will continue to diversify, perhaps opening up niches for groups with new emphases.

I think the current debate will continue, perhaps concluding with an agreement to disagree, but with the potential to continue growth and change in the maturation of the science. It is valuable to have the discussion, and I hope all of the participants will recognize the value of continuing it, rather than refusing to communicate.

NIH’s predicament

In “Has NIH Lost Its Halo? (Issues, Winter 2015), Robert Cook-Deegan has cogently described the crosscurrents affecting the National Institutes of Health (NIH). This venerable institution can rarely satisfy its patrons on the congressional left or right, nor can it move quickly enough to meet expectations of groups that advocate for patients with serious illness or disease. For the basic scientist, NIH is too clinical; while for the clinician, its priorities neglect pressing diseases. Industry believes that NIH is distant from the most effective means to find new drugs and devices. Those in the physical sciences and engineering believe they are the preferred routes to the country’s economic development, security, and competitive strength. Universities fault it for failing to assure sustained, predictable investment in programs and people. Above all, to many, NIH seems unlikely to make the most of scientific knowledge that is potentially valuable to medicine and public health. The undercurrent is a growing belief that more money—by itself—will be inadequate for the task.

Three additional factors account for NIH’s predicament:

First, dramatic successes in medicine of earlier decades (such as polio vaccines in the 1950s or AIDS therapies in the 1990s) have been few in recent years, especially for diseases of increasing prevalence, such as Alzheimer’s, autism, or adult diabetes. The pace of discovery is slowing, and the interval to application at the bedside is lengthening. To put this another way, productivity has declined. The drop is due primarily to the intrinsic difficulty of the science relevant to these diseases.

Second, the NIH mission is ambiguous. Is NIH a science agency or a public health agency? The diffusion of responsibility among the Centers for Disease Control and Prevention, the Food and Drug Administration, the Surgeon General and Public Health Service, the military, and NIH creates this ambiguity. Inconsistent responses to emerging infections (such as coronavirus or Ebola) are emblematic, since even within the Department of Health and Human Services (HHS), which oversees NIH, rapid trials of vaccines and antivirals are stymied. Similarly, is NIH expected to find new, effective educational, behavioral, and social interventions (such as for drug addiction or obesity), which are rather distant from biology yet have important roles in disease prevention and treatment? In an era when suicide claims more lives of the young than cancer, such criticisms become persuasive.

Third, NIH’s current organization and funding priorities may not reflect the way biomedical science might best be conducted. Basic mechanisms, such as those in cell signaling, biological networks, the cell-cycle, and protein-protein interactions, have wide potential utility against many diseases. Within NIH, the right mix of basic, clinical, “big science,” and individual laboratory investigations has been elusive. Successive NIH directors have sought remedies to these shortcomings, through such efforts as the National Centers for Advancing Translational Sciences, the Clinical and Translational Science Awards (CTSAs), and the Advancing Medicines Partnership. These have been incremental and not (yet) unambiguously successful in boosting productivity. Therefore, the continued Balkanization of basic studies within disease-defined institutes makes diminishing scientific sense.

What changes might improve NIH’s effectiveness?

Create an Institute of Basic Biomedical Science. The institute would have responsibility for laboratory-based studies, and would function much as do the freestanding Howard Hughes, Broad, or Whitehead institutes, with a focus on biological mechanisms and platform technologies applicable to many diseases.

Reorganize the Clinical Center as a Translational Institute. The institute would conduct rapid proof-of-principle and high-risk/high-reward studies in humans, using NIH and the university-based CTSAs, which would operate with one another seamlessly.

Bring NIH closer to universities, companies, and investigators. Mobility between external institutions and all NIH divisions should be the rule, not the exception. Similarly, interchange of biological material, intellectual property, clinical and scientific databases, informed consent procedures, and clinical trial participants should be effortless, with speed and efficiency rewarded. The primary measure of effectiveness should be the speed with which an answer to a particular scientific or clinical question is found: Yes it works, or No it doesn’t, but here is how it can be modified and tried again.

Clarify within HHS responsibility for devising educational and behavioral interventions. NIH’s natural role is in the science relevant to particular conditions and early trials, a role parallel to that in biomedical studies.

Of course, such changes will not be undertaken easily. Yet, we must remember that the stakes are high. In an era when the nation’s population is aging, the cost of care is growing (albeit at a slower rate), and human need is obvious, we must become much more effective in applying the stock of scientific knowledge that is close at hand. This is a moment when radical change is warranted.

Free genetics innovation

The article by Henry Miller and Drew Kershen, “Give Genetic Engineering Some Breathing Room” (Issues, Winter 2015), accurately captures the dismal history of U.S. regulators of genetically modified plants and animals. Their scholarly and dispassionate essay describes the history of the science and how the various federal agencies involved managed to place politically based policy considerations above science and law to delay or deny applications that offer alternatives and improvements to conventional agricultural and animal products.

Although the authors do not address the dichotomy or logical contradiction, the same technology has been welcomed and adopted widely in the production of novel biologicals for medical use. The first example of this was, of course, Henry Miller’s leadership in the review and approval of the first recombinant human health product, called Humulin, in 1982. The authors do highlight the burdensome and sometimes irrational policies that have been pursued during the past 30 years, and the failure of regulatory agencies to demonstrate leadership in informing societal concerns for new products based on modern molecular genetics. In my own experience, the role of economically vested opposition groups have had enormous political and regulatory impacts on administrations and regulators, misleading the public regarding the safety and value of new technologies. Such a corruption of a science-based regulatory policy introduces arbitrary and subjective regulation, stifling innovation and discouraging investment in and development of new products.

The authors are absolutely correct when they observe: “We need and deserve better from governmental regulatory agencies and from their congressional overseers.” In my view, we must make science-based regulation a reality, not a slogan.

Diversifying STEM

As Monica Gaughan and Barry Bozeman document in “Daring to Lead” (Issues, Winter 2015), critical issues for the nation’s science and engineering infrastructure remain unsettled. Among them, the nation faces a demographic challenge with regard to its science, technology, engineering, and mathematics (STEM) workforce: underrepresented minority groups comprised 31.5 percent of the national population in 2013, yet during the same period they earned less than 15 percent of all engineering bachelor’s degrees. Although the case has been made for increasing the domestic talent pool by increasing opportunities for native-born students to prepare for study in STEM disciplines, there are still many individuals who are not likely to have these opportunities available to them.

Since 1974, the National Action Council for Minorities in Engineering Inc. (NACME) has developed partnerships at 160 colleges and universities, providing $142 million to over 24,000 underrepresented minority engineering students. NACME has had a long history of supporting the engineering pathway for African American, Latino, and American Indian women and men. Although the primary delivery model has been through scholarships supported by a preeminent group of Fortune 500 companies, NACME has learned that achieving success in increasing underrepresented minority participation in engineering study requires a multifaceted strategy to address the continuum from middle school to workforce entry. Our multifaceted strategy integrates:

Scholarships and university relations. NACME currently partners with a national network of 51 leading colleges and universities to recruit, enroll, educate, retain, and graduate increasing numbers of underrepresented minority students. We are responsible for more than 1,000 scholarships awarded annually to these students. Through the NACME Scholars Program, we provide block grants to colleges and universities that, in turn, award funding as part of financial packages to qualified students enrolled in engineering programs.

Pre-engineering. NACME’s pre-engineering strategy directly addresses the lack of “dually disadvantaged” students in the STEM pipeline. As founding partners, NACME, Project Lead the Way, and the National Academy Foundation launched the Academies of Engineering (AOE), a network of career-themed academies. Through open enrollment, the high schools provide students with a strong science and math education to assure college readiness for engineering study. Scholarships are awarded to AOE high school graduating seniors, and NACME’s corporate and university partners participate on AOE advisory boards. In addition, NACME provides a suite of awareness materials to middle schools and high schools across the country to inform students about the possibilities of an engineering career.

Research and program evaluation. Since 1974, NACME and its partners have fostered research-based changes in policies and practices that guarantee equal opportunities for the preparation and participation of all U.S. students in STEM. With the support of corporations, foundations, government agencies, and individuals who share our vision, NACME has conducted research and analyzed trends in education, engineering enrollment, degree completion, and workforce participation for underrepresented minorities. We have raised awareness and promoted the discussion of equity and engineering education issues throughout our history.

Engineering public policy. To further address the institutional barriers that contribute to the deficit of women and underrepresented minorities in STEM, we provide research-based recommendations on federal policy in our Research and Policy Brief series and our new Policy Statement series.

The achievement gap between underrepresented minorities and their peers in the STEM subjects is substantial, especially for those who are dually disadvantaged. To improve STEM achievement for all students, multifaceted pathway strategies that include financial support for those from disadvantaged backgrounds must be funded and replicated.

Retirement conundrum

It is good to know that Alan Porter has not let any grass grow under his feet since his early official retirement from Georgia Tech. He has obviously put together an absorbing, rewarding, and productive post-retirement career through his continued affiliation with Tech and his leadership engagement at Search Technology, Inc.

Abstracting from his positive personal experience, however, brings at least two questions to mind. First, Porter suggests that regularizing opportunities for retired faculty to engage in research could help open faculty positions for new PhDs by incentivizing earlier retirements. Yet, his own experience, if typical, would suggest that freeing experienced faculty members from teaching and administrative duties so they can focus on research might have the opposite effect if those “retired but active” faculty were thus able to claim an even larger share of federal research dollars than they already do. This is part of the societal dilemma caused by the current simultaneous rapid growth of both life expectancy and worker productivity. That dilemma is whether it is better to (A) keep older workers working and contributing longer, thus blocking opportunities for younger workers, but freeing them of some of the burden of supporting the elderly, or it is better to (B) encourage older workers to retire sooner, thus opening opportunities for younger workers, but adding to their burden of elderly support. This is a larger question than Porter raises, but his proposal is a good illustration of the conundrum.

Second, Porter also suggests, but does not fully explore, the implications for universities of extending privileges to conduct research under the university’s umbrella to persons who are no longer employed by the institution. As a former Vice Provost for Research, I am aware that research performance, funded or not, is subject to increasing numbers and levels of regulations intended to protect research subjects, avoid conflicts of interest, protect health and the environment, guard against sharing classified and sensitive information with potential enemies, and so on. Although much of this regulation directly affects the activities of faculty members, its enforcement is largely through the institution. The fact that the faculty member is employed by the institution provides the mechanism through which regulations are imposed and enforced. Porter is right—institutions need to reexamine the implications for regulatory compliance of continued participation by retired faculty members in university research. So far as I have been able to determine, my own former employer, George Mason University, has no provisions for governance of such relationships. An inquiry of one of the principal organizations responsible for representing university interests in federal regulatory agencies turned up no systematic attention to this question. A few universities have adopted their own policies on such matters. If Porter’s encouragement to “retire to boost research productivity” is acted on by very many of our colleagues, addressing its implications for responsible conduct of research will become a pressing matter on their campuses.

Humanistic engineering

To say that Carl Mitcham in “The True Grand Challenge for Engineering: Self-Knowledge” (Issues, Fall 2014) offers a strong critique of the current state of engineering in the United States would be an understatement. He presents a richly insightful and powerful indictment of the dominant paradigm of engineering education, culture, and professional practices. At the foundation of his indictment lies the idea that engineers need to do much more to connect the dots between the work they do and overall human well-being. And this cannot happen, he argues, unless engineers engage in humanities-informed critical reflection about what it means to engineer itself.

I wonder if Mitcham both underestimates the urgency for engineers to engage in such reflection, and overestimates what humanities faculty might want to or be able to do to help spark and inform this engagement.

Although the second Axial Age he mentions demands attention to techno-human relations, a third Axial Age is already looming on the horizon. In it, as Luciano Floridi observed in The Fourth Revolution, techno-techno relations will replace techno-human ones. Humans will become “redundant,” “outside the loop.” The large body of social science research underscoring how poor we are at decision-making helps bring this age ever closer. The intense race among automobile manufacturers to perfect self-driving cars is part of this general phenomenon of innovation cum self-distrust. But the more engineering effort contributes to the Internet of Things, the more pressing it becomes for engineers to think not only about sustainability—a difficult-enough responsibility already—but also about what kind of world this effort would create and the prospects for well-being within it. Would it be a world, to put it bluntly, worth living in?

Engineering in the United States is arguably resource-poor when it comes to reflecting on the grand challenge of self-knowledge. But the same can be said for the humanities with respect to thinking seriously and critically about technological innovation. For example, it is possible to get an undergraduate degree in philosophy without having to think deeply, if at all, about the engineered world. Even the most highly regarded ethics textbooks seem written solely for issues connected to the first Axial Age; it is the trolley problem that is the focus of ethical consideration, not the trolleys themselves. What numerous observers have noted about the average U.S. citizen also holds true of most philosophy students and faculty members: they are ill-prepared to address the difficult questions about value and well-being connected to technological design.

Amidst these sobering facts there is still some good news. More venues exist now than a decade ago for engineers, engineering educators, and those in the humanities to come into contact and have frame-of-reference-expanding conversations with one another. These include the Engineering and Liberal Education Symposium at Union College, now in its eighth year, and the Forum on Philosophy, Engineering, and Technology, of which Mitcham was a co-founder. Consciousness of the need for beginning engineering students to be able to frame problems as technical-social in nature—and not merely technical—is spreading, as are efforts to radically revamp introductory engineering design courses. Such changes are indeed at the margins, but one can imagine a “halo effect” coming from them that would contribute to accelerating change in entrenched practices and attitudes in engineering.

But it is still important to bear in mind that the percentage of women in both professional engineering and professional philosophy in the United States is roughly the same: 22 percent. For this accelerating change to happen, engineering and philosophy need to get their own houses in order with regard to increasing this percentage and that of other underrepresented minorities. For both of these professions, this is another Grand Challenge.

Carl Mitcham offers a thought-provoking and much-needed discussion of the true grand challenge for engineering. I look at this from a European perspective and find that the issues raised regarding engineering education are virtually no different. Mitcham raises a number of issues, one of which is related to C.P. Snow’s “two cultures” argument. I agree with him when he differentiates between the cultures of “science and the humanities” and “engineering and the humanities.” I agree with him when he argues that all engineers need to become critical thinkers, become critically reflective, and become more than technological problem solvers. As elucidated by Andrew Feenberg: “engineers tend to be more at home with ‘function’ but have no place for meaning.”

I would suggest, however, that there are also important issues to be considered relating to the concept of perception: of what is an engineer and what it is to be one. These perceptions can serve not only to shape the expectations of those attending engineering schools; they can and do affect the various curricula on offer. These perceptions about engineering tend to orientate toward a technical model denoting the concept of engineering and engineering education that, as Mitcham rightly points out, are distinctly lacking any education directed toward the humanities.

In schools across Europe, science education is perceived by the public, politicians, and students as an important subject for study. A good examination result in this subject in high school is, for the most part, considered to be a prerequisite for entry into an engineering degree. Moreover, science education—and physics, in particular—is considered to be an area that will help to drive economic growth. For this reason, a lot of taxpayers’ money is invested in research not just in science and engineering, but into ways and means for encouraging young people, and particularly females, to take up science and engineering careers.

Significantly, the same perceptions do not seem to apply to technology education, or “industrial arts,” as it sometimes has been called, in the United States. This is a subject area that openly aligns itself with engineering education. The International Technology Education Association in the United States recently changed its name to become the International Technology and Engineering Educators Association. In Europe and elsewhere in the world, technology education tends to hang on to its industrial past. Even though a great deal of research is being done to change this emphasis, classroom practice tends to remain grounded in technical education, a curriculum having an emphasis on the development of workshop-based practical skills related to trades-based occupations. These perceptions—about school-based technology education being related to industry and science education being related to science and engineering—tend, in my view, to emphasize, perceptually at least, the science and humanities paradigm over the more important engineering and humanities paradigm offered by Mitcham.

Since the National Academy of Engineering publicly articulated its “14 Grand Challenges for Engineering in the 21st Century,” many engineering educators have used its ideas to motivate their work. Prominent among them is a reflective response from a social justice perspective by Donna Riley, presented in an article titled “We’ve Been Framed! Ends, Means, and the Ethics of the Grand(iose) Challenges,” published in the Fall 2012 issue of the International Journal of Engineering, Social Justice, and Peace. Riley was concerned with the process surrounding the framing of the Grand Challenges, and also with the series of ethical questions it generated about the specifics of the challenges and the processes that gave rise to them.

For the sake of precision, the apparent “Grand(iose) Challenge” hyperbole put forward seems in need of epistemological clarification. The notion of “challenge” suggests that a particular phenomenon is or rather must be perceived by someone (epistemologically speaking) to constitute a challenge. Without a perceiving mind, there would be no “challenge.” Hence, it would be more appropriate to speak of “challenge perception(s).” This is a main point made by Riley. She asks: Who chose the challenges? What were their underlying assumptions? Should the grand challenges be undertaken, and if so, for which ends? How should they be defined and pursued, and through use of which means?

Taken at face value, Mitcham’s labeling of the “True Grand Challenge” seems fraught with the same epistemological imprecision as the “14 Grand Challenges.” On closer inspection, however, such suspicion vanishes as Mitcham’s main line of argument is of an axiological nature implicitly in line with Riley’s questions. But more pointedly, he argues that “Engineers, like all of us, should be able to think about what it means to be human. Indeed, critical reflection on the meaning of life in a progressively engineered world is a new form of humanism appropriate to our time—a humanities activity in which engineers could lead the way.” The author devotes substantial attention to a penetrating analysis of why such an endeavor has so frequently failed, and even worse, why it was programmed to fail due to the dominant epistemological core-periphery distinction in engineering education.

Mitcham shows how humanities faculty working in engineering schools struggle to justify their courses. He also shows how many of the opportunities for humanities provided by ABET’s Engineering Criteria 2000 have been “lost in translation,” leading to three ideal typical approaches to justify the value of the humanities: namely, an instrumental, an enhanced instrumental, and an intrinsic-value approach. Only the latter provides a conversation space for critical thinking and questioning circumscribed by the Socratic maxims “(Engineer) know thyself” and “The unexamined (engineering) life is not worth living.” In sum, both the Mitcham and Riley articles provide a richness of material and original insights that supplement each other very well. They will no doubt stimulate further research on the “Grand Challenges” in the United States and elsewhere, both of an instrumental and a critical reflective nature.

In the end, there is hope that they might also be able to serve in pushing through a political agenda aiming at changing our unsustainable way of life related to what I consider to be the three Greatest Challenges of Humanity: climate change; the population bomb; and social injustice locally, nationally, and globally.

I completely agree with Carl Mitcham that self-knowledge for engineering students and engineers is quite important. Engineering education in Japan, unfortunately, faces difficulties similar to those the author so ably explained. The technical community is concerned about the image of engineering in the public sphere and its limited attractiveness to students, but engineering programs, even if accredited by the Japan Accreditation Board for Engineering Education, almost never give us any tools to reflect on what it means to be an engineer. As graduate attributes and professional competency have been defined more strictly, engineering students and teachers are forced to accomplish many tasks to achieve these requirements in an overloaded curriculum. There is not enough room for integrating humanities and social sciences into the engineering curriculum.

Besides that, engineering students and faculty have a tendency to look on these courses as extra work. An imaginary dichotomy, known as humanities course and science course, created for convenience sake, has a certain influence among us. We are still subject to C. P. Snow’s two cultures argument. Various improvements are required in the present situation.

These difficulties deserve to be overcome, because their settlement may finally lead us to a new point of view that encompasses the happiness and existential pleasure of engineers. Engineering institutes stress that all engineers have to give the highest priority to the safety, health, and welfare of the public. That is undoubtedly true. Then, who treats and realizes engineers’ well-being? Usually, the public hardly pays attention to the happiness and existential pleasures of engineers. In some textbooks on engineering ethics, engineers sometimes seem to be regarded as if they may contribute to criminal negligence. This view is simply wrong, but suggestive. To be more precise, we might excessively consider engineers as special. All of us have to return to and draw attention to the simple fact that engineers are human as well as members of the general public. Humanities and social sciences will help us have this kind of self-knowledge.

However, I am a bit pessimistic of our current strategy. Depending on the enrichment of engineering education for engineering students may soon encounter some new difficulties, because all of us, including engineers, live in an already well-engineered world. Amid the enormous amount of engineering products and artifacts, how could anyone continue to be a bystander? We all ought to know about engineers and engineering activity, and about the sociocultural context associated with them more strongly than ever before.

Therefore, I think that engineering education for nonengineering students may be needed in the near future. As a matter of course, this is not a critically examined hypothesis. But there is no doubt that contemporary society has been designed and constructed by engineering activities, and because of this, both engineers and nonengineers should have self-knowledge and also should keep trying to increase mutual understanding through engineering education.

Mitcham proposes that engineers need to examine what it means to be an engineer, and, further, that the humanities may offer the educational means to such self-knowledge. Although others have examined what should be done on the engineering side, I’d like to look at the role that humanities can play in enhancing this process of reflective engineering.

Take the case of philosophy, a privileged domain for reflective practice. Why is engineering wholly untouched by philosophy? The blame is not just with engineers and other professionals. For many years, philosophy, especially analytic philosophy, has failed to consider public issues. As a result of its own increasing professionalization, philosophy has become a form of scholasticism in which philosophers discuss with great sophistication of detail, issues that are not necessarily relevant to the fundamental questions of being human. Philosophy has often been socially and epistemologically ineffective. As Bertrand Russell put it in “The Place of Science in A Liberal Education,” philosophy lived in a “certain self-absorption.” Thus it was not surprising that professionals found it uninteresting.

Fortunately in the last three decades or so, philosophers have begun to work to break philosophy out of its academic isolation. But more must be done for philosophy to become more than a technique of logical and conceptual analysis.

From my observations in a developing country, I agree with Mitchum that interdisciplinary approaches to engineering and engineering education are lacking. Fortunately, the negative effects of economic crisis are forcing some changes, including mental changes. More and more broad-minded philosophers, sociologists, and engineers are turning to interdisciplinary research to improve the situation. They use websites to communicate with others, and they are contributing to fundamental change. They work to influence the model and practice of education, even from the elementary school, to introduce more integrity between knowledge on nature and culture. When the critical mass is achieved, the transformation will be effective.

Physics Envy: Get Over It

Physics studies different things, and in different ways, than other sciences. Understanding those differences is important if we are to have effective science policies.

Physics has long been regarded as the model of what a science should be. It has been the hope, and the expectation, that if sufficient time, resources and talent were put into the sciences concerned with other phenomena—in particular the life sciences and the behavioral and social sciences—the kind of deep, broad and precise knowledge that had been attained in the physical sciences could be attained there too. In science policy discussions there often is the presumption that all good science should be physics-like: distinguished by quantitative specification of phenomena, mathematical sharpness and deductive power of the theory used to explain these phenomena, and above all, a resulting precision and depth of the causal understanding.

Lord Kelvin’s remarks of over a century ago remain the generally held belief regarding the importance of quantification. “When you can measure what you are speaking about and express it in numbers, you know something about it: but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind.” Galileo’s remarks probably are the most famous argument for mathematical theorizing: “The universe…cannot be understood unless one first learns to comprehend the language and interpret the characters in which it is written. It is written in the language of mathematics.”

There is no questioning the amazing success of physics. It has cast a bright light on the underlying structure and operation of the physical world and enabled humans to use that knowledge to develop the technology that helped create the modern world.

But to what extent are quantification and mathematization necessary or sufficient for the remarkable achievements of physics? Certainly they are related. Quantification is an important part of the reason that physics can achieve such precision of description and predictive capability. And the mathematical structure of its theories not only provides amazing sharpness to its explanations and predictions, but also enables productive deduction and calculation to an extent greater than that of any other science. It is no wonder that scientists in other fields often suffer from physics envy, or that policymakers long for similar power in the sciences that bear on the problems they are trying to address.

But this may be a fool’s quest. The nature of the subject matter studied by a science strongly constrains both the methods of research and analysis that are likely to be productive and the nature of the insights that science can achieve. The emphasis on quantification and mathematical theorizing that has been so successful in physics may not be so appropriate in sciences dealing with other kinds of subject matter. Without playing down their value when attainable, neither quantified characterization of subject matter nor mathematical statement of the theory unifying and explaining that subject matter are strictly necessary, or sufficient, for a science to be precise and rigorous. Some sciences have achieved considerable precision and rigor without having these features. Other sciences have embraced these characteristics methodologically, but have not achieved particularly sharp illumination of their subject matters. I am particularly concerned with these latter cases.

For many sciences, the kind of precise, law-like relationships that physics has identified simply may not exist. On the other hand, the more qualitative understanding that these sciences can achieve can be illuminating and practically valuable. A number of the sciences whose insights are strongly needed to help society deal more adequately with the urgent challenges of today’s world are of the latter sort. The tendency of scientists and policymakers to think that such sciences should be creating physics-like knowledge can diminish the ability of society to take advantage of the knowledge that they are capable of providing.

When numbers are not enough

The nature of the subject matter studied by science differs greatly from field to field. As a consequence, the way the phenomena, and the causal mechanisms working on them, can be characterized and understood effectively also differs. And these differences strongly influence the kinds of research methodologies that are likely to be fruitful. This is not recognized as widely and clearly as it should be.

The subject matter that is today addressed by physics is quite special and seems particularly suited to quantitative and mathematical analysis. Thus consider the Newtonian treatment of planetary motion, which continues to serve as a canonical example of successful science. The location of any planet at any time can be completely described in terms of numbers, as can its motion at that time. Its closed path around the sun can be expressed in terms of parameters of the mathematical function that describe the shape of the orbit. Newton’s explanation involves the mass of each planet and the sun, and how they relate to each other, as well as their location, and this also can be expressed in equations and numbers.

The fruitful reduction of apparently complicated and varied phenomena to a set of numbers and equations is the hallmark of physics. Consider modern astrophysics, and in particular the study of whether, and if so the manner in which, the universe is expanding. Things like galaxies, the central objects of observation and analysis in this kind of research, would appear to be enormously complex and heterogeneous, and indeed they are—if one is asking certain kinds of questions about them. But for the purposes of exploring how the universe is expanding, the relevant complexities can be characterized in only a few dimensions, such as mass, age, location, and rate of movement away from the earth. The processes going on within and working on them would appear to be the same throughout the universe. This is the faith of physics as a science and it seems well born out. Astrophysicists are able to characterize what they are studying using numbers and mathematical laws, just as Newton did in his great work.

Physics is remarkable in the extent to which it is able to make predictions (which often are confirmed experimentally) or provide explanations of phenomena based on mathematical calculations associated with the “laws” it has identified. This analytic strategy sometimes is employed to infer the existence or characteristics of something previously unobserved or sometimes not even conceptualized, such as the argument that there must be “dark energy” if one is to understand how the universe is expanding. No other science comes close to physics regarding this kind of theory-based analytic power.

As philosopher Nancy Cartwright has stressed, however, the “laws” of physics hold tightly only under narrow or tightly constrained conditions, such as the vacuum of space or a vacuum in a laboratory. It is not apparent that such tight laws exist, even under controlled conditions, in all arenas of scientific inquiry. That they do seem to exist for physics should be regarded as an important aspect of its subject matter, not a general condition of the world.

But is the quantification of subject matter and mathematical form of theory strictly necessary for a science to be able to make reliable predictions and point the way, as physics so powerfully does, to effective, practical technology?

Consider organic chemistry. Numbers certainly are central aspects of the way elements and molecules are characterized. However, particularly for complex organic compounds, the way molecules are described involves significantly more than just numbers. What atoms are linked to what other atoms, and the nature of their linking, generally is described in figures and words. So too the shapes of molecules. And the characterization of the processes and conditions involved in the forming and breaking up of molecules is to a considerable extent narrative, accompanied by various kinds of flow charts. A part of the “theory” here may be expressed mathematically, but much of it is not.

Or reflect on molecular and cell biology, in particular the exposition of the structure and functioning of DNA, of genes, of gene expression, and the making of proteins. The characterization of DNA resembles the way organic molecules are characterized. Although the helix is a mathematical form, without exception that I know about, the double helix form of DNA is presented as a picture. The base pairs of nucleotides that in different combinations contain the fundamental biological information for the creation of proteins are depicted as strung between two backbone strands, and genes are depicted as sequences of the nucleotides. The processes that lead to the production of a particular protein similarly are described mostly in pictures and flow charts, accompanied by an elaborate verbal narrative.

As biology delves into more macroscopic matters such as how the cell forms proteins, the scientific perspective takes on characteristics that Ernst Mayr has argued differentiate biology from the physical sciences. There often is considerable variation among phenomena classified as being of a particular kind, with individual instances having at least some idiosyncratic elements. And the forces and processes at work tend to vary somewhat from case to case and need to be understood as having a stochastic aspect. The make-up of cells and the details of how a particular protein is made are good examples.

Yet description and prediction of the phenomena studied are quite precise in molecular biology—both those aspects that are basically organic chemistry and those that are more biological (in the sense of Mayr) in nature. Although in neither organic chemistry nor molecular biology does “theory” have anything like the analytic deductive power that theory has in some areas of physics, it does provide an understanding of considerable precision and depth. And as with physics, the kind of understanding that molecular and cell biology has engendered often has provided a clear guide to the practical design of production processes and products. But in organic chemistry and, even more so, molecular biology, although numbers are an aspect of the way phenomena are described, they are far from the full story; nor is mathematics the main language of theory.

In evolutionary biology, differences Mayr highlighted come into still sharper focus. The study of evolution these days takes from molecular biology the understanding of genes and gene mutation. However, its orientation as a field of study in its own right is to phenomena at a much more macro level: the distribution of different phenotypes and genotypes in a population of a species at any time, changes over time in these distributions, and the factors and mechanisms behind those changes.

A certain portion of this characterization is quantitative. Some of the phenotypic characteristics, such as the number of teeth or toes, height and weight, the length of a beak, or speed of movement can be counted or measured, but important phenotypic characteristics such as agility, strength, or attractiveness to the opposite sex may not be readily measurable, or at least not fully captured by numbers. In evolutionary biology, numerical characterization of phenomena, such as Darwin’s description of the beaks of finches on different islands of the Galapagos, almost always is embedded in verbal and sometimes pictorial language, which on the one hand provides a context for interpretation of those numbers and on the other hand contains significant information not included in them.

Not only does a full description of Darwin’s finches include qualitative information, evolutionary biologists also recognize that all finches on a given island are not exactly the same. On average they differ significantly from island to island, and even on a particular island there can be considerable variation. This is very different from the way physicists think of classes of things they study, say electrons, which are understood to have precisely uniform characteristics everywhere they occur. As I’ll explain in more detail below, the presence of a considerable degree of internal heterogeneity in the objects or classes of objects studied by many fields of science distinguishes them from physics in a very important way.

Also, in contrast with Newton’s great work, Darwin’s theory is expressed verbally. And this continues to be the dominant mode of theoretical articulation in modern articles and books concerned with evolutionary biology. Mathematical models are widely used in modern evolutionary biology, but they are not meant to depict, as does theory in physics, how things actually work (even if only under controlled conditions). I recall vividly a conversation I had several years ago with John Maynard Smith regarding the role of his formal models (for example those in his 1982 book Evolution and the Theory of Games) in evolutionary biology. He observed that “evolutionary processes are much more complicated than that. These models are just intellectual tools to help you think about what is going on.”

Yet while the understanding evolutionary biology has given us is largely qualitative, and does not enable sharp prediction of how species will evolve, or the formulation of tight “natural laws” like those Newton discovered, it shapes the way we look at a wide range of empirically observed biological phenomena and processes, and provides a convincing explanation for many. And that understanding is useful, practically. It provides guidance for a range of human efforts, from developing better plant varieties, to understanding and trying to deal with changes in the bacteria that threaten humans, to seeing some of the dangers of environmental changes to which we otherwise would be blind.

Describing the human world

The kinds of understanding that can be attained from the social and behavioral sciences diverge even more from those of the physical sciences. The phenomena studied are almost always very heterogeneous, and classifications somewhat blurry. The kinds of regularities that exist tend to be qualitative and stochastic, rather than sharp and precise.

Much of the description of the phenomena studied by the social sciences is qualitative and verbal. As in biology, the verbal description often is accompanied by numbers, which are intended to give greater precision to such description. However, how much precision is achieved obviously depends on how completely, accurately, and sharply those numbers characterize the phenomena they quantify. Here the situation in the social and behavioral sciences is very different from that in the physical sciences.

A good part of the difference is due to variations in the kinds of phenomena studied. Much of the subject matter treated by the social and behavioral sciences is not only quite heterogeneous, but the general conception of the nature of the phenomenon often has uncertain boundaries, for example, as with “unemployment,” “intelligence,” and “innovativeness.” Phenomena with blurry conceptual edges are not special to the behavioral and social sciences; consider the concept of a biological species where there is cross-species breeding, or the geological conception of an earthquake, which may be accompanied by foreshocks, aftershocks, and ongoing creep of the earth’s crust. In such cases, the phenomenon will often be operationally defined by the numbers used to characterize it. But choice of such numbers has an arbitrariness to it that may conceal the underlying fuzziness.

For example, consider the concept of unemployment, and the statistics used to measure it. What does it mean to be “unemployed?” In the standard measure, people are unemployed if they report that they do not have a job and have actively been seeking work but not finding it. However, the concept of not having a job but actively seeking one obviously has ambiguous boundaries. People who have part time jobs but want and are seeking full time ones are not included in the official unemployment numbers. Also, the official definition of unemployment excludes from the ranks of the unemployed people without a job who have given up hope of finding one and for that reason do not report they are actively searching. And, of course, there is no clear-cut notion of what “actively searching” means.

I am not attacking unemployment statistics. Rather, I want to illustrate that the numbers used by social scientists almost never have the hardness or precision of most of the numbers used in the physical sciences. A good part of the reason for that is that the phenomena studied often are not as sharply defined. As a consequence, analyses of the state of unemployment by knowledgeable analysts almost always involve a verbal, qualitative discussion and several additional numbers, for example the number of part-time workers, to supplement the standard unemployment figure.

In the case of unemployment, at least there are some obvious things to count or try to measure. For many of the subjects studied by the social and behavioral sciences there are no direct ways to count or measure the variables directly being addressed. If these phenomena are to be associated with numbers, some proxies need to be identified or some quantitative indicators constructed.

IQ is a good example. Although the concept of intelligence, and the notion that some people are more intelligent than others, is common and apparently useful in lay circles, there are real problems in laying out a sharp general definition of what intelligence means. In such circumstances there is a tendency to define the concept in terms of how it is measured, but those who know a lot about the subject matter often disagree about whether that definition is appropriate to a concept with fuzzy boundaries and heterogeneous attributes, like intelligence or unemployment. As a consequence, psychologists studying intelligence, and economists studying unemployment, tend to use such standard measures as part of a more general and largely qualitative characterization.

The situation is not dissimilar to that of the study of innovation. Again, a basic issue is that innovation cannot be defined in a way that is broad enough to cover the range of phenomena to which the term seems applicable, while also maintaining clear-cut definitional boundaries. Consider the kind of research involved in trying to assess the innovative performance of different firms in an industry. One plausible research strategy is to work with various written records of innovation in the field and what different firms have done, perhaps supplemented by interviews. The characterization of a firm’s innovativeness that would come out of such a study would be qualitative. However, informed people might be able to agree on at least a rough ranking of firms. And one could try to code indicators of innovativeness in the written records quantitatively and construct the interviews to provide a numerical score for various responses. In addition, one can use published numbers that have some relationship with innovation, such as firm research and development (R&D) expenditures and patents. For many economists, it has proven attractive to focus their research on these kinds of numbers by, for example, exploring the relationship between R&D spending and patenting.

However, R&D expenditures, or patents, have serious limitations as measures of innovative input or output. In many industries, much of innovation goes on through activities that are not counted as R&D. Many innovations are not patented. Qualitative descriptions of the relevant technological histories, and of the role played by different firms and other economic actors in those histories, almost certainly provides not only needed interpretation and context for the numbers but also a way of assessing their meaningfulness. The numbers are part of a description that also is qualitative to a considerable degree. Moreover, paying attention exclusively or largely to such numbers not only ignores or downplays other kinds of knowledge that are at least as relevant, but also can lead to a very distorted view of what is going on.

Complicated is different

Let us reflect again on Newton’s laws of planetary motion. Although planets clearly differ in a large number of ways, for the purpose of understanding their orbits, it turned out to be possible to characterize all planets as basically the same kind of thing, with their differences specifiable in terms of a few quantitative parameters that determined their orbits, given the way that gravity works.

In contrast, all planets have complex surfaces, and the details of their surfaces vary considerably from planet to planet. Characterization of these surfaces, and description of the differences among planets, involves a lot more than a set of numbers. Various theories have been developed over the years to explain why the surface of, say, Mars is what it is. Parts of these theories involve propositions about the physics and chemistry involved, and some of this may be expressed mathematically. But the broad theory that aims to explain the reason for the topography of the surface of Mars, or other planets, is not expressed mathematically, but rather in the form of a narrative. That narrative will tend to refer to the same set of variables and forces as affecting the surfaces of all planets, but the details may differ significantly from planet to planet.

Such studies are not customarily treated as part of physics. Rather, they are much more akin to the phenomena studied and the questions asked by geologists or climate scientists. Or biologists trying to understand macro subjects like evolution and ecology.

Whereas physics can limit the subject matter it addresses so that such heterogeneity is irrelevant to its aims, for other sciences, this diversity or variability is the essence of what they study. Generally some order can be achieved by identifying a limited number of subsets or classes within which the elements are more homogeneous than in the collection as a whole. But in these fields intra-class heterogeneity still tends to be significant, and in many cases the lines between classes is fuzzy. I referred earlier to the concept of “species” in biology as having all of these characteristics.

The issue of significant heterogeneity within a class comes up especially sharply when the questions being asked are concerned with a particular case of a given phenomenon. General scientific knowledge about earthquakes and hurricanes may tell us only a small portion of what we need to know to predict accurately when the next earthquake will hit Berkeley, or whether the next hurricane will hit New York.

The issue of variety within classes and fuzzy class boundaries is especially formidable in the social sciences. The social sciences also have to face the problem that the subject matter they study often changes over time and hence both the entities they study and the basic causal relationships affecting these variables may be different today than they were last year, or a decade ago. Thus economists long have been interested in the relationships between market structure and innovation. However, there are many different kinds of innovation, and a large number of ways in which industry structures differ. Further, over time the nature of the important technologies tends to change, as do the dominant ways firms are organized and the modes of competition. It is not surprising that economists have been unable to find any tight stable “laws” that govern how innovation relates to market structure.

Most emphatically this is not to argue that research on subjects such as innovation and earthquakes cannot come up with general understanding that can be of significant practical value. As noted, evolutionary biology is a very successful science in this respect. Regarding innovation, one important finding is directly related to the heterogeneity and stochastic nature of the subject matter: because of the lack of predictability of which specific innovation paths will work best, a variety of efforts in a field is an almost essential condition for significant progress to be made. In the judgment of at least some economists, this fact provides a much more powerful argument for economic policies that encourage competitive market structures and relatively easy entry into an industry than the static arguments in most economic textbooks. Another important finding is that new firms often play a much more important role in generating significant innovations when a technology is young than when it is more mature. This kind of knowledge is extremely relevant to firms trying to map out an R&D strategy, and to policymakers guiding government decisions on issues ranging from science policy to anti-trust.

What we can expect from science

I have been arguing that sciences that study phenomena that vary significantly from instance to instance, with each instance itself influenced by many factors that also often are quite heterogeneous, are very different from physics. This argument has significant practical implications, because the types of scientific research that focus on understanding such phenomena are particularly common in what Donald Stokes has labeled as “Pasteur’s Quadrant.” Such research is concerned with phenomena that we want to understand better, not simply because we are curious, but also because of our belief that better understanding will help us to deal more effectively with practical problems. The latter objective often imposes a serious constraint on the degree of simplification of the subject matter that scientific research can create through controlled experiments, or assume in theorizing, while still generating understanding that meets the perceived needs that motivate the research. Yet, in science aimed at providing such knowledge, we should not be surprised if the results obtained in one study differ significantly from those obtained in another, even if both appear to be done in similar contexts, in similar ways, and with similar close attention to scientific rigor.

This problem is acutely familiar in the kind of knowledge that has been won by scientific research concerned with deepening our understanding of and ability to predict patterns of global warming. Over the past quarter century research has gained for us a significant increase in our knowledge about historical climate trends and patterns as well as the conditions and forces that seem to be behind these changes.

But the ability to predict many important types of changes (such as future greenhouse gas emissions levels), or to assess the effects of various changes (future rainfall patterns, for example), not to mention the costs—and benefits—of efforts to reduce emission, is limited, and different models are based on somewhat different assumptions, but all basically compatible with what we know scientifically, yield different predictions.

What I want to emphasize here is that whereas the general knowledge about climate change and its causes is strong, specific knowledge about future effects and their timing is not only weak, but inevitably so. But the expectation that climate science should be like physics has fostered the expectation that the research should provide physics-like precision and accuracy. These false expectations lead to an inappropriate attention—by scientists, policymakers, and the interested public alike—to questions of uncertainty that are unlikely ever to be resolved because of the nature of the phenomena being studied.

The same characteristics are obtained in the biomedical sciences. Certainly scientific research has won for us important and reliable knowledge about the causes of many of the ailments that used to devastate humankind, and in many cases this knowledge has served as the basis for the development of effective methods for dealing with those diseases. However, the precision and power of scientific understanding often is relatively limited.

A good part of the reason is that broad disease categories, like cancer or dementia, are very heterogeneous, both regarding the precise nature of the ailment and the causes that generated it. Science struggles with this heterogeneity by trying to divide up the variety into sub-classes that are more homogenous. But the history of such research shows that almost always there continues to be considerable heterogeneity within even the finer disease classifications.

Both because the causes, and also the pathways, of many diseases are multiple, and vary from case to case, scientific understanding of the disease is likely not to be strong enough to point clearly to effective treatment. As a consequence, much of the relatively effective medicine we now have owes its origins not so much to scientific understanding as to trial and error learning of what works. Sometimes this learning occurs through deliberate experimentation, but in many cases, it is almost as a matter of accident. And we have limited understanding of why a number of those treatments work as they do, even if we have strong evidence that they do work.

Also, for many diseases what works for some patients does not work well for others. In some of these cases we have a reasonably good understanding of the patient characteristics and other variables that are associated with effectiveness of particular treatments, and when we do, this can be built into the statistical design for testing different treatments. But in many cases we have little understanding of the characteristics of patients and other factors that cause different responses to a treatment.

Many of these characteristics hold even more strongly in research aimed to improve the effectiveness of educational practice. Practices that perform well in a particular controlled setting (e.g. a laboratory school) very often do not work well when they are tried out in another setting. It also is clear that different children learn in different ways, and different teachers are good at different modes of teaching. Despite this variety, there has developed over the years a body of “common sense” understanding of generally good and generally bad teaching practice. Much of this is the result of professional experience. Some has been won, or at least brought into brighter light, through research. A good example is the relatively recent comprehension that what children have learned in their very early years has a strong and lasting effect on what they learn in school. But here, too, the enhanced understanding is the result of careful examination of experience rather than knowledge deduced from deeper causes.

Research in child development psychology did, indeed, provide a basis for suspecting the importance of early childhood learning. On the other hand, virtually the only reference to research results in brain science that one finds in the education literature is evidence that the physical brains of children develop very rapidly at an early age. Although it long has been hoped that growing scientific knowledge in fields that would seem to be foundational to understanding of how children learn would contribute greatly to our ability to identify better teaching practice, there would appear to be few cases where it has.

In recent years the cutting edge of the design of empirical research on the efficacy of educational practices has been to assign students randomly to the practice being studied, and to compare how they do with the performance of a control group. This research strategy provides a way of assessing whether a generally broadly defined way of doing something is on average efficacious in comparison with another practice or treatment or arrangement. However, when applied to practice in education there almost always are differences in exactly what a nominal practice is between schools in a school system, or even within schools between classrooms. And almost always, students vary in their responses to different practices. Further, there are good reasons to doubt that another empirical study done in ways that are as similar as possible would yield results just like the first study.

This is not to argue that random assignment testing is useless as a tool for helping us to improve educational practice. In some cases, scientific testing may show large and quite general differences in the efficacy of particular methods of teaching or modes of organizing schools that, although noticed by some, have not been widely recognized and accepted. In other cases, evidence that a particular technique seems consistently to benefit a certain class of students, if not all students, can be helpful in inducing more effective tailoring of teaching.

Beyond physics envy

When studying phenomena that tend to lie with Pasteur’s Quadrant, it is a mistake to think one can get the precision or generality of knowledge that one expects from physics or chemistry. The kinds of numbers one can estimate and work with in many fields tend to be at best approximate and incomplete indicators of what we would like to know about, rather than precise measures. As a consequence, almost always they can be understood only in a richer context of description and narrative. In research on these kinds of subjects and questions, qualitative description and explanation should not be regarded as an inferior form of scientific understanding with the aim of research to replace them with numbers, but rather as a vital aspect of our understanding that numbers can complement but not replace. A set of numbers without such a qualitative context—the result of research that one might call naked econometrics—is likely to be worthless as a guide to policy, or worse.

A good case in point is the long-standing objective of policymakers and scholars to measure a “rate of return” on public R&D spending in a field of activity or a government program. Any such numbers that are calculated are bound to be highly sensitive to the very particular and somewhat arbitrary assumptions that enabled them to be generated, and the particularities of the context for which they were estimated. I would argue that, taken alone, they can tell policymakers nothing of value. On the other hand, if those that generate those numbers, and those who interpret them, know a good deal about the particular programs and activities involved, and have a good feel for just what kind of knowledge or capability the research generated, and the numbers were generated in the light of that understanding, then those numbers may sensibly be interpreted as providing an indicator of what the research accomplished.

An important consequence of my argument is that productive advance in practice in many of the arenas that sciences in Pasteur’s Quadrant aim to facilitate requires a significant interaction between learning through research by scientists and learning by doing on the part of those involved in policymaking and implementation. The research enterprise needs not only to light the way to better practice, but to try to understand at a deeper level what has been learned in practice. I note that this is a well-recognized characteristic of effective fields of engineering research and biomedical research. It is a less-well-recognized need in the social and behavioral sciences, but there have been important moves to establish better two-way interaction in fields like education. And I would argue that this very much needs to be done regarding studies that evaluate research programs.

Research programs that are justified in terms of their potential contributions to solving practical problems should be designed with clear awareness of the strengths and weakness of the sciences involved—and scientists and policymakers alike should temper their expectations accordingly. High-level insights of considerable power, such as our knowledge about the importance of early childhood education or the human influence on climate, can provide valuable general guidance for our policies. But expecting science to achieve physics-like, quantified precision that can allow us to optimize policies in domains as diverse as cancer treatment, industrial innovation, K-12 education, and environmental protection is a fantasy. Here we will need to focus on improving our processes of democratic decision making.

Richard R. Nelson is director of the Center for Science, Technology, and Global Development at the Columbia Earth Institute, and Professor Emeritus of International and Public Affairs, Business, and Law at Columbia University.

From the Hill – Spring 2015

“From the Hill” is adapted from the newsletter Science and Technology in Congress, ­published by the Office of Government Relations of the American Association for the Advancement of Science (www.aaas.org) in Washington, DC.

2016 budget proposal

President Barack Obama’s proposed Fiscal Year (FY) 2016 research and development (R&D) budget, released on February 2, calls for $146 billion in total federal R&D funding.

Click to see a larger version of the chart

The president’s overall FY 2016 budget requests that Congress increase discretionary spending—the portion of the budget that does not go to mandatory entitlement programs—by seven percent over the forced spending caps known as sequestration. If approved by Congress, federal R&D funding would increase to its highest level since 2012.

The $146 billion figure represents an $8 billion or six percent increase from 2015 enacted levels, though it does not take into account inflation, which is expected to increase 1.6 percent from FY 2015 to FY 2016, said John Holdren, director of the White House Office of Science & Technology Policy (OSTP). The total R&D budget request allocates $68.8 billion for non-defense-related R&D and $76.9 billion for defense R&D. Most agencies that carry out R&D would receive some level of increase over their FY 2015 budgets.

“Overall, the budget is definitely more ambitious than we saw last year,” said Matt Hourihan, director of the American Association for the Advancement of Science R&D Budget and Policy Program. “It’s particularly ambitious in certain priority areas where we’ve seen big increases requested in previous budgets as well, such as low-carbon energy technology, infrastructure R&D, and advanced manufacturing.”

Several cross-agency initiatives would receive substantial funding, reflecting key areas of interest for the White House, said Holdren. The FY 2016 budget provides $2.4 billion, spread across several agencies, to support innovation in advanced manufacturing. The budget also includes $215 million for the National Institutes of Health (NIH), the Food and Drug Administration, and the Office of the National Coordinator for Health Information Technology, to launch a Precision Medicine Initiative on personalized medicine. It also provides $1.2 billion to NIH and other agencies to implement the National Strategy to Combat Antibiotic Resistance. The 13-agency U.S. Global Change Research Program would receive approximately $2.7 billion to help carry out the president’s Climate Action Plan.

The budget includes several other allocations related to implementing the Climate Action Plan, reflecting the fact that President Obama is “absolutely committed to continuing the administration’s leadership on addressing climate change,” said Holdren. These include the effort to expand the nation’s “Climate Resilience Toolkit,” as well as research on ocean acidification and the role of natural resources as carbon sources.

Funding for basic research would surpass FY 2015 levels, Holdren said. The National Science Foundation (NSF), Department of Energy’s (DOE) Office of Science, and the National Institute of Standards and Technology (NIST) within the Department of Commerce, together would receive a total of $13.8 billion, an increase of $0.7 billion over FY 2015. NIST would fare particularly well, according to ScienceInsider; its budget would increase 29 percent, primarily to support research on advanced manufacturing. NSF and DOE each would see an increase of roughly 5 percent. The areas within these agencies that would receive the biggest increases are education and human resources at NSF, which would increase by 11 percent, and the advanced computing program at DOE, which would receive a boost of nearly 15 percent.

The United States Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA) are some of the biggest winners, ScienceInsider reported. USGS would receive $1.2 billion, an increase of 13.7 percent, and NOAA would receive $3.33 billion, an increase of 6.3 percent.

NIH would receive $31.3 billion, representing an increase of 3.3 percent from FY 2015. In addition to antibiotic resistance and personalized medicine, other key areas of focus include the BRAIN initiative, cancer, and Alzheimer’s research.

NASA’s proposed budget increase is also relatively modest, with a 2.7 percent bump up to $18.5 billion. Missions to fly past Europa and to land on an asteroid are among the top priorities, according to ScienceInsider. At the briefing, Holdren also highlighted some other goals, including the development of a “vibrant, American commercial space industry and to regain the capability to send an astronaut into space cost-effectively and safely from American soil by the end of 2017.” He also noted that the budget includes $1.9 billion for Earth science.

In summarizing the president’s proposal, Holdren said: “The budget also reflects the reality that we continue to have to govern in an era of very tough choices. Not everything that is desirable is affordable.”

However, the FY 2016 budget, which will now be evaluated by Congress, “ends the harmful spending cuts known as sequestration while achieving spending cuts through more sensible and less disruptive means,” said Holdren. “And, also like this president’s past budgets, this one treats science, technology, and STEM education well.”

Hill addendum

New report from education task force

The Task Force on Federal Regulation of Higher Education, appointed by a bipartisan group of senators from the Senate Education Committee, has released its report, Recalibrating Regulation of Colleges and Universities. The report reviews the federal regulations and reporting requirements on colleges and universities, identifies specific regulations of highest concern, examines the processes for the development and implementation of regulations, and makes recommendations for ways to ensure that the regulatory process is easier to understand and easier to comply with.

New Rules for Spouses of H-1B Visa Holders

Last week, the government announced that spouses of H-1B visa holders will now be able to apply for work permits. The hope is that the change will incentivize highly skilled workers and their families to stay in the United States. The new rules take effect on May 26.

UMR/ITIF report examines NIH funding

United for Medical Research has teamed with the Information Technology and Innovation Foundation on a new report entitled Healthy Funding: Ensuring a Predictable and Growing Budget for the National Institutes of Health. The report examines the implications of reduced federal commitment to NIH-funded research as well as options for altering the budget process to enable continued government investment in biomedical R&D.

Ranking Democrat’s Letters to 7 Academic Institutions Draws Ire

Rep. Raul Grijalva (D-AZ), ranking member of the House Natural Resources Committee, sent letters to seven academic institutions requesting information regarding the funding sources, testimony, and related communications of specific academics who have testified before Congress on climate change.

His request was in response to revelations that Dr. Wei-Hock Soon, a scientist at the Harvard-Smithsonian Center for Astrophysics, had not fully disclosed all of his funding from industry that supported his research. The congressional request has prompted a strong reaction from a number of scientific organizations that have expressed concerns regarding academic freedom. Rep. Grijalva has since acknowledged that his request for communications was probably an “overreach.”

FCC Adopts Open Internet Rules

On February 26, the Federal Communications Commission (FCC) passed Open Internet Rules, establishing that internet service providers (ISPs) cannot “unreasonably interfere with or unreasonably disadvantage the ability of consumers to select, access, and use the lawful content, applications, services, or devices of their choosing.” The rules specifically forbid ISPs from blocking legal content, throttling internet traffic, and using paid prioritization.

Significantly, the order reclassifies broadband Internet access as a telecommunications service under Title II of the Communications Act, thus giving the FCC more regulatory authority over broadband services. The FCC’s previous Open Internet Rules were struck down in January 2014 by the DC Court of Appeals, and the court’s opinion indicated that reclassification would be a potential way to regulate broadband in the future.

Informing Public Policy with Social and Behavioral Science

Many of the challenges facing our society today—from military preparedness to climate change—have a social or behavioral dimension, as do the policies considered by government officials to address them. A better understanding of the factors that influence how people act and interact can help policymakers design more effective procedures.

The vast majority of policymakers are not trained as scientists. As a result, they have varying degrees of understanding about how the social and behavioral sciences can help them do their jobs. Likewise, the vast majority of researchers have little to no policymaking experience. As a result, researchers often approach policymakers in ways that policymakers find unhelpful.

As social scientist Robert Cialdini observed at a gathering of researchers and policymakers on Capitol Hill a little over a year ago, if the social sciences were a corporation, they would be renowned for research and development. But they lack a crucial element: a shipping department. Social and behavioral scientists do not have a distribution system to deliver what they know to decisionmakers, packaged in a form that they can use. As a result, a wealth of potentially useful information that could yield practical benefits for the public never realizes that potential.

I propose that the social and behavioral sciences move quickly to develop an efficient and effective “shipping department”—a mechanism for delivering the most useful findings and methods into the hands of public policymakers. Having been both an active researcher and a member of Congress, I have seen how the absence of a concerted effort to effectively communicate social science has limited its impact in critical policy contexts. The social and behavioral sciences can increase their social value by working to translate and transfer their insights to real-world policymakers in ways that stay true to the content of the scientific research, while responding to and reflecting the policymakers’ actual informational needs. In other words, to help policymakers better understand science, it is critical that social scientists better understand the kinds of information that policymakers do and do not need.

To that end, I suggest five actions that can help the social and behavioral sciences make a more positive impact on policy and our society. Although any one of these actions taken independently could increase the relevance and public value of the social and behavioral sciences, each endeavor will have greater value if all are pursued together. Let us consider each of the proposals in turn.

Use a collaborative, consensus process to identify robust scientific methods and findings that are of potential interest to policymakers. The social and behavioral sciences should join together to create a high-level, cross-disciplinary project involving leading experts in communication and learning along with actual policymakers. The goal would be to produce practical, empirically driven, and readily applicable presentations that are accessible and usable for policymakers at different levels of government.

This would, emphatically, not be a typical academic work. Rather, it would be practical and translational in purpose, and it would be guided by an awareness of real-world policy needs and how our methods and findings can help impact that policy. Just as important, it would derive communicative content and presentational strategies from the substantial knowledge base on these topics that the social and behavioral scientists have taken the lead in producing.

From the research side, the consensus process would be guided by the following questions: What do we believe are the most significant principles of how social and behavioral scientists approach questions relevant to public policy? Which of our theoretical insights and robust empirical discoveries are most relevant from a policymaker’s point of view? At the same time, we would ask policymakers to articulate the insights that they most want from the social sciences. In other words, what are the situations in which they would most value the knowledge that social and behavioral sciences produce? Are there situations in which social and behavioral science methods and findings can help policymakers avoid ineffective or counterproductive policies and programs while crafting more effective ones?

An example of the type of outcome that this process could produce pertains to “regression to the mean”—i.e., the long-known tendency in social science research for scores at the extreme high or low ends of a distribution to “regress” toward the mean on subsequent measurement owing to chance factors alone. Researchers are aware of the potential illusory effects of regression to the mean. Policymakers, however, often want to help those at the most extreme ends of the curve, such as students in the very lowest performing schools. As a result, laws may be enacted and programs created whose apparent effectiveness is an illusion. For example, a school where students test at an extremely low level one year is likely to perform at a less-dire level the following year, regardless of any policy intervention, because of the tendency to move toward the mean. This could happen for a variety of reasons unrelated to the new program—for example, if several particularly difficult students leave the school or some high-performing students join. Those unrelated changes, however, could produce higher average scores for the school, leading the policymaker to see an apparent improvement and attribute that improvement to the intervention. Researchers know that there are methodological design and statistical analytic techniques to guard against this error, but again, policymakers are not only unaware of the problem of regression itself, they are also likely to have very little knowledge of research design or statistical techniques.

Helping decisionmakers who care greatly about problems and the people affected by them to craft policies that are not prone to this and other comparable errors could help direct more resources to policies that have real effects and avoid policies with spurious or even harmful impacts.

As a second and related example, it might be very useful to provide policymakers with practical tools to understand how the findings of randomized, controlled trials can or cannot be appropriately transferred from one setting or application to another. In general, a collaborative effort among researchers and policymakers to first identify, and then more effectively communicate, methods and ideas for greater policy effectiveness and efficiency is one route to increasing the public value of social and behavioral science knowledge that already exists.

Develop a comprehensive and outcome-oriented entity to create more effective communication strategies. This entity would not just produce content, but also commit to evaluating and making public the relative effectiveness of different science communication strategies. When we discover social and behavioral science knowledge that has the potential to benefit the public, the realization of that potential will depend on the effectiveness with which the information is conveyed. We should develop a means of producing and disseminating such information that makes use of many modes of communication. These modes can include printed products, electronic publication and distribution, and, possibly, a new online journal directed to an audience of both policymakers and social and behavioral scientists. We should also consider developing practical handbooks or, perhaps better yet, massive open online courses (MOOCs) to communicate with the widest possible audience. Another possibility would be developing apps that employ decision trees, algorithms, or augmented analysis and decisionmaking to help policymakers use what the panel develops. In all such cases, we should commit not just to developing content, but also to evaluating the extent to which our target audiences find it valuable. If this entity is linked to the researcher-policymaker collaboration described above, that group could advise it on how best to evaluate the impact of its activities.

This entity’s main target audiences would be policymakers, those who support policymakers, and those who seek to aid policy processes. If sufficiently effective and accessible, these resources could also be used as part of graduate training in the social and behavioral sciences—providing templates for researchers and organizations that want to deliver valuable advice to policy communities. This resource, if sufficiently effective, should also be incorporated into the orientation and other services provided to members and staff on the Hill and in other legislative and policy bodies. The key is to develop content that this population believes is necessary for them to achieve their ambitions. Another, much broader aspirational goal would be to make this information available to the general public as they seek to understand social problems and policies.

Create an independent, non-governmental resource to which policymakers can turn to have more personal and ongoing interactions. Policymakers can use this resource to obtain credible and objective information about existing or proposed programs and legislation. In contrast to the model used in the United Kingdom, where the government has a central office of behavior, we should consider an alternative approach: establishing an independent, external resource—like the Congressional Research Service or the Congressional Budget Office—to provide an expert, nonpartisan sounding board to which policymakers could turn for feedback about the likely social and behavioral consequences of current and proposed policies.

This is a subtle but important distinction from how things work currently. The proposed resource would not replace existing entities such as the National Research Council or other organizations that offer analysis of social challenges and policy options. Rather, we can augment and amplify the effects of such analyses by creating a way for policymakers to routinely gain assistance in thinking things through as a regular part of their own policy development processes.

As this entity responds to requests from legislative or administration policymakers, specific policy examples might be offered and specific findings of research would be presented, but the purpose of doing so would be to demonstrate how certain actions and consequences are related. This resource would not advocate for a specific policy for a specific problem.

Suppose, for example, that a policymaker is concerned about the consequences and costs of elevated high school drop-out rates. This resource would provide a venue for policymakers to learn about how social scientists have examined the issue, what attributes of the problem are most and least likely to be affected by various policy alternatives, and what mistakes or successes researchers have documented. If the resource could provide this type of information to policymakers in an accessible and actionable way, it could help them make more effective decisions.

Our purpose in this endeavor would be to transform how individual policymakers and their staffs understand and use directly relevant scientific methods, findings, and concepts in their thinking and actions. To make this project work, however, it is essential that we focus not just on how to educate policymakers about science but also to help social and behavioral science researchers better understand the situations that policymakers regularly face. This resource will be of value to policymakers only if researchers understand enough about policymakers’ needs to provide the kinds of information that policymakers can use.

Establish a series of presentations that are readily accessible to policymakers and staff on Capitol Hill and elsewhere in government. As the consensus panel does its work and identifies the key challenges and relevant insights and findings, we also need to take our findings and methods to where the audience is and show them what we know, how we know, and why it matters. The previously proposed journal, MOOCs, apps, and other mechanisms would all contribute to this, but we should also begin to have events on the Hill at convenient times, with food and other incentives to attract interested staff.

When I chaired the Energy and Environment Subcommittee of the House Science and Technology Committee, we initiated a series of what I called “Gee Whiz” presentations on the Hill. These were intended simply to highlight for staff and members of Congress the most interesting and exciting findings from Department of Energy scientists. The events were a huge success and drew increasingly large and very interested audiences.

There is no reason the social and behavioral sciences could not do the same. For these to be successful, what is presented at such events must be offered by compelling speakers—not merely people with impressive academic or research credentials—but strong, engaging communicators. These events must also address topics beyond esoteric subjects or psychological parlor tricks, and the presentations must not be laden with the usual “on the one hand, on the other hand, more research is needed, etc.” unless it is relevant, interesting, and meaningfully illuminates the topic. Topics and speakers must be tightly and strategically chosen and the information must be practical, have substantial magnitude of effect, and must speak to people on both sides of the aisle. And again, it must incorporate what we know about cognition, emotion, and behavior change.

For example, in the fall of 2013, the National Research Council organized an event in the U.S. Capitol that featured public benefits of social science. However, the event was not billed as such. Instead, we framed the proceeding as “How Social Science Saves the Government Money.” The event was framed this way to reflect the needs of the target audience—in this case, staff who could gain a type of knowledge that members of Congress could then use to benefit their constituents. The event featured leading scholars from several disciplines and former members of Congress from both major political parties. The presenters delivered sharp and cogent examples of how the social sciences transformed the provision of health services, enhanced the effectiveness of military strategies, and increased the efficiency of environmental programs. Instead of engaging an audience of congressional staffers in abstract conversations about science, the presenters highlighted how science could help them do their jobs more effectively. If done right, these presentations should become the kinds of events that members and key staff look forward to and make a point of attending because they value the intellectual stimulation and the practical policy implications.

Develop and implement a parallel media communications plan, based on social science research, to enhance public awareness of social science methods, findings, and impacts. In other words, social and behavioral scientists need to use what we know to communicate how we know and why it matters. If a behavioral and social science method or finding does or could change the world for the better, but no one who makes policy knows that, why would policymakers support the science that produced it to begin with?

In response to a general lack of awareness among policymakers of the many potential and actual contributions of the behavioral and social sciences and a devaluing of social science research, an independent funding source should develop a communications campaign directed toward increasing awareness, understanding, and support for the social and behavioral sciences. This campaign would incorporate principles and findings of the behavioral and social sciences to maximize effectiveness. The initial focus would be on policymakers inside the Washington Beltway, but consideration would be given to a broader public market so that average citizens will be better informed about the social and behavioral sciences and their value.

As one example of how such a campaign might be developed using behavioral science principles, the “Trans-theoretical” or “Stages of Change” model suggests that there may be merit to an initial messaging strategy designed to move people who may be at the pre-contemplation level to contemplation of the methods and benefits of the social and behavioral sciences. Based on this model, several striking examples of proven applications could be highlighted, with the initial focus not on the specific findings, but on the methodologies and disciplines that produced them.

For instance, a media campaign might use the following: “What is the best treatment for PTSD and how effective is it? How do we know?”

Another message, perhaps at one of the Metro stations leading to National Airport, might include an image of the 1982 jet crash in the Potomac with a caption: “This tragedy has not been repeated, and your air travel is much safer today because of fundamental research. What changed?”

As a third example, “With no change to the tax code and no new government expenditures or mandates, millions of Americans are saving billions of dollars more in their retirement accounts. Who figured out how to do that?”

Ideally, these or other messages should be tested empirically and compared with other messages and media. If they are shown to be effective, they would be deployed strategically through media and locations identified by research and with expertise and evidence from communications firms.

As part of a comprehensive strategy, these messages could be used to drive interest to further information, or they might be used as part of a series in which the first messages move from pre-contemplation to contemplation, with subsequent messages moving through other stages of change toward the desired end of greater awareness and support for social science research. The goal would be to craft messages that reach out to different audiences in different ways so that each can, in its own way, recognize that the social and behavioral sciences can help contribute to better outcomes, financial savings, and more effective and efficient policy.

Our disciplines have established a body of methods, findings, and knowledge that is directly applicable to a host of public policy areas. The task before us now is to turn that “applicable” into “applied” in ways that benefit our society and demonstrate the value of our disciplines to policymakers. Whereas this article has suggested several ways to go about that endeavor, there are undoubtedly many other possibilities. What matters most is that we consider a number of options and then put in place a strategic plan to implement the initiatives that seem most promising.

Clean Energy Diplomacy from Bush to Obama

The Bush administration didn’t get everything wrong about climate change, and the Obama administration isn’t getting everything right. A truly effective climate policy would include the best elements of each approach.

Among those concerned about climate change, a common perception is that the steps taken to reduce greenhouse gas (GHG) emissions under the administration of President George W. Bush were mere fig-leafs for a policy of inaction, whereas those taken under the administration of President Barack Obama have been robust and limited only by the unwillingness of Congress to support more substantive policies. A closer, inside look at the actions taken by both administrations reveals a more complex and nuanced story.

Indeed, far from being a simple “Bush bad on climate/Obama good on climate” story, an examination of each administration’s approach can point the way to a hybrid model that may better bridge the current political divide on climate action and effectively address this critical global concern. Although there are examples to support my arguments in both the domestic and international policy spheres, I will focus mainly on energy-related international cooperative activities to address climate change, drawing on my first-hand experience managing international programs in the U.S. Department of Energy (DOE).

Not surprisingly, each administration’s efforts to mitigate climate change were greatly influenced by their parties’ ideological preferences regarding the roles of the private sector and government regulation. More subtle, however, is the way in which those ideologies influence the choice of technology pathways, with the Bush administration focused on investments to improve existing technologies, versus the Obama administration’s inclination to also invest in new technologies that could have an impact on existing market structures and technological preferences. Less obvious, and perhaps counterintuitive to outside observers, are differences in the way that the White House has managed government climate efforts, with the Bush administration embracing more explicit interagency cooperation and the Obama administration preferring centralized White House control. In the international context, these ideological manifestations also played out in contrasting degrees of willingness to pursue policy goals through the multilateral engagement mechanism of the United Nations Framework Convention on Climate Change (UNFCCC), with President Bush a reluctant player at best, and President Obama a more enthusiastic partner. Yet both administrations developed means to make progress on climate outside that forum.

I make these arguments from the perspective of a 10-year civil servant engaged in staff and leadership roles in the climate efforts of both administrations. At DOE, I was executive director of the Secretariat of the International Partnership for the Hydrogen Economy (IPHE), co-chair of the Renewables and Distributed Generation Task Force of the Asia-Pacific Partnership (APP), a Senior Policy Analyst in the Climate Change Technology Program (CCTP), and director of the office leading many Clean Energy Ministerial (CEM) initiatives as well as running its Secretariat. I had previously worked in the technology sector, managing research and development (R&D) agreements between Intel Corporation and other integrated circuit manufacturers and suppliers developing new technologies. I take the climate threat extremely seriously, agree with the consensus views of climate scientists, and believe efforts to mitigate, as well as adapt to, climate change should be a priority of the government. I have had the immense pleasure of working with hundreds of other government professionals who also take this threat seriously and want to do their utmost to address it, but who must, in order to do their jobs, adjust their efforts to serve the elected administration, and thus its policy goals and their underlying ideological foundations. Though this non-political role for civil servants has to be accepted as a necessary responsibility within the structure of the government, I would nonetheless argue that a greater effort to evaluate existing programs and maintain continuity of effort between administrations could make for more effective government action and therefore greater benefit for citizens—and for whichever party is in the White House.

Ideologies of technological change

The recent history of U.S. government actions to address global climate change through large-scale reduction of GHG emissions from energy production and use reflects two distinct and contrasting perspectives. One is based on the view that existing low-carbon technologies favored by the traditional environmental community, such as wind and solar power, are insufficient for large-scale emissions reductions, and that new or greatly improved ones must be developed through increased public funding for energy-related R&D. This view goes hand-in-hand with a focus on centralized large-scale energy production, such as carbon capture and storage or new generations of civilian nuclear power. It envisions R&D partnerships with existing market players and seeks a seamless introduction of improved or new technologies into current market structures with minimal regulatory intervention. In its focus on minimizing disruption of existing economic and technological arrangements, it is an approach commonly viewed as “conservative” in the traditional sense of the word, though there are certainly those who believe in this approach who would not otherwise portray themselves as conservatives.

The other approach holds that existing low-carbon technologies are largely sufficient to drive down emissions and that what is needed are policies to incentivize their commercialization, whether through targets, subsidies, or carbon pricing. This perspective tends to be linked to a focus on regulations and decentralized distributed energy production from renewable sources, with corresponding changes in market structures to ensure their successful integration into the energy system. Energy R&D is still valued, though with a greater emphasis on renewables and the potential to uncover new disruptive technologies or enable new market paradigms. This view can be characterized as a philosophically “liberal” one, but again, the distinction I am making, although important for telling my story, is not a rigid one. Indeed, in my own experience as a professional policy staffer, I have known thoughtful proponents of diverse technology R&D portfolios and technology-neutral regulatory frameworks who would not identify with either political ideology. As I will explain, however, such policy-agnostic approaches often fall victim to the more doctrinaire and conventionally “conservative” or “liberal” policy preferences of the party in power.

These ideological differences are linked to competing theories of technological change. One theory holds that direct government support for R&D results in cost-competitive products that will succeed in the marketplace without regulatory help; the other, that regulations are necessary to drive product improvements and cost reductions through “learning by doing” in the absence of a strong market signal. This is a legitimate intellectual debate, with proponents of the former approach pointing to the government-sponsored R&D that led to developments such as the internet and advanced integrated circuits, and proponents of the latter approach pointing to cost-effective regulations, such as those aimed at reducing emissions of sulfur dioxide and chlorofluorocarbons. Differing assumptions about the relative importance of these approaches are even incorporated into models that are used to provide insights about future energy systems and help inform policy choices.

Although these contrasting ideological and intellectual views of technological change may seem important only in the context of domestic policy and politics, they also have a profound impact on U.S. engagement in international climate change mitigation activities. The approach taken by the UNFCCC to date falls very much on one end of the spectrum, with the regulatory nature of the Kyoto Protocol and the lack of a meaningful private sector role in the negotiations. It is, therefore, not surprising that the Bush administration was hostile to that approach. What many people are less aware of, however, is the new avenues of engagement that were developed and pursued under President Bush and then continued under President Obama.

The Bush approach

In 2001, DOE launched an international partnership for the development of next-generation nuclear reactors, the Gen IV International Forum (GIF), followed in 2003 by two additional international partnerships, the Carbon Sequestration Leadership Forum (CSLF) and the International Partnership for the Hydrogen Economy (IPHE). The formation of these partnerships mirrored domestic R&D investments. Nuclear fission R&D ramped up to $123 million in 2003, after being virtually zeroed out in 1998 under the Clinton administration; the budget for coal R&D increased almost three-fold, from $121 million in 2000 to $339 million in 2003, and for hydrogen R&D almost four-fold, from $24 million to $92 million over the same period.

The charter or terms of reference for these three partnerships read fairly similarly, focusing on international cooperation to accelerate the research, development, demonstration, and commercial deployment of nuclear, carbon-capture, and hydrogen technologies. GIF started with nine major-economy signatories, CSLF with a dozen (11 major economies and the European Commission), and IPHE started with a similar mix of 15 members.

The significance of these partnerships lay not in the fact that they created new international technology cooperation agreements. The International Energy Agency (IEA) had been doing this for many years, sponsoring more than 40 multilateral technology initiatives, known as “implementing agreements,” on various energy topics. Rather, they were significant because these three technologies were chosen for elevation to a political level, creating the basis for a new technology-centric approach to addressing global climate change.

Against the backdrop of the Bush administration’s lack of support for comprehensive climate legislation and refusal to agree to mandatory emission reduction targets under the UNFCCC, can these partnerships really be seen as sincere efforts to implement a climate change strategy? Critics point to the long-term nature of these investments as a delaying tactic, as well as to the fact that carbon capture and sequestration (CCS) preserves the use of coal in the energy system. One can reasonably argue that the threat of climate change was not taken seriously enough in the Bush administration, but it is important to acknowledge that such criticism is often based as much on technological (and ideological) preference as on analysis of the Bush administration’s motives. Widespread adoption of nuclear power and CCS are conceivable (and many would argue essential) means of achieving deep cuts in carbon emissions in coming decades, especially given the widespread global use of coal and the role of CCS as the only potentially available means for dramatically reducing the carbon emissions associated with its use.

Moreover, R&D in these three technology areas, which continued to grow substantially under the Bush administration, has continued at comparable levels in the Obama administration. Likewise, the three international partnerships established more than 10 years ago continue to operate. Support for R&D on these technologies runs counter to the supposedly “liberal” approach of the Obama administration, a point to which I will return later.

Private sector partnerships

An important aspect of the Bush administration’s approach to climate policy was its desire to incentivize direct involvement by the private sector. On the R&D front, this took place through cost-sharing agreements. The cost share was necessary in this framework because, absent a policy incentive, the private sector would not invest in innovation unless the financial risk associated with potential failure was reduced. Indeed, the vast majority of DOE-applied R&D funding is obligated on a cost-share basis with commercial entities. However, the private sector was not just envisioned as a recipient of R&D dollars; commercial entities were also to be supported by government action to disseminate their technologies.

There is nothing unusual or ideologically distinctive in this strategy from a trade or export-promotion perspective: Bipartisan majorities have long supported the work of entities such as the Foreign Commercial Service (to assist U.S. businesses overseas), the Export-Import Bank (to facilitate the export of U.S. goods and services), and the Overseas Private Investment Corporation (to support the expansion of U.S. businesses into global markets). However, the Bush administration took a further market-oriented step when it created the Methane-to-Markets Partnership (M2M) and its associated Project Network in November 2004.

Led by the Environmental Protection Agency (EPA), though funded largely by the Department of State, the goal of the M2M is to “reduce methane emissions and to advance the recovery and use of methane as a valuable clean energy source [and to] focus on the development of strategies and markets for the abatement, recovery, and use of methane….” Fourteen countries signed onto the partnership at the start, as well as more than 100 participants in the Project Network, described on its web site as a “community of private-sector entities, financial institutions, and other governmental and non-governmental organizations with an interest in methane abatement, recovery, and use projects.” Project Network members are “actively involved in the Partnership,” are “critical to its success,” and “can galvanize action, setting the stage for concrete methane projects.”

Renamed the Global Methane Initiative under the Obama administration, M2M now consists of 43 government members and more than 1300 Project Network participants. The eager engagement of many companies in M2M from the start provides evidence of the private sector’s appetite to partner with the federal government in international activities to address climate change, as long as the government convenes and supports the effort with sufficient funding and political will. It provides further evidence for a somewhat strategic, “conservative” approach to climate change mitigation, though the cost-effectiveness of methane capture made the business case more of a ”win-win” approach than other mitigation strategies. M2M also set the stage for a unique new partnership that combined international cooperation among major economies with engagement by the private sector, the key elements of the Bush administration approach.

The Asia-Pacific Partnership

In January 2006, ministers from Australia, China, India, Japan, Korea, and the United States met in Sydney to launch the Asia-Pacific Partnership on Clean Development and Climate (APP), which “explores a new approach for harnessing the power of our private sectors, our research communities and our government sectors to drive sustainable development.” The APP focused on specific energy-intensive sectors and used “a ground-breaking new model of public-private task forces to address climate change, energy security, and air pollution.” It established these public-private task forces in eight areas: cleaner fossil energy; renewable energy and distributed generation; power generation and transmission; steel; aluminum; cement; coal mining; and buildings and appliances.

To those familiar with the Bush administration initiatives that preceded it, the APP was a natural extension of its approach, but it had greater visibility and was more controversial from the start. For one, it was led by the State Department office with responsibility for U.S. participation in the climate negotiations under the UNFCCC. The leadership level from the other governments was similarly constituted. This led to the perception that the APP was established as an alternative to the Kyoto Protocol and an explicit rejection of the UN’s inclusive multilateralism, in which all countries participate in the negotiations, even if they don’t have to make commitments. This fear was exacerbated by a confluence of factors involving the APP participants: the United States and China, the world’s largest emitters; India, along with China, the world’s fastest growing emitters; the United States, the only Annex 1 country not to have ratified the Kyoto Protocol; Australia, the first to have ratified and then explicitly backed away from its targets; and Japan and Korea, technology-driven export economies with strong business interests in the region. The concern was evident enough among the participants that they felt it necessary to explicitly address it in the Sydney Ministerial communique: “The Partnership will be consistent with and contribute to Partners’ efforts under the UNFCCC and will complement, but not replace, the Kyoto Protocol.”

Another factor making the APP more visible and controversial was the direct involvement of the White House and the business community. White House Council on Environmental Quality Chair James Connaughton championed the APP and met regularly with business leaders to encourage their involvement. That involvement was not simply to enable them to share their views; the APP was explicitly structured to ensure direct private sector participation. If a company engaged in an APP task force, it earned a seat at the table. For those who have never participated in international government meetings, it is hard to describe how big a change this was. The discussions that ensued in task force meetings were refreshingly undiplomatic at times, allowing for direct engagement on issues such as intellectual property protection that would have been difficult to imagine in a government-only context. Having the private sector at the table also made the prospect of large-scale investment much more tangible, since governments are rarely able to offer financial support for projects at the scale required for substantive impact on GHG emissions.

Nonetheless, APP critics voiced fear of undue business influence on government decision making. The BBC environmental correspondent Richard Black summed up the situation quite well at the time:

“To insiders, the Asia-Pacific Partnership on Clean Development and Climate is a real world, mature-person’s solution to climate change. No economic pain, no mandatory targets, no international commitments and no need for open, accountable negotiations. No place for the fetid unwashed of the environmental movement; keep it in the family of power-suited industrial and political brokers, the few who can really get things done. The electronic juice will keep flowing, the giant developing economies of Asia will keep growing, and no government will have to do anything it doesn’t want to do.

“To other observers, it’s an empty vessel; a fig-leaf to cover the embarrassment of George Bush and John Howard, the only western leaders to have reneged on commitments their predecessors made at the UN Kyoto conference in 1997. In this thesis, the Partnership will deliver nothing of benefit to the climate, because technology alone cannot bring the huge reductions in greenhouse gas emissions which, according to consensus climate science, are needed.”

Yet the international partners were fully engaged and the various task forces began meeting to draft work plans and identify projects, which, in turn, had to be approved by a Policy and Implementation Committee (PIC) made up of government representatives. The PIC met nine times from April 2006 to April 2011, approving work plans and more than 150 projects across the task forces. A second ministerial meeting was held in New Delhi in October 2007, at which Canada officially joined the partnership.

Unlike the R&D-focused or market-oriented partnerships from earlier in the Bush administration, the APP covered the spectrum from adoption of existing technologies to the development of new ones. For example, the power generation task force included a focus on improving the efficiency of power production in existing coal-fired plants, and the cleaner fossil energy task force focused on development and demonstration of CCS technologies. The APP also added agencies other than the usual State Department, DOE, and EPA to the mix by including the Department of Commerce (to help manage the private sector relationships) and the Department of the Interior (to participate in the coal mining task force).

Following the launch of the APP, the State Department, DOE, EPA, and Commerce requested funds to support their work in both the FY2007 and FY2008 budget appropriations. Though complicated by all-too-familiar House and Senate committee differences, continuing resolutions, and consolidated appropriations bills, the State Department was ultimately able to obtain total funding of $35 million. However, DOE was unable to surmount these political difficulties, receiving no funds even the first year, when the Republicans controlled both houses. This failure was due largely to the traditional congressional view that DOE should focus its funding on domestic priorities but also reflected a lack of effort on the Bush administration’s part to gain congressional support. The result was not just severely restricted resources for the work of the six task forces in which DOE was involved, but also considerable interagency tension over resources and alignment with administration priorities. State Department support to DOE national laboratories enabled sustained expert engagement, but the lack of DOE involvement arguably limited the effectiveness of the work. Other countries contributed substantially, with an initial set-aside by Australia of more than $100 million and spending of more than $10 million by Canada. Because of the partnership model in the APP, these investments leveraged even greater private sector spending, an important point when considering the overall impact of the effort. Ultimately, however, the lack of dedicated U.S. funding became apparent to the other participants and limited their willingness to contribute further. This was soon exacerbated by political developments.

Lost in transition

After the election of President Obama in November 2008, federal employees working on climate policy expected that existing efforts would be reviewed and then perhaps adjusted to match his stated intent to make climate change a government priority. Staff assigned to the Climate Change Technology Program, an interagency coordination mechanism established under the Bush administration, prepared a “Climate Change Transition Sourcebook” listing all climate change mitigation activities across the government in anticipation of such a review. However, the new administration’s focus on trying to pass comprehensive climate legislation (the Waxman-Markey bill) meant that other government climate policy efforts were of lower priority. The sourcebook was provided to incoming administration officials, but those of us who worked to prepare it never received acknowledgment or feedback. The interagency group, despite being codified in the Energy Policy Act of 2005, never met again and has functionally ceased to exist.

Those engaged in the APP had reason to believe that it was a successful model of international engagement on climate, worthy of continuing in some fashion. After all, the European Commission and other governments had inquired about joining, and a related activity initiated by President Bush in May 2007, the Major Economies Process on Energy Security and Climate Change, was continued by the Obama administration under the name of the Major Economies Forum on Energy and Climate (MEF) in March 2009. The MEF convened governments of 16 nations and the European Commission to focus mostly on areas of common ground with respect to the UNFCCC negotiations.

At an APP PIC meeting in Australia in May 2009, U.S. representatives noted the appointment of new senior officials in various agencies, including a Special Envoy for Climate Change, and highlighted the possibility of new domestic climate legislation. Although they stated that they thought the APP had been successful, they indicated uncertainty about its future: “Therefore while it is true that we are clear on our commitment to climate change and clean technology development and deployment, it is also true that the leadership that will ultimately define our engagement strategy is still coming together….” (italics mine).

By the time of the third APP Ministerial meeting in October 2009, formal U.S. statements were beginning to make clear that the APP would, at most, be taking a back seat to the UNFCCC process and the MEF: “We expect Copenhagen to be a signal meeting in our efforts to define measurable, reportable and verifiable national actions, as well as the international framework to support such efforts through finance, technology transfer and capacity building…. All of us are also working to establish a Global Partnership through the Major Economies Forum process, and we have been deeply involved in the development of action plans that will soon be provided to our leaders.” The tone with respect to the APP was much less assured: “We will have a continuing need to evaluate the APP’s niche as our approaches and the broader framework for technology cooperation develops, both over the coming year and beyond.”

At COP-17 in Copenhagen in December 2009, new Energy Secretary Steven Chu announced, on behalf of President Obama, the launch of a five-year, $35-million Renewables and Efficiency Deployment Initiative, known as Climate REDI, along with the release of 10 Technology Action Plans that had been developed after the first meeting of the MEF. The Action Plans, according to a White House fact sheet, were intended to “summarize mitigation potential of high-priority technologies, highlight best practice policies, and provide a menu of specific actions that countries can take individually and collectively to accelerate development and deployment of low-carbon solutions.” This statement, with its focus on best practice policies and specific actions, provides a clear indication of the shift toward a more policy-centric approach. The fate of the APP was becoming evident as well. Though it would hang on formally for almost a year and a half, no PIC meetings were held until the final one in April 2011, at which the formal dissolution of the partnership was agreed to at the behest of the United States.

The demise of the APP was a considerable disappointment to the partner governments that had invested in it, the private sector players who had been successfully engaged, and many of the staff who had been involved in its successes. A summary presented at the third and final APP ministerial observed that the “Partnership is now widely noted as a model for sectoral public-private sector cooperation,” consistent with the Bush administration’s original intent. Beyond its 175 projects, plus 22 “flagship” projects, key APP accomplishments included: promoting peer review and dissemination of best practices in the power, steel, and coal mine sectors; demonstrating high efficiency buildings in India and China; piloting post-combustion and oxyfuel CCS technologies; supporting efforts to harmonize compact fluorescent light testing standards; promoting the use of combined heat and power technology in China; and helping build capacity to match small and medium enterprises investing in renewable energy with sources of finance.

The Obama approach

The Copenhagen announcement stated that the mechanism for carrying forward Climate REDI and the implementation of the Technology Action Plans would be a new forum, the Clean Energy Ministerial (CEM), to be convened in Washington in 2010. The following July, the first meeting took place, featuring ministers or other high-level representatives from 22 governments and the European Commission, essentially the same governments represented in the MEF, plus some smaller economies that were there for geographic representation (South Africa, the United Arab Emirates) or specific leadership in clean energy deployment (Denmark and the other Nordic countries). However, there was a key difference between the MEF and CEM: the CEM deliberately invited ministers with responsibility for the energy portfolios in their countries, not environment or climate change.

That decision followed careful deliberation by the leadership of the State Department and DOE. Although senior officials in both agencies felt the CEM should remain a spin-off from the MEF, since it had its origins there, they also noted that the expertise to manage engagement across a wide range of clean energy topics was in DOE. Staff in State and DOE recalled the challenges of having the APP managed in the State Department but executed by other agencies, as well as the political complications of having an initiative linked so closely to the climate agenda. Secretary Chu was also felt to have a degree of credibility and recognition that would help to raise the profile of the effort. This would turn out to be a fateful decision, with both positive and negative results.

At the first CEM meeting, participants offered up various initiatives in which they would lead or participate. Unlike the APP approach of focusing from the start on specific energy producing or consuming sectors, the CEM is a bottom-up process, where new initiatives reflect the interests of governments willing to support the work. As with the APP, participation in any given initiative is voluntary. The CEM describes itself as “a global forum to share best practices and promote policies and programs that encourage and facilitate the transition to a global clean energy economy.” Consistent with that theme, the United States put forward the Clean Energy Solutions Center (CESC), which “helps governments design and adopt policies and programs that support the deployment of clean energy technologies.” The United States also offered to lead the Superefficient Equipment and Appliance Deployment (SEAD) initiative, to provide “access to the resources and technical expertise needed to build and implement cost-effective product efficiency standards and labels and market transformation programs.” SEAD receives U.S. funding of $4 million per year, more than any other CEM initiative, and was frequently touted by Secretary Chu, a passionate advocate of appliance standards. CESC and SEAD, with their focus on policies, programs, and standards rather than private sector engagement and project development, are clear hallmarks of the more policy-centric approach of the Obama administration.

Another U.S.-led CEM initiative receiving substantial support is the International Smart Grid Action Network (ISGAN), a “collaboration to advance the development and deployment of smarter electric grid technologies, practices, and systems.” While the smart grid is valuable for improving the reliability of the transmission and distribution network, one of its other key benefits is that it enables greater demand-side management and integration of distributed renewable energy sources, both required elements of a more decentralized electricity system. The 21st Century Power Partnership, also led by the United States, was later added to focus more explicitly on the role of the grid, distributed renewables, and flexible demand response to contribute to development of a new paradigm for the electricity sector, driven by factors such as the growth in rooftop solar and the need to manage intermittent electricity supply and shift demand between different times of day. This willingness to envision disruptive technologies and new approaches that threaten existing utility business models is another hallmark of the Obama administration’s approach.

The United States put forward several other CEM initiatives, all of which share a focus on policies to increase the deployment of existing technologies or more broadly disseminate best practices. None explicitly partner with the private sector.

Not surprisingly, relevant private sector actors feel, in contrast to their experience with the APP, that the CEM has not adequately engaged them. CEM meetings have included public-private roundtables on clean energy topics, and ministers typically report that they enjoy these opportunities to engage with private sector representatives and other experts. But it is difficult for private sector participants to justify long trips to distant venues for such a brief time spent with policymakers, and with no other opportunities to weigh in or participate in the projects. This neglect has been exacerbated by a lack of explicit White House support. In the Obama administration, no White House champion for international climate cooperation outside the UNFCCC process emerged until John Podesta was named as counselor to the President in 2014, and no White House representative has participated in a CEM meeting since the first one in Washington in 2010. Yet such high-level representation is critical to attract private sector engagement.

As alluded to earlier, the consequences of the lack of explicit linkage of the CEM to the MEF and to those engaged in climate negotiations have been significant. The absence of climate negotiators in the CEM has enabled it to be remarkably free of the unhelpful rhetoric surrounding the relative responsibilities of developed and rapidly industrializing economies that plagues the UNFCCC negotiations. But energy ministries do not command the same attention or receive the same funding for international engagement as those focused on climate change. As a consequence, the CEM has a relatively low profile among those who follow climate issues. Energy ministries also suffer from a lack of funds for international cooperation. DOE has overcome this by means of an agreement with the State Department that enables an interagency transfer of funds, but not all countries have a comparable mechanism. The U.S. has contributed $40 million to the CEM but, in contrast to the APP, the total for other countries is less than $10 million. Efforts to raise the ambition of other CEM participants, perhaps through a more explicit linkage to the MEF or a leader-level process, are under consideration by senior State Department and DOE officials but would need support from the White House.

The dissolution of the APP and the move away from private sector engagement in international climate cooperation represents a shift from a more “conservative” to a more “liberal” policy approach to international climate policy. But the CEM is only one element of a more diverse and complex Obama administration portfolio. As mentioned, funding for major multilateral R&D efforts (GIF, CSLF, IPHE) begun in the Bush administration has continued, and the MEF is still being used for constructive engagement of major economies outside the UNFCCC. On the domestic front, although EPA’s impending GHG regulations are often painted as intended to destroy coal-fired power plants, the American Recovery and Reinvestment Act (ARRA) of 2009 provided $3.9 billion in funding for CCS, larger than the $1.6 billion for renewable energy. However, ARRA also provided support for potentially disruptive technologies: $3.9 billion for smart grid investments, as well as $390 million for the Advanced Research Projects Agency – Energy (ARPA-E), which focuses on advancing “high-potential, high-impact energy technologies that are too early for private-sector investment.” Although ARPA-E was mandated under the Energy Independence and Security Act of 2007, the Bush administration did not support its creation and made minimal efforts to implement it, in keeping with their desire to focus on more conventional technology R&D investments. The range of ARRA investments underscore a recognition, in the White House and in Congress, of the potential for both large-scale, centralized low-carbon energy generation and smaller-scale, distributed generation, as well as an openness to new technologies that might emerge. Indeed, the Obama administration’s approach is clearly more “technology agnostic” than that of its predecessor.

Unfortunately, the opposition by much of the private sector to Obama administration climate proposals, as well as the inability of the administration to constructively engage corporate actors as the Bush administration did with the APP, fuels unhelpful hyper-partisan narratives on both sides. Going forward, it will be essential for the private sector to take a more constructive stance on climate change than they have, but this, in turn, will be accomplished only by their active engagement and inclusion by the White House.

The best of both sides

Clean energy technology development and policy implementation are slow processes with no guarantee of success. Program effectiveness requires continuity of political and financial support, as well as support from key non-governmental stakeholders, including environmental groups and the private sector. The timeframe associated with transfers of power between the political parties, whether in the executive or the legislative branches, makes the required continuity difficult to achieve. This has only been exacerbated by the current level of political acrimony, where long wait times for confirmation of presidential appointees can leave existing programs on hold, waiting for direction for a year or more, while the failure to pass annual appropriations leaves new programs unfunded. The irony is that the bigger the political push in support of a program, the greater the possibility of implementation at the scale required, but also the greater likelihood of a backlash from either the appropriators in Congress or the next occupant of the White House. A corollary in the international context is that the tighter the linkage of an international program to the climate negotiations, the more attention it will draw, but also the greater likelihood that it will be derailed by spillovers from the controversies in that forum.

Is there a way around these tensions? I believe it is critical to realize that neither innovation nor regulation alone will solve this problem. Waiting for government-funded innovation to lower mitigation costs risks too long a delay on climate action and ignores the evidence that targets and regulations can deliver huge cost reductions, as they have with solar photovoltaics, which now cost only a third of what they did in 2009. Relying on regulatory approaches alone may catalyze progress in the near term but is unlikely to deliver the mitigation ultimately required to drive emissions to near-zero on a global scale. A parallel approach of using regulations and scaled-up R&D investments stands a better chance of harnessing the market forces needed to enable a successful transition to a low-carbon future. Sustained and adequate funding is also critical, ideally from a policy mechanism that isn’t linked to annual appropriations. This parallel approach has implications for international cooperation. A consensus seems to be emerging that international efforts to address climate change will be a bottom-up collection of commitments by all nations. However, these first steps are likely to fall far short of what is needed to limit GHG emissions enough to avoid significant impacts while also meeting the demand of the world’s emerging economies for economic development. It is therefore incumbent on the major economies of the world to cooperate to a greater degree on complementary R&D and best practice policy efforts. These efforts should be linked to climate goals, yet insulated from the actual negotiation (and politics) of those goals. Participation by and support from the private sector is essential.

Managing U.S. efforts to address climate change is hugely challenging. Reflecting on my own experiences, I believe that what is needed is an administration with the management skills, private sector relationships, and global development focus of the Bush administration combined with the commitment to address climate change, openness to new technologies, and willingness to challenge existing business models of the Obama administration. That is a tall order in today’s partisan environment, but it could also represent an enormous political opportunity for a visionary leader of either party. Bridging the political and philosophical divides necessary to draw sustained support for climate action is terribly difficult, but then, so are the challenges we will face if we fail to do so.

Graham Pugh ([email protected]) served in a number of senior staff positions focused on domestic and international energy and climate issues in the U.S. Department of Energy from June 2005 to June 2014.

Climate Models as Economic Guides: Scientific Challenge or Quixotic Quest?

In the polarized climate change debate, cost-benefit analyses of policy options are taking on an increasingly influential role. These analyses have been presented by authoritative scholars as a useful contribution to the debate.

But models of climate—and especially models of the impact of climate policy—are theorists’ tools, not policy justification tools. The methods used to appraise model uncertainties give optimistic lower bounds on the true uncertainty, at best. Even in the finest modeling exercises, uncertainty in model structure is presented as known and manageable, when it is likely neither. Numbers arising from these modeling exercises should therefore not be presented as “facts” providing support to policy decisions.

Building more complex models of climate will not necessarily reduce the uncertainties. Indeed, if previous experience is a guide, such models will reveal that current uncertainty estimates are unrealistically small.

The fate of the evidence

Climate change is the quintessential “wicked problem:” a knot in the uncomfortable area where uncertainty and disagreement about values affect the very framing of what the problem is. The issue of climate change has become so resonant and fraught that it speaks directly to our individual political and cultural identities.

Scientists and other scholars often use non-scientific and value-laden rhetoric to emphasize to non-expert audiences what they believe to be the implications of their knowledge. For example, in Modelling the Climate System: An Overview, Gabriele Gramelsberger and Johann Feichter—after a sober discussion of statistical methods applicable to climate models—observe that “if mankind is unable to decide how to frame an appropriate response to climate change, nature will decide for both—environmental and economic calamities—as the economy is inextricably interconnected with the climate.” Historians Naomi Oreskes and Erik M. Conway, in their recent book The Collapse of Western Civilization (2014), paint an apocalyptic picture of the next 80 years, beginning with the “year of perpetual summer” in 2023, and mass-imprisonment of “alarmist” scientists in 2025. Estimates of the impact of climate change turn out to be far too cautious: global temperatures increase dramatically and the sea level rises by eight meters, resulting in plagues of devastating diseases and insects, mass-extinction, the overthrow of governments, and the annihilation of the human populations of Africa and Australia. In the aftermath, survivors take the names of climate scientists as their middle names in recognition of their heroic attempts to warn the world.

That the Earth’s climate is changing, partly or largely because of anthropogenic emissions of CO2 and other greenhouse gases, is not the core of the dispute. Instead, the focus has moved to the more difficult questions of “what will be the consequences?” and “what is the cost of offsetting climate change?” Opposing factions use scientific uncertainty instrumentally either to deny or to support the urgency of action to mitigate adverse outcomes. In their previous book, Merchants of Doubt, Oreskes and Conway talk of uncertainty amplification by unscrupulous stakeholders and draw parallels between the denial of the health effects of smoking by the tobacco lobby and the denial of climate change by climate sceptics. Conversely, climate scientist Richard Lindzen, a possible source of Michael Crichton’s novel State of Fear, compares climate change to eugenics at the beginning of the 20th century: a wrong idea vigorously supported by scientists. In the case of eugenics, this included some of the founding fathers of statistics.

In this battlefield of norms and worldviews, what is the fate of scientific evidence?

Given the economic and societal ramifications of climate change, it is not surprising that several disciplines claim to provide certainties and solutions. Among these, computer modeling is perhaps the most visible, pervasive, and opaque.

A recent example that rests on such models is the American Climate Prospectus: Economic Risks in the United States, a study commissioned by the Risky Business Project, a non-profit group chaired by former New York mayor Michael Bloomberg, former U.S. Treasury Secretary Henry Paulson, and environmental philanthropist Tom Steyer. The report invokes a broad battery of models for the impact of climate change, predicting when, where, and how much temperature variation to expect and what the costs will be to address the consequences.

The claimed precision and resolution of these modeling efforts are staggering. The Risky Business report forecasts—at the level of individual counties in the U.S.—energy costs and demand, labor supply, mortality, violent crime rates, and real estate property prices up to the year 2100. (Evidently, these investigators were not enlisted to predict the collapse of real estate prices from subprime mortgage crisis that triggered the recent recession, or that economic catastrophe might have been avoided.) The report presents the amount of computer power and data generated as evidence of the scientific legitimacy of the enterprise. The authors note, however, that out of an abundance of caution they did not model deterioration in cognitive performance as temperatures rise.

Other models, such as those reported in a 2013 Nature paper by Camilo Mora and colleagues, predict when the mean climate in various locations will move outside the range of historical variability under alternative greenhouse gas emissions scenarios, prompting the Washington Post headline, “D.C. climate will shift in 2047.”

To quantify the uncertainty in model predictions—and especially in the response to changes in drivers such as anthropogenic CO2—requires quantifying the uncertainty in the assumptions of the model, the structure of the model, the physical approximations in the model, the data used to calibrate the model, and the parameters of the model. As a result, forecasts of global average temperature even a few years into the future are extremely uncertain, even at the level of global averages—and likely much more so at the level of counties or cities. For example, in the fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC), forecasts for the period 2071-2100 generated from 12 different climate models predict that England will experience anywhere from a 60 percent decrease to a 10 percent increase in summer precipitation. Our own technical research has shown that if one accounts for all the uncertainties built into Nicholas Stern’s well-regarded and influential The Economics of Climate Change, the uncertainty in the cost of climate damage is so large as to preclude any meaningful conclusion as to the urgency to act at the present time to counteract it. The same critique applies to those who, like William Nordhaus, conclude from the same type of cost-benefit analyses that action can be delayed, in contrast to Stern.

Some major climate modeling exercises strive to give a level-headed assessment of uncertainty. The UK Meteorological Office attempted to quantify the overall uncertainty in climate forecasts provided by their HadSM3 model, using simple numerical approximations of the more complex, but still approximate, numerical climate model to account for the uncertainty in a wide range of model parameters. This is laudable, but such “emulators” of climate models have their own large uncertainties as approximations of the already-approximate, high-dimensional models.

Likewise, the fifth assessment report of the IPCC gives qualitative descriptions of uncertainty for forecasts and parameters. For example, the assessment report states, “Equilibrium climate sensitivity is likely in the range 1.5°C to 4.5°C (high confidence), extremely unlikely less than 1°C (high confidence), and very unlikely greater than 6°C (medium confidence).” These qualifiers reflect the type, amount, quality, and consistency of the evidence, using probabilistic language to describe uncertainty and expert judgment. Unfortunately, the probabilistic assessments appear to rely on stylized, untestable assumptions without an empirical basis, and the expert judgments are, at the end of the day, opinions rather than facts—opinions influenced by the very models whose reliability is in question. Indeed, the 1.5°C to 4.5°C uncertainty range has persisted through 30 years of advancing climate science; as long ago as 1998, Jeroen van der Sluijs and others showed that the range was arrived at through what amounts to a back-of-the-envelope estimate whose stability over time is much more a social and political phenomenon than the result of any sound statistical method.

Although climate models have become more complex and techniques for evaluating their uncertainty have evolved in the past decades, quantifying their uncertainty usefully in climate models remains impossible. In many cases little or no information is available to justify even crude ranges of uncertainty assumed for various inputs. “Expert opinion” is not a substitute for data or tested physical theory.

When the uncertainties are uncertain

It may be possible, at least in principle, to quantify the uncertainties of inputs to the model—the range of plausible values of a given driver. But “structural uncertainty,” which concerns the choice of variables and processes to include in the model, as well as how the variables and processes are characterized mathematically and how they interact, is likely a larger source of uncertainty.

A variety of methods have been proposed in recent years that, according to their proponents, can explore structural uncertainty, thereby giving a full accounting of forecast uncertainties. The most common method, which uses the results of multiple climate models from various research institutes, is based on the assumption that differences between the results of different climate models are a reasonable approximation of the structural uncertainty of a particular model as a representation of the real world. This amounts to assuming that the biases of different models average out over the “ensemble,” whereas in fact, the models are likely to share similar biases, since they involve similar approximations, similar algorithms, and similar training data.

To understand the quantification problems posed by the structural uncertainties, let us investigate the analysis of uncertainty in a climate model given by the UK Meteorological Office in 2009’s UK Climate Projections (UKCP09) Science Report: Climate Change Projections. In this nearly 200-page document, the uncertainties from many sources are explained, and their effects propagated through to the model results, ending in “probabilistic” forecasts of climate change. The report states, “[although] a number of methods for probabilistic climate projection have been published in the research literature, we are not aware of any that have been designed to sample uncertainties as comprehensively as is done in UKCP09.” This suggests that UKCP09 represents the state-of-the-art in uncertainty analysis of climate models as of 2009.

UKCP09 seeks to sample both parametric and structural uncertainties. Sampling parametric uncertainties is done by constructing a “perturbed physics ensemble,” which is simply a collection of model runs of variants of the Met Office’s climate model, where each run has different, but plausible, values assigned to variables. For example, the model may be run several times with different values for temperature and water vapor in a given area to determine future cloud cover. The distribution of input values is an invention constructed by eliciting opinions from experts. Running the model many times, using many different variables results in some climate simulations that are more realistic than others, so each model variant is additionally weighted according to its performance in predicting recent climate observations and in hindcasts over the past 90 years. In the case of cloud cover, if the model output bears little resemblance to observed cloud cover in a particular area, that projection is given less weight than one that more accurately describes observed cloud cover. The perturbed physics ensemble thus produces a set of projections that have, according to the report, statistically knowable parametric uncertainties that can be described in terms of probability. However, the reporting obscures the fact that the probability distribution is an input, not an output.

UKCP09 also attempts to evaluate structural uncertainties in its model. It does so by comparing its ensemble of predictions to those of alternative climate models from other research groups. This approach is based on the assumption that “the effects of structural differences between models can be assumed to provide reasonable a priori estimates of possible structural differences between [the model] and the real world.” That is, it assumes that predictions from members of the ensemble somehow bracket the truth.

This assumption has no basis. UKCP09’s authors compare the projections of their ensemble with those of the other climate models and then estimate the structural uncertainty as a probability distribution of those projections, effectively treating the ensemble of models as if they were a random sample of all possible models.

For instance, for the UKCP09 to project future rainfall in a particular area, the authors use the Met Office climate models to run the perturbed physics ensemble with many different variables that might affect future rainfall to generate a range of possible outcomes. These are then judged by how well these outcomes conform to observed rainfall to produce an initial probability distribution—say, a 90 percent probability that summer rainfall in 2050 will decrease by less than 40 percent. This distribution is compared to the rainfall projections from alternative climate models, which have their own uncertainties—but which are assumed to be uncertain in their own distinct way—so that the predictions of the ensemble are, overall, unbiased. This, according to the authors, allows for the quantification of both parametric and structural uncertainty in the model projections of future rainfall. But there is no reason to think that the variability across the ensemble is a probability distribution at all, much less a distribution centered at the “real” answer.

This approach may give lower bounds on the uncertainty, but cannot give defensible upper bounds, for several reasons. First, such “ensembles” are not in any sense representative of the range of possible (and plausible) models that fit the data. Second, the structural uncertainties of the models considered are related: the models generally rely on similar physical approximations, similar numerical methods and algorithms, similar parameterizations, and similar calibration data. Climate models reflect, to differing degrees and with varying approaches, climate science’s best understanding of the processes that govern the Earth’s climate. But some processes, such as aspects of the methane cycle and the feedback effects of clouds, are poorly understood and not accounted for reliably in current climate models. So models share common errors whose magnitudes are simply not known.

The errors in the ensemble of model runs with differing variables (using the Met Office’s climate models) are not statistically independent—or even random. This fact is acknowledged in the UKCP09 report, which states, “our estimates of discrepancy [structural uncertainty] can be viewed as a likely lower bound to the true level of uncertainty associated with structural model errors.” Furthermore, the structural uncertainty is estimated, in part, by comparing the model with other models in hindcasting historical climate change. Since these models rely on similar modeling assumptions and approximations and are calibrated to the same historical observations, one would expect their output to be similar—and to have similar errors and biases. The biases of different models are unlikely to offset each other. The models do not provide independent estimates of climate change.

The Met Office also performed sensitivity analysis to assess the relative impact of assumptions about various inputs on the uncertainty of model outputs. But UCKP09’s sensitivity analysis relies on the assumed randomness of the input parameters, among other things. As the report puts it:

The key point is that although the UKCP09 probabilistic projections provide estimates of uncertainties in future climate change, it is also inevitable that the probabilities are themselves uncertain. If the uncertainties in the probabilities are sufficiently small compared with the uncertainties quantified by the probabilities, then the UKCP09 results are likely to be sufficiently reliable to be used in support of assessments of impacts, vulnerability, or adaptation.

This neglects the fact that the “uncertainties in the probabilities” are also assumptions—not a matter of physics or measurement error.

Finally, the sensitivity analysis varies only a subset of the assumptions and only one at a time. That precludes interactions among the uncertain inputs, which may be highly relevant to climate projections. Elsewhere we have called these styles of sensitivity analysis “perfunctory.” In multidimensional spaces, varying one factor at a time is tantamount to counting uncertainties instead of weighing them.

Overall, there is a worrying tendency in climate science to claim that model uncertainties are quantifiable and manageable, but there is little or no statistical basis in the methodology of estimating uncertainty, especially structural uncertainty. The evidence suggests that even the quantifiable uncertainties are significantly underestimated. Used in this way, models become, in the words of a classic 1993 paper by Silvio Funtowicz and Jerome Ravetz, “substitutes for disciplined thought and scientific rigor.”

Scientific insight is not policy evidence

Economist Frank Knight distinguished between risk and uncertainty in a celebrated 1921 work entitled Risk, Uncertainty, and Profit. According to Knight, risk corresponds to the possibility of applying probabilistic reasoning and the calculus of probabilities (such as when playing roulette), whereas uncertainty corresponds to the real-life situations where such a computation is impossible, simply because “we do not know what we do not know.” Applied to the economy, profit should accrue to one who accepts inescapable uncertainty, not to one who can compute risks. Intellectually, Knight’s position was close to that of John Maynard Keynes, in denying that our thinking can be described by a probability distribution over all possible future events. The hubris of modeling “epistemic uncertainty”—the unknown unknowns—as a probability distribution lies, in part, in assuming that we know a great deal about what we do not know.

Brian Wynne, a leading risk theoretician, expanded Knight’s framework by distinguishing between:

RISK – Know the odds.
UNCERTAINTY – Don’t know the odds: may know the main parameters. May reduce uncertainty but increase ignorance.
IGNORANCE – Don’t know what we don’t know. Ignorance increases with increased commitments based on given knowledge.
INDETERMINACY – Causal chains or networks open.

Wynne elaborates: “Science can define a risk, or uncertainties, only by artificially ‘freezing’ a surrounding context that may or may not be this way in real-life situations. The resultant knowledge is therefore conditional knowledge, depending on whether these pre-analytical assumptions might turn out to be valid. But this question is indeterminate—for example, will the high quality of maintenance, inspection, operation, etc., of a risky technology be sustained in future, multiplied over replications, possibly many all over the world?”

Yet some experts seem convinced that they can model the structural uncertainty of climate models and refuse to make the Knightian distinction between risk and uncertainty, let alone ignorance and indeterminacy. In truth, no one knows how well climate models can forecast climate change: estimates of uncertainty are themselves almost entirely uncertain. One only has to examine the IPCC’s recent assessment report to see this: of the 114 models in the ensemble, 111 failed to predict the recent 15-year slowdown in the increase of global mean surface temperature, many by an order of magnitude. Although natural decadal variability may explain this to some extent, and the long-term trend might still be valid, it does not inspire confidence in the accuracy of model forecasts.

Research is improving our understanding of the complex processes that affect the climate. Does this, coupled with increasing computing power, mean we will eventually have models that provide accurate forecasts of climate change and the costs of its effects? No. Even proponents of model-based assessment of climate impacts admit that the more one understands climate, the more model predictions may reveal that current estimates of uncertainty are unrealistically small. The UKCP09 report states that although they hope that better modeling will eventually reduce uncertainties, “this cannot be guaranteed as the introduction of processes not yet included (for example, feedbacks from the methane cycle), or as yet unknown, could have the opposite effect.”

Our theoretical and observational knowledge give us strong reasons to be concerned about the consequences of climate change and to act to mitigate its future effects. Modeling the economic cost of climate change necessarily requires accurate forecasts of the magnitude and locations of its various effects (which aren’t available). But, as detailed in a recent article by Richard A. Rosen and Edeltraud Guenther, extra layers of uncertainty are added because of the need for assumptions about the future growth of the economy and population—not to mention the highly subjective “discounting” of future costs and benefits against present ones, the uncertainty in future technologies, and the uncertainty of future changes in production and consumption patterns.

A good demonstration of the volatility of these cost estimates is that even when using the same model, different teams cannot agree on the urgency and severity of action. Much of the difference is due to the assumed form of the function that relates damage to surface temperature. Different research teams are apparently able to propose different functions that are equally plausible, since there is little or no evidence to constrain them, as inadvertently shown in a recent paper by Simon Dietz and Nicholas Stern that tries to show that models used by the economist William Nordaus to suggest less urgency to act on climate are consistent with an interpretation of more urgency.

Given their uncertainties, the value of climate models to the policy debate depends on the important difference between policy simulation (performed by scholars to gain insight in their discipline) and policy justification (where the same scholars or other parties produce evidence to support adopting a specific policy). The difference between scientific insight and evidence for policymaking is profound. Indeed, in policymaking, the question raised by some model-based “facts” is whether, in the face of such substantial uncertainty, they are scientific at all. Yet when these numbers enter the policy world, often through the media, they look and sound like incontrovertible facts. The Financial Times recently published an article by its chief economic commentator Martin Wolf, who considers as “plausible” economic models suggesting “that the aggregate loss of world output by 2030, under the low-carbon option, would be equivalent to a one-year hiatus in economic growth.” If models are judged by their plausibility—by definition a non-quantitative attribute—why should we derive from these models quantitative information? And why should this information be relevant for policy?

A parallel could be drawn here with long-term weather forecasts. A story is told by Nobel Laureate Kenneth Arrow, who was asked to provide weather forecasts one month in advance during World War II:

The statisticians among us subjected these forecasts to verification and they differed in no way from chance. The forecasters themselves were convinced and requested that the forecasts be discontinued. The reply read approximately like this: “The commanding general is well aware that the forecasts are no good. However, he needs them for planning purposes.”

Climate models, by augmenting our scientific intuition, may help us to understand climate, though we might question whether the cost in time and resources absorbed by these exercises might be deployed better elsewhere. But when we attribute to them predictive capabilities and attempt to introduce them, through political processes, into our policy planning, the numbers pollute the debates with a spurious impression of rationality, prediction, and control. One danger for society is that we will be condemned to endless debates over uncertainties, with models deployed to support various competing positions about which policy pathways to follow. Another, just as serious, is that, with excessive confidence in our ability to model the future, we will commit to policies that reduce, rather than expand, available options and thus our ability to cope with the unknown unknowns of our future.

Where Does it Hurt?

Pain compels sufferers to “pay attention.” Suddenly, the person in pain becomes aware of her body—the clutching at the throat, the rough thump-thump in the region of the heart, the rumbling of the stomach, or the piercing spasm in the lower spine. Witnesses to suffering are also part of the drama of pain. They watch, listen, and judge. Is her pain real? Is it mild or severe? On a scale of one to ten, in which “one” represents “no pain” and “ten” is “the worst pain possible,” is it a two or an eight? The suffering person knows that worlds of unhappiness rest on the way she communicates her pain to these witnesses. As an author known simply as “A Mother” advises her children in Hints on the Sources of Happiness (1819), if a person enduring “bodily torture” comports herself correctly, she could stimulate in witnesses “a pity, a love, a veneration that binds him perhaps for ever after to the sufferer.” Implicit in such instructions is the assumption that sympathetic communities could be forged only if the person in pain followed certain rules of comportment. People in pain need to follow the appropriate pain script: they need to learn to “suffer well.”

Sufferers have always sought to communicate their pain. However, they have repeatedly been dismayed not only by how difficult it is to find the right words to talk about their disruptive body but also by the often-dismissive attitude of those people who profess to wish to help them. It is no exaggeration to say that a political and cultural war is being waged against people in pain. And not just any sufferers: those whose aches are most likely to be disparaged or even ignored altogether tend to be poor or female. In contrast, the people who decide who deserves to be relieved of pain are those with power: physicians, pharmaceutical companies, politicians, lawyers, and judges.

This is the problem that Keith Wailoo addresses in his book Pain: A Political History. It is a brilliant exposition of the political function of physical suffering in the second half of the 20th century. Wailoo, the Townsend Martin Professor of History and Public Administration at Princeton University, has a reputation as one of the most distinguished commentators on the health of Americans and the politics of medicine. This latest book is a forensic analysis of the political realities of pain in America.

Although the book is about polemics, Wailoo is relentlessly even-handed. He shows how Republicans and Democrats, conservatives and liberals, seek to appropriate pain to their cause. In the aftermath of the Second World War, U.S. health policy was forced to undergo a major overhaul. Universal military service had changed the relationship between citizens and the state. The battleground was decided when President Truman fought for a “fair deal” for wounded veterans, arguing for the establishment of compulsory health insurance, and the American Medical Association disputed him by evoking fears about “socialized medicine.”

The clash between those who fear the provision of public relief on the grounds that it creates “Big Government” and dependent people, against those who reiterate the duty of governments to their citizens, has contributed to the neglect of suffering Americans. Certain themes return time and again: health commissioners, politicians, and physicians debate how they can truly know whether a complaint of pain is real or simply an excuse for shirking. How can pain be objectively calibrated? How much was each ache or sting worth in dollars? Crucially, who should be allowed to decide?

Unsurprisingly, physicians found themselves at the forefront of these debates. But they often turned out to be reluctant assistants to people in pain. For example, in 1955, General Omar Bradley’s Commission on Veterans’ Pensions asked 153 eminent physicians whether pain and mental anguish should be taken into account when calculating pension entitlements. These doctors fretted over the reality of “subjective symptoms;” they confidently declared that many veterans were malingerers; they were concerned that pensions would penalize the stoical ones; and they worried about the lack of an objective way to measure pain. These anxieties recurred throughout the century.

People in pain were made into convenient symbols for what was thought to be wrong in society more generally. In the 1960s, for instance, “permissive parenting” was blamed for the lack of forbearance among youth. In the 1970s, there were fears that suffering was a form of “learned dependency.” As Steven Brena argued in his influential book Chronic Pain: America’s Hidden Epidemic (1978), people who fixated on their suffering ended up hurting more. Those who had less of a stake in their pain seemed to feel less agony and respond better to medication. Whatever the period, “dependency” and “addiction” were the twin goblins to be feared above all else.

The socio-political nature of these debates was especially evident in the rapid adoption of the “gate control theory” of pain. Introduced in 1965 by Ronald Melzack and Patrick Wall, this new theory drew on research in computer science to argue that people were processors of information. Melzack and Wall proposed that there was a “gating mechanism” in the dorsal horns of the spinal cord that allowed the perception of pain to be modified. In other words, cognitive and affective processes (as well as physiological ones) influence how people actually experience pain, and non-painful stimuli could “block” or suppress the sensation of pain. It was a theory that was receptive to more “alternative” treatments, including hypnosis. Crucially, it endorsed subjective feelings—resonating, Wailoo notes, “with the era’s legal battles, cultural critiques, pain relief practices, and liberalizing political commitments.” Even scientists who were ambivalent about gate control’s scientific underpinnings ended up endorsing it. After all, it worked. As senior pain researcher P. W. Nathan rather grumpily concluded, “although the theory has led to the successful treatment of chronic pain, this does not mean that it is correct…. Ideas need to be fruitful, they do not have to be right.”

Wailoo’s book should be read alongside Daniel S. Goldberg’s The Bioethics of Pain Management: Beyond Opioids (2014), who shares Wailoo’s dismay at pain medicine in the United States. Both scholars lament the failure of the health care system and practitioners to take account of the social and cultural contexts in which real people in the real world suffer. They acknowledge that both the problem and the solution are political. Access to effective pain relief is stratified. Wailoo shows that Americans are “overmedicated and undertreated.” The problem, though, is that it is the rich who are overmedicated; the poor, undertreated. As Wailoo observes, in the Reagan era “the pain of the taxpayer was true pain; the pain of the disabled or the addict was suspect. The pain of the fetus outranked the alleged pain of the disabled housewife or injured worker.”

Wailoo castigates both conservative and liberal positions. He calls on readers to pay more attention to the political motives of people who make claims about pain, whether they are politicians, spokespeople from the pharmaceutical industries, physicians, or even pain-sufferers themselves. Wailoo’s subtle and critical exploration of these claims illuminates the contested ground that pain occupies in U.S. political culture.

Pythia of Science

Sophia wakes to find her SocialStream full of supportive texts, toots, bleets, and bumps, including one from Noah.

gr8 luck today, babe!

His message grates her, negating the positive vibes from her other well-wishers, as she moves about in the early morning darkness, brushing her teeth, showering, shoving her shoulder-length gray hair into its usual functional ponytail.

Babe? Who is he to call her babe? When they’d been together—years ago now—he’d never used the term. Maybe it’s the kind of word that’s hip in Bangalore. Certainly being there has changed him. His SocialStream is nothing but science stuff and the most banal pictures imaginable: a bunch of women in saris in a Starbuckle’s, some families eating chicken nuggets at a McKFC. She’s refrained from commenting innumerable times: You could see the same damn thing in Chicago or Boston.

Or even in this backwater town, Sophia thinks, heading out into the frosty air. Though it’s less likely than it used to be, with so many heading back to India, accompanied by a slew of Americans like Noah.

She breathes deeply, the cold air scorching her nostrils and lungs. This place is a backwater, but it’s come to feel like hers. The fields of 20-foot-tall Ethocorn™ surrounding the town may be the butt of jokes told by people who’d see them only from their airplane seats seven miles up, but to Sophia they’re a protective cocoon: the promise of security and stability. She’s lived here for six years, by far the longest anywhere since graduate school, and she’d be happy never to leave. Give her cornfields and real winters any day.

The bus drops her a block from the Bionomics Building. She scans inside and trudges down the dim corridors, past purring sequencers, humming freezers, and ominous groaning from the autoclave room. Assistant professors like Sophia enjoy small desks at the edge of the building’s “photic zone” (a joke among Bionomics denizens: the layer beyond which no natural light can penetrate). Senior faculty luxuriate in their very own cubicles near the windows. But most everyone else operates entirely with shared machinery, space, and lab benches, every inch piled with equipment: centrifuges and microscopes, flasks and tubes, boxes of wipes and stacks of petri dishes, jars of reagents and powders.

Sophia loves the lab, but there’s a reason—beyond her pittance of a salary—that her rented apartment is so sparsely decorated: after spending most of her waking hours in this insane clutter, retreating to order and simplicity is essential.

She turns a corner and faces precisely what she hoped not to see, especially this morning: the back of Professor Emma Davis’s bald head. Though it’s not yet seven, Davis works feverishly at the bench, a whirl of test tubes and flying pipette tips. Music—Sophia can’t tell what she’s listening to, wonders if Pythia have a special mix—blasts into Davis’s ears. She wears latex gloves at the end of her toned arms, obscuring the dark tattoos on her wrists, but otherwise she’s clad for the gym, from which—if the reflective sheen from the fluorescent lights on her head is any indication—she’s recently returned.

Sophia feels a familiar sense of inadequacy. Sure, Pythia like Davis are always working, but they’re also fanatical about physical fitness. Pipetting like that would be an open invitation for another one of Sophia’s increasingly frequent arthritic flare-ups. But it’s more than that: despite having no meaningful existence outside the lab, Emma Davis looks a good 15 years younger than Sophia.

But we’re about the same age, Sophia thinks. And we’re colleagues…at least for now.

She rubs her wrists absently as she remembers the day, two years before, when she’d learned that her fate was intertwined with Emma’s. Sophia waited uncomfortably in Myles Lutton’s palatial eighth-floor cubicle. Photos of the chairman’s children—three or four from what she could discern, and they seemed to play every sport imaginable—adorned the desktop and shelves. Professor Lutton wore a white lab coat, though it’d surely been years since he’d worked at the bench. He flipped through papers, pretending not to enjoy prolonging her unease.

Only a certain number of tenured slots came open, and when they did, it was up-or-out for assistant professors. University life was always like that, but with competitive tenure, it wasn’t just their own research productivity—grant dollars, publications, citations, students, and postdocs—that mattered; it was their productivity relative to particular colleagues. Up-or-out meant up for one and out for the other.

Finally, he spoke. “Emma Davis.”

“She’s Pythia,” Sophia responded, trying to keep her surprise, and panic, down.

Lutton cocked an eyebrow. “I realize that. But there aren’t many other choices.”

“Well, what about Dorsey? Or Chang? Or Velasquez?”

Lutton smirked, his eyes on the floor. “The algorithm,” he said, “chose Davis.”

Oh, bullshit. She saw it now: the others were men. It made perfect sense politically. This choice guaranteed the tenure line went to a woman. Regardless of whether Sophia Sandoval or Emma Davis won tenure, the real winner would be the Department of Oncological Metabolomics …and its chairman, Myles Lutton. But someone was going to lose in this situation. And Pythia almost never lost.

Coming back into the moment, Sophia slinks past the bench, grateful that Davis hasn’t noticed her.

At her desk, Sophia checks up on happenings since she left the lab nine hours ago. Something looks off in her postdoc Alexandru’s latest batch of results, but insofar as she can interpret the broken English of his notes, he’s not troubled. She sighs; she’ll have to take it up with him when he comes in later. Second-rate people, a critical voice in her head says, you’ve got second-rate people because you didn’t go to Xu’an as you should have. None of this would be happening if she’d gone to Xu’an. And, while Bangalore wouldn’t exactly be close by, it’d sure be closer.

But it’s too easy to forget she’s not the only one with something at stake. Should Sophia lose her competitive tenure bid, Alexandru—who she knows tries his best—will be left without a valid visa sponsor. Before she’s even finished cleaning out her desk, he’ll be on a one-way flight back to Bucharest to spend the rest of his life driving a taxi.

After the conversation with Lutton, Sophia opened up a new line of research: Emma Davis herself. But beyond Davis’s bibliometric productivity statistics—right there, of course, on her ResearchCVBook profile—the trail was cold. Davis joined the Pythia nearly 25 years earlier and at that time ceased to exist beyond her scientific persona. Typical. But what had Sophia been hoping for? Some dark personal secret? A case of research misconduct swept under the rug?

Sophia exchanged few words with Emma over the years, either before or after being assigned to an academic death match with her. In this way, at least, she knows competing with a Pythia makes life easier. In other cases, all manner of dysfunctional relationships have developed between competitive tenure rivals. Some steal each other’s spouses; others become each other’s spouses. Some refuse to acknowledge the other’s existence; others do everything in their power to stamp it out. There’s the whole category of “PostProfs” who have lost their competitive tenure bids. Many leave the university entirely. Some accept offers to work for the victor in what Sophia considers a mix of desperation and self-loathing. Others, in a form of academic regression, return to work for their dissertation advisors. And then there’s the famous instance where both victor and vanquished, who’d become good friends, went to a bar after the decision and drank themselves to death.

Well, that sure as hell isn’t going to happen here, Sophia thinks. But with no vulnerability to exploit, what was she going to do: spike Davis’s reagents? Poison her samples?

Messing with a Pythia meant courting disaster, and science lore—the kind of stories told to graduate students at boozy lab happy hours or conference hotel bars—was full of chilling rumors. A disagreement over the use of lab equipment, missing chemicals, even an improper citation leads to a visit—usually at home, late at night—from a stern, bald woman you’ve never seen before. She warns, and then she leaves, but now you’ve embarked down the Pythia Force Continuum. Few continue further, but there are cases.

An infamous one involved an assistant professor who liked making lewd remarks to the Pythia in his department. He was warned repeatedly, which only provoked him. His tires were slashed. His pet cat went missing. He kept it up.

When his home was broken into, he responded by taking a swing at his Pythia colleague. The next day his seven-year-old son arrived home from school terrified, his head shaved bald, with tattoos—they were permanent—on his wrists. Soon after, that professor left the university.

Sophia would never sabotage another’s work and she’s confident she needn’t worry about it herself. Such action on Davis’s part would be completely unacceptable to the Pythia. Their motto is “The Science Comes First,” four words not only describing their entire raison d’etre, but also laying out the limits of loyalty to individual “sisters” in a group that might otherwise be confused with a cult or a gang.

Sophia’s thoughts over the past two years have, over time, become less about Emma Davis and more inwardly focused, a round of soul-searching she thinks of as her mid-life crisis (or, when she’s feeling cynical, her end-career crisis). It’s easy to forget, after all this time, how close she herself, as a graduate student, came to joining the Pythia. She found their militancy and focus attractive, but many things held her back: her elderly mother—now gone for more than 15 years—with whom she was close, a boyfriend—now long forgotten—who seemed serious at the time, a fondness for cooking and hiking…hobbies she’s long neglected. Sophia thought she could never make the level of sacrifice the Pythia required.

Acquaintances and colleagues decided differently. Determined young women disappeared, replaced by bald-headed, tattooed fanatics with hard eyes; women Sophia simultaneously envied and pitied, who’d taken monastic vows of devotion to science. Her friend Amanda, after much soul-searching, took the plunge; the new Amanda no longer enjoyed bicycling or happy hours or planning travel adventures. Weeks after the old Amanda spontaneously broke into tears deep into one of their conversations about the future, the new Amanda seemed unable even to laugh at a joke.

Sitting at her desk, Sophia scolds herself. Home is for brooding, lab is for working. But that’s easier said than done, especially today. Where do Pythia like Davis brood, she wonders, with no home to go to? Maybe they brood at the gym, the critical voice inside her replies.

As the first rays of the thin winter sun land on her desk, her daily to-do list pops up on her screen. She scans its dozen items. Move some experiments forward; check in with Karolina, her Latvian graduate student, on those weird physio read-outs she’s been getting; fill out forms to certify her appropriate use of transgenic mice; call the Oberlin-University-Sponsored-By-Doric-Colleges™ Central Service Center to haggle over incorrect sequencing charges; order those…oh, who is she kidding? Every so often life compresses down to just one thing. Today is one of those times. The Koch-Zuckerberg Foundation is announcing its latest round of funded grants today at 10 a.m. sharp, with one of two possible outcomes: 1) they’ve decided to fund her latest proposal, in which case she stands a very good chance of beating out Emma Davis for the tenure slot, or 2) they’ve decided not to fund it, in which case she’s toast. Thus all the encouraging bleets and toots this morning, including the one from Noah.

“I don’t understand why you have to move to Bangalore to be a virtual lecturer,” she’d said during one of their heated discussions before his move.

“Honey,” he’d replied—and now that she thinks of it, maybe “honey” isn’t so far removed from “babe”—“it’s the students who are virtual. Kaplan-Appanoose requires staff to be on-site.” Noah—her pale, pudgy, loveable Noah, with whom she’d lived for five years before they realized they’d save a mint on health insurance if they married—had shrugged his shoulders. “I don’t have anything here. I haven’t for six months.”

She remembers this moment so well because she’d wanted to say, “You have me.” Getting married—even so late, even for such practical reasons—put thoughts in her head, in both their heads. Thoughts of their future, of children. Back then, it still wasn’t too late. Maybe it wouldn’t have changed anything, maybe still all she’d have now would be his boring photo stream and idiotic texts. But she wishes she’d said it.

She rises from her desk and strides toward the windows, stands near the vents. The snow glints in the early morning sun. They don’t have days like this in Xu’an or Bangalore. Do they?

Her proposal is good. Despite all the talk about the best years of young researchers’ lives being squandered in such a tough funding environment, this lead came only around the time Lutton paired her with Emma Davis in a passive duel to career death. It’s the excitement of a possible breakthrough more than anything else that’s kept her motivated. She’s found preliminary evidence that tumor-forming cells produce combinations of metabolites different from those of normal cells. What if cancer cells can be identified this way? Even more exciting, what if particular chemical interventions can change those cells’ metabolisms so they never form tumors at all? Or kill them before they do? Or mark them for elimination by t-cells? Or…the possibilities, if the hypothesis holds true, seem limitless.

Sophia prepared her proposal for the Koch-Zuckerberg Foundation, the world’s second-largest funder of cancer research. Thinking about the largest funder of all still makes her squirm because she’d had a chance, after her fourth postdoc, to join the gravy train. Xu’an University offered her a position with five years of guaranteed funding from the Chinese government. After that, she’d have to compete, but success rates there were higher than anywhere else. She was in her early 40s, and China was hot.

With the best of intentions she flew to Xu’an to check it out: exchanged her dollars for yuan, strapped on an OtoTranslator™, and rode an immaculate bullet train to the city’s center. But when the doors opened, the bubble burst. Crowds jostled her on the sidewalk, JauntCars nearly ran her down on the street. The air was a choking haze; within minutes, dirty sweat droplets formed on her brow, her nostrils clogged, her throat swelled, and dust collected under her fingernails and in her hair. “You’ll get used to it,” people said by way of consolation. “You’ll be spending all your time in the lab anyway. Besides, it’s all the more reason to work on finding a cure!” Morbid humor aside, Sophia couldn’t fathom living someplace where she couldn’t go outside. She flew home and declined the offer.

Had she been Pythia, such action would be unthinkable. The Science Comes First. Joining the Pythia was always good for a woman’s career, and through the Pythia the number of successful female scientists skyrocketed across the disciplines. But Sophia often wondered at what cost.

The story of the Pythia’s origin was a science legend that everyone—even the smarmiest tenured male in the most backward department—knew. It started with Giorgina Blanchett, a 30-something chemistry postdoc who, in the early years of the 21st century, worked at a major university, in the lab of a senior professor named William Wendell. Giorgina slaved away on her research for years and was just at the stage where she was ready to write it up. She hoped to publish it in Science, one of the world’s top journals, which would go a long way toward securing her a tenure-track position. But Dr. Blanchett became pregnant and when she told Wendell the news, he fired her. Blanchett sought out Barbara Hought, the dean of arts & sciences and herself a chemist, to file a grievance and seek reinstatement. But Hought reminded Blanchett that postdocs were at-will employees who served at the pleasure of their supervisors. “Choices have consequences,” Hought said. Blanchett was out on the street: pregnant, without income or health insurance, career in tatters, years of work squandered.

Stories like this were common, but what happened next was not.

They say that Blanchett snapped. She slit her wrists, but her husband called the paramedics in time. Nobody knows what was going through Blanchett’s mind, but as soon as she left the hospital, using money that she surely didn’t have, she placed a full-page ad—ironically, in Science—in the form of an open letter to Wendell and Hought.

You doubt my devotion to science, it read, but I assure you my commitment is complete.

The letter listed steps she would take to prove it:

I will terminate my pregnancy immediately.

I will divorce my husband and move out of our home, ceasing all contact and pledging not to pursue other romantic relationships.

I will take up permanent residence in my lab, leaving only for hygienic, nutritional, or health purposes, or those related to the work of the lab.

I will sever all contact with my family.

I will cut all social connections with my friends and acquaintances and will not develop any new such relationships.

I will cease spending time on other activities and interests, devoting myself solely to maximizing my research productivity.

The letter was a bombshell. Some thought it a hoax, others definitive proof of mental illness. But Blanchett followed through on her steps and in the ensuing outcry was reinstated in her lab long enough to publish her research and earn an assistant professor position at another university.

She also attracted a following of female scientists who made similar pledges. The shaved heads appeared soon after, first for functional reasons—they made personal grooming easier—but ultimately as a proclamation of solidarity and identity. The tattoos followed, designed to mimic the cuts in Blanchett’s wrists. And so was born a new class of people adapted to institutional life: the university equivalent of the Aryan Brotherhood or the urki of the Gulag.

If this new phenomenon of women publicly forsaking their personal lives does not unequivocally illustrate how badly the system is broken, trumpeted the editor-in-chief of Science in a famous editorial several years later, I do not know what does. Nobel Laureates, university presidents, and federal agency heads made similar public statements. (In private, they were giddy at the Pythia’s productivity.) Over the following ten years, half a dozen committees of muckety-mucks assembled: they navel-gazed and proselytized, they expressed their “strong concern” and “deep commitment to systemic change,” they generated reams of damning data and shelf-feet of dense reports with recommendations totaling in the hundreds. But funds were too tight, institutions too competitive, globalization too real. No group ever managed, either through policy or cultural change, to develop a realistic career disincentive to joining the Pythia.

Sophia senses eyes on her and turns. Emma Davis, gripping a pipette in her latex gloves, is staring at her. Sophia feels ashamed again, this time to be caught in idle reverie. What’s the point of coming in so early, the critical voice asks, when you mope around and get nothing done?

“Your proposal is promising,” Emma says. Her expression is flat, her eyes unfathomable.

Sophia is caught surprised. “Th-thank you.”

Emma doesn’t move. The ghost of a smile—a kind one, Sophia thinks—forms on her lips. Emma hesitates before opening her mouth as if to say something more. Just as she does, a stopwatch in her pocket begins beeping. Whatever she’s left brewing on the bench is ready for the next step. Davis clicks it off and walks away.

I guess that’s what passes for a heartwarming conversation with a Pythia, the critical inner voice says. But the voice is weak; Sophia feels touched.

Back at her desk, she pulls up her ResearchCVBook profile to await the results from the foundation’s reviewers. It seems like everyone’s online now; the chatter of bleets and toots is like a party.

The first score pops up in her feed: a perfect 10.000 from KZ_PeerReviewer1.

Speaking of parties, Sophia imagines the one she’ll throw if she gets the grant…and with it, her tenure. She imagines Lutton coming down from the eighth floor to congratulate her, the smugness wiped off his face forever. Alexandru and Karolina will be there, both grinning, any lingering worries about forcible returns to Eastern Europe erased. Maybe Noah will fly in from Bangalore, or at least VidAppear for a while.

The second score pops up.

KZ_PeerReviewer2 Score: 10.000

There’ll be cake at the party, which they’ll hold in the departmental seminar/faculty meeting/conference/multi-purpose room in the basement. Noisemakers. Funny hats. Maybe even stupid games. Lighthearted stuff …the sort of stuff Sophia would have done for her kids’ birthday parties, if she’d had kids.

A third 10.000 arrives from the final peer reviewer. Only one more score to go, this one from the foundation itself.

What will her research uncover? Might it lead to new cancer treatments? To the alleviation of massive amounts of human pain and suffering? To prestige and success, and maybe even wealth, for Sophia? Even if not, she thinks, even if none of it pans out, this investigation will be a worthy way to spend the remainder of her career.

The last score arrives.

KZ_Program_Officer Score: 9.854

Comment: “interesting hypothesis, though we are concerned that the applicant’s prior decision to turn down an offer from Xu’an University may suggest less than full dedication to her career.”

Average score: 9.964

Score required for top vigintile/positive funding outcome: 9.968.

Funding outcome: NEGATIVE

The data autopopulate her ResearchCVBook profile and automatically re-toot to the world. Before Sophia can process what’s happened, the first sympathetic emoticons from colleagues appear in her feed. Noah bleets a wailing face with a tear rolling down one cheek and a cloud of steam escaping from its nonexistent ears. She wants to slap him for responding to the destruction of her career with a yellow smiley-face’s unhappy cousin, like she’d texted that she missed the bus.

It’s too fast, but just like that, it’s over.

She stands, needing to get away from the screen.

She should break the news to Karolina and Alexandru. She should try to negotiate with Myles Lutton. She should go home, pour a stiff drink, and climb into bed.

Instead, she walks—wobbly and jittery at first, then more certain—back between the lab benches, where she knows she’ll find Emma Davis, working away in the name of science.

Josh Trapani ([email protected]) is writing a novel about a young scientist who faces the same situation as Giorgina Blanchett, but makes a different choice. He has worked at the intersection of science and policy for nearly ten years.

Climate Redux: Welcome to the Anthropocene

There are few topics as politically and ideologically contentious as anthropogenic climate change and the possibility of responding by deploying geoengineering technologies. Despite, or because of, all the Sturm und Drang, however, the current discourse is both misdirected and unhelpfully superficial. It is misdirected in that it frames climate change as a problem that can be solved, either through policy or technological silver bullets, rather than a condition, inherent to a planet with seven billion people, which must be managed. It is superficial because although it may be the most visible concern right now, the real challenge is not climate change. The topic that truly deserves our attention is the Anthropocene, the new stage of human history characterized by the growing significance of human actions in the overall state of the planet. Focusing exclusively on climate change is equivalent to treating symptoms rather than attacking disease. The point is not that climate change should not be a concern or that its effects do not have to be managed. Rather, the sad irony is that, despite the best intentions of the participants, the climate change and geoengineering discussions have so far been a way to evade knowledge and responsibility, not to extend them.

In 1992, the United Nations (UN) Rio Earth Summit adopted the UN Framework Convention on Climate Change (UNFCCC), with the objective, stated in Article 2, of achieving “stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system.” The implementing treaty, the Kyoto Protocol, was adopted in 1997 and entered into force in February 2005. Since 1992, except for a brief dip in 2008-2009 when global economic activity took a sharp dive, emissions of the most important anthropogenic greenhouse gas, carbon dioxide (CO2), have steadily increased; anthropogenic emissions of methane, after a period of relative stability from around 1999 to 2006, are also climbing.

The increasingly obvious failure of the UNFCCC process, combined with growing social concern about global climate change, has led to increasing interest in geoengineering, which the UK Royal Society defines as “deliberate large-scale intervention in the Earth’s climate system, in order to moderate global warming.” Geoengineering technologies are further broken down into two categories. CO2 removal (CDR) technologies remove CO2 from the atmosphere through biological or industrial means. Solar radiation management (SRM) technologies reflect some of the incoming energy from the sun back into space before it has a chance to reach the Earth’s surface. Each of these technologies has a unique mix of potential costs and benefits. For example, one result of high ambient levels of CO2 in the atmosphere is increasing acidification of the oceans with potentially deleterious effects on marine life; CDR technologies would mitigate such effects, whereas SRM technologies would not.

No reputable scientist disputes the planetary greenhouse effect. Mars, with little atmosphere and therefore little atmospheric radiation absorption, is cold, whereas Venus, with a substantial atmosphere composed mainly of CO2, has a surface temperature of about 870 Fahrenheit. That water vapor, CO2, and methane all absorb energy at crucial wavelengths to contribute to increased atmospheric energy content is well established. Nonetheless, to observe that this domain is contentious is a gross understatement. The controversy is not really over whether the Earth is subject to a greenhouse effect, because it clearly is; moreover, human activity produces CO2 and methane that are known to increase the greenhouse effect. But there is disagreement over whether such human influences are meaningful given the complex dynamics involved and over how worried we should be about any resulting changes in temperature and other aspects of climate.

Technically, such questions could be approached objectively, with all parties agreeing on a set of factual predicates for subsequent policy debates. Even the most casual observer will, of course, recognize that this is not what has happened. The language used to characterize those perceived as less committed to immediate action to reduce emissions is notably unscientific: Boston Globe columnist Ellen Goodman wrote that “global warming deniers are now on a par with Holocaust deniers.” In 2011, the UK Energy and Climate Change Minister demanded immediate action on climate, saying that “[g]iving in to the forces of low ambition would be an act of climate appeasement,” and that “[t]his is our Munich moment,” referring to the 1938 Munich agreement that ceded Czechoslovakia to Hitler. James Hansen, a U.S. National Aeronautics and Space Administration climate scientist, wrote in a 2009 article that “coal is the single greatest threat to civilization and all life on our planet,” and that “The trains carrying coal to power plants are death trains. Coal-fired power plants are factories of death.” In turn, their opponents have coined the term “climate Nazis” because of their demands for heavy-handed government regulation. This is the rhetoric of morality. One can rationally discuss science and technology options, but one does not negotiate with evil.

Similar arguments swirl around geoengineering. These fall into two general categories. One involves the uncertainties and potentially significant risks of deploying such technologies. No amount of small-scale research will be sufficient to reliably predict all the results of this planetary experiment. The second category is the “moral hazard” argument: no geoengineering technology should be researched, developed, or deployed, because making it an option reduces pressure on individuals to reduce greenhouse gas emissions. Supporters of this position argue that major changes in lifestyle and perspective are very seldom achieved without significant forcing pressure. Opponents respond that a refusal to research geoengineering is an unethical form of social engineering.

Both the climate change and geoengineering debates are premised on a false dichotomy. The choice is not between the Kyoto Protocol and geoengineering. Rather, the choice is between a world view in which human activity has only isolated effects on the planet and an acceptance of a new reality in which human activity is unavoidably a major Earth system.

Anthropogenic climate change is merely a symptom of a far more profound emergent reality. Revisions to the failing Kyoto process or the premature deployment of a powerful technology fix are not what is needed. Rather, what is needed is an understanding that we have now crossed a threshold from a past where humans were but one species wandering the planet to a present where humans and their myriad activities, institutions, and aspirations now increasingly affect all planetary systems. Failure to accept that responsibility by burying one’s head in romantic ideologies or loud pontification at this point in human evolution is not just irresponsible, it is profoundly unethical. And it will have serious implications, for if climate change is the first test of humanity’s ability to operate rationally and ethically in the Anthropocene, we should try hard not to fail, and to learn from the experience. Neither of those outcomes appears probable on current trend.

Adjusting the focus

I am not saying that global climate change should not be addressed, both through mitigation and adaptation, and quite possibly through scaled introduction of geoengineering technologies. What I am saying is that even if we were to reduce the carbon content of the atmosphere to pre-industrialization levels—say, 280 ppm CO2—we wouldn’t be restoring the planet to its pre-industrial state. Complex adaptive systems do not have a default setting to which they can revert. We can’t de-Anthropocene the planet.

And this is the nub of the issue. The climate change phenomenon, and the debates swirling about it, are worrying, but not just because they may challenge the adaptive capability of individuals, societies, institutions, and other species. They are worrying because they illustrate, all too clearly, the inadequacy of our nascent efforts to respond to the challenges of the Anthropocene—the Age of Humans. If climate change and other similar issues, such as reductions in evolved biodiversity or perturbations in the nitrogen, hydrologic, and phosphorous cycles, are isolatable problems that can be addressed by the familiar methods of reductionism and environmental regulation, we are psychologically and institutionally prepared to respond appropriately. If, however, climate change is simply one of a number of coupled emergent behaviors generated by seven billion people with their vast array of institutions, cultures, and economic and technological systems, that approach is no longer viable. And the first step in adjusting to that reality is shifting to an adequate framing of the reality of the systems we’re dealing with.

The first challenge, then, is simply to recognize that we are, in fact, emerging into the Anthropocene. In this new era in the history of our planet, human activity is surfacing as one of the most important Earth systems, rivaling and stressing the natural systems that govern the planet’s habitability. To ensure a sustainable future as a planetary species, humanity needs to develop the capacity to manage these complex, interwoven systems. Developing this capacity requires that we adopt an integrated planetary perspective. Too often, we view humanity as an imposition on the planet. In this view, Earth can be restored to a pastoral golden age by reducing (ideally, removing) the human influence from nature. This perspective fundamentally misunderstands the Anthropocene as an event that can be reversed.

A more productive perspective is to view the Anthropocene as a natural transition resulting from a very recent innovation: the evolution of tool-using intelligence and the consequent rise of technological civilization. This innovation is as irreversible and disruptive to Earth’s systems as previous major evolutionary innovations, such as the evolution of land plants, the development of skeletons, the origin of multicellular organisms, and the invention of oxygen-producing photosynthesis. Like these prior milestones in the history of life on Earth, the genie of tool-using intelligence cannot be stuffed back into the evolutionary bottle. Evolution is never retrograde. Instead, we need to aim for pragmatic, sustainable design and management of a planetary ecosystem that includes the human system as an integral, permanent, and constantly evolving component—an intelligent part that can impact the planet thoughtfully, as well as thoughtlessly.

As the previous discussion has made clear, we are far from having the capacity, as a species, to be responsible designers and managers of our planetary ecosystem, despite the clear and present need. The good news is that our comprehension of the physical, chemical, and biological systems that go into making a habitable planet deepened dramatically in recent decades. Although there is much yet to learn, our knowledge is expanding at least as rapidly as our recognition of the environmental, energy, and resource challenges before us.

At the same time, the accelerating pace of technological evolution challenges our insight into the human system that drives the Anthropocene. Areas as diverse as nanotechnology, biotechnology, information and communication technology, robotics, and cognitive sciences are advancing in ways that are ever more complex, rapid, and difficult to predict, but that are converging in a way that makes humanity itself a design space. The redesign of the human as currently constituted is an increasingly probable scenario. These changes will not only accelerate human effects on Earth’s natural systems, but also pose significant and as-yet-unpredictable challenges to the social systems that modulate these effects. We do not yet have the capability as a species to anticipate and respond ethically, rationally, and responsibly to these coming challenges. That said, we can at least begin to develop some basic principles that would support more effective institutional and policy responses.

The correct answer is none of the above. The challenges of the Anthropocene are not “problems” with “solutions;” rather, they are conditions, often highly coupled to other conditions and systems that can at best be managed.

Be prepared. An important mechanism for managing Anthropogenic challenges is the conscious cultivation of technological, institutional, and social options—a toolkit for adapting rapidly to changes in Earth systems.

Practice makes perfect. Borrowing the techniques of defense and foreign policy strategists, use scenarios and games to expand institutional perception, thinking, and agility.

When in doubt, doubt. The complex adaptive systems that characterize the Anthropocene are inherently unpredictable; it follows that predictions regarding future paths and outcomes should always be regarded skeptically.

Diversity enables adaptability. The inherent unknowability of complex adaptive systems privileges pluralistic institutions and cultures.

Scale matters. Many Anthropogenic systems behave in a linear fashion at small scale but can become unpredictably non-linear at larger scales.

Stay in school. Because the Anthropocene is characterized by evolving conditions that will confront us with new ethical, social, and technological challenges, it demands continuous learning.

The conflictual, partisan, and superficial environment that has developed around the issue of anthropogenic climate change is unfortunate, not just because it is unproductive and ineffective. It has also served to mischaracterize and disguise the full magnitude and complexity of the challenge posed by the Anthropocene, an era in which return to any sort of fabled, golden, pastoral age is fantasy. What is needed now is not policy “solutions,” which for the most part will prove partial and inadequate, nor technological silver bullets, which are likely to be far more disruptive and costly than expected. Rather, what is needed is the courage to perceive and accept the world as it is today, and to appreciate the difficulty of responsibly managing it. That the planet is increasingly shaped by the activities and choices of one species cannot be denied; that we know how to do so consciously and ethically cannot be confidently asserted. That is the real challenge we face at the beginning of the Anthropocene.

Braden Allenby ([email protected]) is President’s Professor, Civil, Environmental, and Sustainable Engineering, and Lincoln Professor of Engineering and Ethics at Arizona State University.

A New Model for the American Research University

Headlines and pundits proclaiming a crisis in American higher education seem to proliferate on a daily basis. Accounts of skyrocketing sticker prices at our nation’s colleges and universities vie for attention with dire pronouncements about the value of a college degree in today’s challenging economy. There is a “crisis on campus” and the “education bubble is about to burst,” religions scholar Mark C. Taylor confidently informs us in his recent book, and according to sociologists Richard Arum and Josipa Roksa, America’s students are “academically adrift.” This apocalyptic genre has become so commonplace, with assaults coming from all quarters and in so many creative guises, that it would be superfluous to cobble together even a representative compilation. As just one more random, high profile sample, consider Peter Thiel, cofounder and former CEO of PayPal, whose Thiel Fellowships provide $100,000 grants on the condition that recipients drop out of college to pursue entrepreneurial endeavors. As Thiel reassures us in the New York Times, “Before long, spending four years in a lecture hall with a hangover will be revealed as an antiquated debt-fueled luxury good.” Cultural commentators and academics alike find it easy enough to represent higher education in various stages of catastrophic decline, but they have been less cognizant of the deeper phenomenon: the challenges that confront universities reflect a confluence of societal trends that threaten to undermine the egalitarian conception of higher education that has been integral to our national identity and success from the outset of the American republic.

A cover article in Forbes magazine asked: “Is Higher Education Still Worth It?” and concludes: “For many students, the answer is probably not—unless they are accomplished enough to be accepted by one of the schools ranked near the top of our annual list of America’s 650 Top Colleges.” This remarkably narrow perspective seems close to becoming consensus opinion. Yet the idea that higher education is only worth the investment for the rarified few admitted to one of our nation’s most selective institutions threatens to undermine the future of our collective quality of life, standard of living, and national economic competitiveness. In this article, we briefly describe one possible path forward and one full-scale, real-time experiment to move down this pathway as decisively as possible.

Although there are many types of colleges and universities, few critiques differentiate among the plurality of institutional types that constitute a heterogeneous academic marketplace. There are roughly 5,000 institutions of higher education in the United States, of which the Carnegie Foundation for the Advancement of Teaching categorizes only 108, both public and private, as major research universities. Approximately 100 additional universities with less extensive research portfolios comprise a second research-grade cohort. This aggregation of universities is held in considerable worldwide esteem. American institutions consistently occupy 17 of the top 20 slots in the authoritative ranking of world-class universities conducted by the Institute of Higher Education at Shanghai Jiao Tong University, and 14 of the top 20 in the Times Higher Education World University Rankings. The number of international students seeking enrollment at American colleges and universities attests to the perception that these institutions offer opportunities found nowhere else.

The top 100 major research universities constitute the academic gold standard in American higher education. Apart from their role in the formation of successive generations of our nation’s scholars, scientists, and leaders in every sphere of endeavor, these institutions serve as the primary source of scientific discovery and technological innovation that fosters economic growth and social development across the global knowledge economy. But just as important are scholarly and creative endeavors in the arts, humanities, and social and behavioral sciences that too often escape notice, precisely because their influence already so fully informs our intellectual culture, as Columbia University provost emeritus Jonathan Cole points out in his indispensable volume, The Great American University.

There is no single model for the American research university—a set of institutions that includes public and private variants that range considerably in scale, from small private institutions, like Dartmouth and Caltech, to large public universities, like Ohio State. But for our purposes they bear a striking family resemblance that justifies our reference to the gold standard model. Yet despite their accomplishments, their institutional evolution since the 19th century has been only incremental. To an alarming extent, the American research university is captive to a set of institutional constraints that no longer aligns with the changing needs of our society. Despite the critical niche that research universities occupy in the knowledge economy, their preponderant commitment to discovery and innovation, carried out largely in isolation from the socioeconomic challenges faced by most Americans, will render these institutions increasingly incapable of contributing decisively to the collective good.

The institutional model that we delineate in our new book, Designing the New American University (Johns Hopkins University Press, 2015), is intended to provide an alternative to the highly successful major research universities, and is only one among many possible variants on this institutional type. Thus, we use the somewhat infelicitous term “academic platform” to suggest that there are many unexplored and unexploited institutional models for higher education—especially those that can provide an excellent education while advancing knowledge and innovation at the scale and timeframe necessary to progress toward desired social and economic outcomes. Our model thus combines three foundational design components: 1) an academic platform committed to discovery and knowledge production, as with the standard model, linking pedagogy with research; 2) broad accessibility to students from highly diverse demographic and socioeconomic backgrounds; and 3) through its breadth of activities and functions, an institutional commitment to maximizing societal impact commensurate with the scale of enrollment demand and the needs of our nation. The model, that is, embodies a reconceptualization of the American research university as a complex and adaptive comprehensive knowledge enterprise committed to discovery, creativity, and innovation, accessible to the demographically broadest possible student body, socioeconomically as well as intellectually, and directly responsive to the needs of the nation and society more broadly. The objective of the new model is to produce not only knowledge and innovation, but also students who are adaptive master-learners, empowered to integrate a broad array of interrelated disciplines and negotiate over their lifetimes the changing workforce demands and shifts in the knowledge economy driven by continual innovation.

Accessibility to research-grade academic institutions

The confluence of economic, political, and social currents that propelled America to global preeminence in the 20th century engendered a social compact that produced world-leading levels of educational attainment. As economists Claudia Goldin and Lawrence Katz assess in The Race Between Education and Technology, public sector investment in higher education during the first three quarters of the 20th century served for millions as a springboard to economic mobility, and more broadly as the foundation of an increasingly widely shared prosperity built on the rapidly rising productivity made possible by an educated and innovative society. During the three decades following World War II, a period of expansion for colleges and universities that Louis Menand has termed the “Golden Age” of American higher education, growth in undergraduate enrollments, including community colleges, increased fivefold and nearly 900 percent in graduate schools.

Yet despite the success of this model, public investment in higher education has progressively declined ever since. In a 2014 working paper for the National Bureau of Economic Research, Robert J. Gordon finds that between 2001 and 2012, funding for higher education from states and municipalities fell by one-third when adjusted for inflation. Since 1985, state funding for the University of Colorado, for example, has declined from 37 percent to 9 percent of the institutional budget. Research by Phillip Oliff and colleagues at the Center on Budget and Policy Priorities (CBPR) found that state appropriations for higher education declined 28 percent between fiscal years 2008 and 2013: “Eleven states have cut funding by more than one-third per student, and two states—Arizona and New Hampshire—have cut their higher education spending per student in half.” A 2014 CBPR update found that during the past year funding has been restored by an average of 7.2 percent, but state spending still remains 23 percent below prerecession levels: “Per student spending in Arizona, Louisiana, and South Carolina is down by more than 40 percent since the start of the recession.”

Such disinvestment—often concentrated in places most in need of precisely the opposite—is just one of the many factors stemming the momentum of increased accessibility to our nation’s colleges and universities that marked the course of previous decades. As a result, many of the students who would most benefit from this most obvious avenue of upward mobility—those whom we broadly categorize as “socioeconomically disadvantaged” or “historically underrepresented”—cannot gain admission to a research-grade university. The decline comes at a time when more and more Americans of all ages, socioeconomic backgrounds, levels of academic preparation, and types of intelligence and creativity seek enrollment, overwhelming a set of institutions built to accommodate the needs of our country prior to the Second World War, when the population was less than half its present number, and only slightly more than one percent of Americans enrolled in college. The National Center for Education Statistics reports that over the past quarter century, total enrollment in institutions of higher education has grown from under 13 million to more than 21 million, both undergraduate and graduate. Roughly three-fourths of high school graduates now enroll in some form of college, including community colleges and for-profit institutions—a fourfold increase since midcentury. By one estimate, community colleges enroll 45 percent of all U.S. undergraduates, and for-profit schools enroll 10 percent. Although such burgeoning enrollments would suggest progress in meeting demand, degree completion rates have fallen and the outcomes of attendance are drastically uneven, varying according to institutional type.

As nations worldwide invest strategically to educate broader segments of their citizenry for the knowledge economy, America’s educational infrastructure remains unable to accommodate projected enrollment demands, particularly at the level of research-intensive universities. America’s leading institutions have become increasingly exclusive and define—indeed, precisely quantify—their excellence through admissions practices based on the exclusion of the majority of applicants. Prestige is thus attained through the maintenance of scarcity. But if education is a public good, then this meritocratic pretense is a defensive posture and an abdication of implicit responsibility. Although our leading research universities, both public and private, consistently dominate global rankings, our success in establishing world-class excellence in a relative handful of elite institutions does little to ensure the broad distribution of the benefits of educational attainment, nor does it sufficiently advance the innovation that contributes to our continued national competitiveness, especially if we stop to consider the disproportionately few students fortunate enough to be admitted to these top schools. When Princeton historian Anthony Grafton referred to the “little group of traditional liberal arts colleges, all of whose students could fit in the football stadium of a single Big Ten school” in the New York Review of Books, he was not engaging in hyperbole. IPEDS (Integrated Postsecondary Education Data System) data show that the top 50 liberal arts colleges (as ranked by U.S. News & World Report for academic year 2012–2013) collectively enrolled 95,496 undergraduates. Michigan Stadium in Ann Arbor seats roughly 110,000. The eight traditional Ivies enroll 65,677. Yale Bowl holds 61,446. These 50 top liberal arts schools, plus the Ivies, make up less than one percent of the total U.S. undergraduate population of 18.2 million students.

Perhaps this comparison unfairly circumscribes the size of the elite student body. If we take institutional membership in the Association of American Universities (AAU), which represents 60 leading research universities in the United States, both public and private, as proxy for academic quality, available seats for undergraduates climbs to 1.1 million. AAU reports that in 2011 its public member institutions enrolled 918,221, whereas AAU privates enrolled 211,500. This brings us to approximately 6 percent of college students in the United States.

Still too narrow a gauge? Adding the rest of the first-tier research universities to the 60 AAU schools gets us to a little more than 2 million, or roughly 11 percent of American students. And unlike schools devoted primarily to teaching, these institutions offer opportunities found nowhere else. As the late Charles M. Vest, then president of the Massachusetts Institute of Technology (MIT), observed in a 1994 letter to parents, the distinctive character of a research-grade university permits undergraduates to participate in research with scientists and scholars working at the frontiers of knowledge: “Our society will ask much more of these students—and they will ask more of themselves—than just to know what others have accomplished. If they are going to help us expand our knowledge and solve our problems, they are going to have to know how to research, to analyze, to synthesize, and to communicate. They must learn how to gather data, to develop hypotheses, to test and refine them, or throw them out when necessary and start over.”

The gold standard in American higher education represents an immensely successful institutional platform that invariably combines world-class teaching and research with modest levels of enrollment. During the current academic year, for example, undergraduate enrollment in Harvard College numbers roughly 6,700 and at its 363rd commencement in May 2014, the university awarded 1,662 baccalaureate degrees. In March 2014, Harvard College offered admission to 2,023 prospective students—5.9 percent of the pool of 34,295 applicants. Of these, we estimate that approximately 1,600 were likely to enroll, based on the pattern of yields obtained during the preceding three academic years. Harvard does maintain one of the larger graduate and professional student enrollments among the Ivies, however, which exceeds twice its undergraduate population and approaches the number of graduate students attending the University of Michigan.

Harvard’s undergraduate enrollment levels are generally typical of the platform type. In the fall term of 2013, MIT enrolled 4,528 undergraduate and 6,773 graduate students. A three-to-one student-faculty ratio at Caltech comes by dint of enrollment of 997 undergraduates during the academic year 2012–2013, along with 1,253 graduate students. Bard College enrolls roughly 2,000 undergraduates; Williams College about the same number; Bowdoin roughly 1,750; Swarthmore approximately 1,500.

Enrollments in public colleges and universities are normally far higher, of course. The entire student body of Harvard College corresponds roughly in number to the total of undergraduate degrees conferred yearly at the University of California (UC), Berkeley, or the number of undergraduates enrolled in the School of Engineering at the University of Texas at Austin. Yet, even these public institutions have not scaled up their enrollment capacities commensurate either to the requirements of the workforce or levels of population growth.

And how could they? The entrenchment of the present model is the very measure of its success. Because the prestige of these schools remains unrivaled, there is little incentive for them to seek change. As a consequence, these institutions have become so highly selective that the vast majority of academically qualified applicants are routinely excluded. According to one estimate based on IPEDS data, the number of bachelor’s degrees awarded by the eight institutions of the Ivy League during the academic year 2012–2013 totaled 15,541, whereas the top 50 liberal arts colleges awarded 23,672. In the same academic year, the Ivies rejected 222,279 applicants and the liberal arts colleges turned away 190,954.

This pattern of exclusion is consistent with the trend among leading public universities, which continue to raise standards even while enrollment demand increases. The ratio of California resident freshman applicants to students admitted at UC Berkeley from 1975 to 1995, for example, declined from 77 percent to 39 percent, according to John Aubrey Douglass. Institutional data show that between the fall semesters of 1989 and 2013, the ratio of admissions at Berkeley declined from 40 percent to 16.35 percent. The comparable figures for the University of California, Los Angeles (UCLA) show a decline from 46.5 percent to 17.6 percent. The actual numbers present the scenario even more starkly. Of 43,255 resident applicants to Berkeley in the fall semester of 2013, only 7,073 were admitted, which means that 36,182 were turned away. At UCLA, 55,079 applied, but only 9,741 were admitted, which means that 44,338 were excluded. Although the UC system as a whole accepted 76.6 percent of resident freshmen in the fall semester of 1989, by 2013 the acceptance rate had declined to 63 percent. If leading research universities deem it appropriate to maintain limited enrollments while excluding the majority of applicants, other research-grade academic platforms must emerge that offer accessibility to substantially greater numbers of students—especially among public research universities, which typically serve more first-generation and socioeconomically disadvantaged students.

The implications of lack of accessibility

Such limited accessibility to research-grade institutions is out of proportion with workforce projections that indicate a shortfall by 2018 of three million educated workers. Anthony Carnevale, director of the Georgetown University Center on Education and the Workforce, and colleagues estimate that degree production would have to increase by roughly 10 percent each year to prevent that shortfall. For our nation to achieve the ambitious objectives for educational attainment specified by President Obama in his first address to a joint session of Congress in February 2009—the president envisioned an America that by the end of the present decade would again boast the highest proportion of college graduates in the world—our colleges and universities would have to produce an additional 8.2 million graduates by 2020. Another study led by Carnevale and Stephen J. Rose underscored the interrelationship between an “undereducated” society and increasing income inequality: “The undersupply of postsecondary-educated workers has led to two distinct problems: a problem of efficiency and a problem of equity.” At issue is the loss in productivity that comes with a workforce lacking advanced skills. At the same time, “scarcity has driven up the cost of postsecondary talent precipitously, exacerbating inequality.” The upshot, according to Carnevale, is that “to correct our undersupply and meet our efficiency and equity goals for the economy and for our society, we will need to add an additional 20 million postsecondary-educated workers to the economy by 2025.”

Whatever specific numbers one chooses to adopt, there seems little disagreement that the demands of both equity and prosperity entail a capacity to create millions of additional graduates capable of both catalyzing and benefiting from the knowledge economy during the next several decades. But when academic culture assumes that enrollment growth must come at the expense of reputation and competitive standing, few are the institutions willing to pursue strategies to produce the additional graduates our nation needs. Indeed, scarcity is the brand that our elite universities are selling. The idea that these institutions could exercise their potential to produce millions of highly qualified, workforce-ready critical thinkers threatens the current business model.

Thus, in the Ivies and, more recently, the so-called public Ivies—the set of “flagship” public universities that rival private institutional peers in their pursuit of prestige—admissions policies are predicated on exclusion. The announcement by Stanford University in April 2014 that only 5 percent of applicants had been accepted epitomizes the increasing selectivity of top private universities. But leading public universities are becoming increasingly discerning as well, and the broad access to a quality education that could once be taken for granted is now flatly denied to the majority of qualified applicants. In the mid-20th century, high school students from middle-class families who brought home respectable grades could reasonably expect to be admitted to the leading public universities of their respective states. During the 1950s and 1960s, for example, California high school graduates who completed a set of required courses and attained a cumulative 3.0 grade point average qualified for admission to the University of California. The admissions policies of our top-tier institutions may appear meritocratic, but a significant proportion of alumni who graduated in the 1970s or 1980s—many of whom no doubt attribute their professional success in large measure to the caliber of their education—would be summarily turned away under current protocols. As literary scholar Christopher Newfield aptly put it in a 2010 article: “The entrenched practices, the deep culture, the lived ideology, the life-world of American higher education all point toward defining excellence through selectivity, and would seek to improve any university regardless of mission by tightening admissions standards.”

But large-scale enrollment can go hand-in-hand with academic excellence. The University of Toronto, for example, the largest major research university in Canada and a public AAU member institution, enrolls 67,128 undergraduates and 15,884 graduate students at three urban campuses and reports research expenditures exceeding $1.2 billion annually. The institution consistently ranks topmost among Canadian universities, 28th globally in the Academic Ranking of World Universities, and 20th globally in the most recent Times Higher Education World University Report. But whether by design or default, other leading research-grade universities have not similarly scaled up enrollment capacities commensurate with demand or proportionate to the growth of the population. Both the elite private and public research universities continue instead to raise thresholds for admission.

Nearly all leading colleges and universities offer opportunities to students of exceptional academic ability from underrepresented and socioeconomically disadvantaged backgrounds. It is always possible to recruit academically gifted students from across the spectrum of socioeconomic backgrounds. This way, a measure of diversity can be achieved without actually drawing more deeply from the broader talent pool of socioeconomically and ethnically diverse populations. As Robert Gordon observes, “Presidents of Ivy League colleges and other elite schools point to the lavish subsidies they provide as tuition discounts for low- and middle-income students, but this leaves behind the vast majority of American college students who are not lucky or smart enough to attend these elite institutions.” But intelligence is distributed throughout the population, and for many it manifests through skills, abilities, and experiences that current admissions protocols disregard. Admissions policies that merely skim from the conventionally defined top shortchange countless gifted and creative individuals. At issue is not the education of students from the top 5 percent of their high school classes, which represents business as usual at gold standard institutions, but rather the imperative to educate the top 25 percent to very high levels of achievement.

Economist and former Princeton president William G. Bowen and colleagues Martin Kurzweil and Eugene Tobin have framed this dilemma as a contest between “equity and excellence in American higher education.” In their acclaimed 2005 book of that name, they describe a “simmering debate over whether it is better to educate a small number of people to a very high standard or to extend educational opportunities much more broadly—even if this means accepting a somewhat lower standard of performance and, in general, spreading resources more thinly.” Equity and excellence are complementary, the authors observe, because talent is distributed throughout the socioeconomic spectrum; national competitiveness in educational attainment depends on extending opportunities to sufficient numbers from all demographic strata; diversity enhances the quality of the educational experience; and the success of our democracy depends on an educated citizenry. “In its most shallow construction, this linkage [between equity and excellence] takes the form of a direct, zero-sum tradeoff between the two ideals.” To move beyond this justification for the exclusionary business model, “society at large can build the educational scale that it requires only if its institutions of higher education tap every pool of talent.”

The New American University model attempts to transcend this self-aggrandizing zero-sum trade-off. The model brooks no compromise in the quality of knowledge production and insists that equity is attained only when all academically qualified students are offered an opportunity for access regardless of socioeconomic background. Whereas other assessments underscore focus on the socioeconomically disadvantaged and historically underrepresented, the New American University model embraces equally students from all demographic strata capable of accomplishment in a research-grade milieu, including the gifted and creative students who do not conform to a standard academic profile.

A prototype for the New American University model

Accessibility is by no means the sole dimension to the New American University model, nor the exclusive focus of our book. But inasmuch as access to knowledge underpins every societal objective in a pluralistic democracy, accessibility is at the core of the reconceptualization of Arizona State University (ASU), which represents the foundational prototype for the New American University. In the course of a decade, ASU reconstituted its curriculum, organization, and operations through a deliberate design process undertaken to build an institution committed to the pursuit of discovery and knowledge production, broad socioeconomic inclusiveness, and maximization of societal impact. The academic community has been consciously engaged in an effort to accelerate a process of institutional evolution that might otherwise have proceeded, at best, only incrementally, or possibly in the face of crisis. Initiated in part in response to the unprecedented shift in the regional demographic profile in one of the fastest-growing states in the nation, the design process constitutes an experiment at full institutional scale and in real time. We offer our account of the reconceptualization as a case study in innovation in American higher education.

To revive the social compact implicit in American public higher education, ASU revived the intentions and aspirations of the historical public research university model, which sought to provide broad accessibility as well as engagement with society. ASU resolved to expand enrollment capacity, promote diversity, and offer accessibility to world-class research and scholarship to a diverse and heterogeneous student body that includes a significant proportion of students from socioeconomically diverse and underrepresented backgrounds, including a preponderant share of first-generation college applicants. ASU thus implemented admissions policies similar to those of the University of California in the 1950s and 1960s. ASU’s attempt to realize an academic platform that combines world-class teaching and research with broad accessibility may be likened to coupling the research-intensive milieu of the University of California system with the accessibility offered by the Cal State system.

How is the experiment doing? Soaring enrollment growth has been accompanied by unprecedented increases in degree production, freshman persistence, minority enrollment, growth in research infrastructure and sponsored expenditures, academic accomplishment both for scholars and students, and the transdisciplinary reconfiguration of academic organizations around broad societal challenges rather than historically entrenched disciplines. Enrollment has risen from 55,491 undergraduate, graduate, and professional students in the fall of 2002 to 83,301 in the fall of 2014—roughly a 50 percent increase. Degree production has increased even more sharply—more than 67 percent. ASU awarded 19,761 degrees in the academic year 2013–2014, including 5,380 graduate and professional degrees, up from 11,803 during ] 2002–2003. The university has conferred more than 100,000 degrees during the past six academic years. Minority enrollment from the fall of 2002 through the fall of 2014 increased 146 percent, currently constituting 34 percent of the total student population.

Leading scholars are increasingly attracted to and inspired by our academic community. Our faculty roster includes recipients of prestigious national and international honors, including three Nobel laureates and more memberships in the National Academies than during the entire history of the institution. And as a consequence of an ambitious expansion of the research enterprise, research-related expenditures over the period fiscal year (FY)2002 to FY2014 have grown by a factor of 3.5—without significant growth in the size of the faculty—reaching a record $425 million in FY 2014, up from $123 million in FY 2002. This, without a medical school, and during a period of declining federal research and development (R&D) investment, no less. Among U.S. universities with research portfolios exceeding $100 million in expenditures, ASU has hosted one of the fastest-growing research enterprises over the period FY2007 to FY2012, according to data from the National Science Foundation. ASU has outperformed peer institutions in this context, with total research expenditures growing 62 percent from FY2007 to FY2012, more than 2.5 times the average growth rate of its peer institutions.

We want to emphasize the significant simultaneous progress made by ASU on measures that are supposed to be contradictory. Increases in degree production, socioeconomic diversity, minority enrollment, and freshman persistence; improvements in academic achievement and faculty accomplishment and diversity; and the expansion of the research enterprise have been realized in a university committed to offering admission to all academically qualified Arizona residents regardless of financial need, and to maintaining a student body representative of the socioeconomic diversity of America. Improvement of graduation rates or freshman persistence could readily be achieved by limiting admissions to ever-more handpicked selections of graduating high school seniors. ASU has done it by offering admission to a widening range of academically qualified students of varied and diverse backgrounds to whom admission to a world-class research university would otherwise be denied. And it has done so in a period of both robust enrollment growth and historic disinvestment in public higher education. The New American University model defies the conventional wisdom that correlates excellence with exclusivity, which generally means the exclusion of the majority of qualified applicants.

Toward new models for the American research university

Unable or unwilling to accommodate our nation’s need to deliver superior higher education to millions of new students, most major research universities, both public and private, appear content to maintain the status quo and seek prestige through ever-increasing exclusivity. But success in maintaining excellence in a small number of elite institutions does little to advance our society or ensure continued national competitiveness. The issue of broad accessibility to research-grade academic platforms is far more urgent than policymakers realize, even those on the national stage charged with advancing higher education policy. Our national discussion on higher education must not simply focus on the production of more college graduates. Mere access for greater numbers to rudimentary forms of instruction will not deliver desired societal outcomes—on this point, Peter Thiel is exactly right. The imperative is to ensure that far more students —an order of magnitude more—have access to research-grade academic platforms that deliver advanced skills commensurate with the demands of the knowledge economy.

Our nation must begin in earnest to build a higher education infrastructure proportional to the task of educating to competitive levels of achievement not only the conventionally measured top 5 percent but the most capable 25 percent of academically qualified students representative of the socioeconomic and intellectual diversity of our society. The demand for advanced teaching and research, and for the production of new ideas, products, and processes that are its outputs, is at a fever pitch that far exceeds the current supply. Appropriate historical models from which to derive a course of action do not exist. Entrenched assumptions and rigid social constructs hinder adaptability, even though inherent design limitations hamper rapid change in response to real-time demand. Risk-taking in the academic sector is thus essential if our society is to thrive. As de facto national policy, excluding the majority of academically qualified students from the excellence of a research-grade university education is counterproductive and ethically unacceptable. To accelerate the evolution of our research universities, we must develop new models that insist upon and leverage the complementarities and synergies between discovery and accessibility.

Machine Smart

The subject of intelligent machines that decide that they don’t have much use for us has haunted our species at least since golems first were mentioned in the Talmud. And more recently, the issue of superintelligence has been worked over by science fiction authors from Isaac Asimov to Vernor Vinge and beyond. We’ve thought about this a lot.

Now philosophers have their turn. Oxford University philosopher Nick Bostrom’s book Superintelligence gives the subject a thorough treatment. His conclusion? We better be damn careful what kind of intelligent machines we build.

Bostrom’s erudition bursts from every page. He has a background in physics, computational neuroscience, and mathematical logic, as well as philosophy. He uses all of these disciplines, and more, to advance his argument, which has four main parts.

Part 1: Machine intelligence is feasible. Bostrom reviews the current approaches to computer-based intelligence and divides them roughly into brain emulation and pure artificial intelligence (AI) approaches, with hybrids and mongrels in between.

Brain emulation intelligence works by completely emulating a human brain—down to the level of neurons and dendrites and cortical columns—in such detail that the person instantiated in that brain comes to life in the artificial medium of computer hardware and software.

Pure AI takes a different course, attempting to build in software a pure artifact that acts intelligently but not in any way that traces a heritage to our native wetware (other than the important detail that we designed the artifact in the first place.)

Bostrom maintains that both approaches could feasibly lead to AIs, although he believes that the two approaches have different strengths and weaknesses, and may lead to different future scenarios. Because we are presumably just “running mind software” on a different hardware platform, Bostrom believes that brain emulation AIs are more likely to “be like us,” whatever that means, but pure AIs, because all of the design elements are explicit, may be easier for our minds to comprehend and predict. He concludes that brain-emulation AIs are likely to come on the scene sooner, but that either form may arrive by mid-century.

Part 2: Bostrom then argues that once an AI exists, it may (and likely will) rapidly improve its own intelligence. By “rapidly,” he means within seconds or hours or days, not months or years. He believes that there may be no limit to this self-improvement, to the point where an AI develops what Bostrom calls “decisive strategic advantage” and is able to neuter potential alternatives or adversaries and, rather rapidly, consolidate its power as what he calls a “singleton.” Such a singleton would, in effect, control the future of humanity, what Bostrom calls its “cosmic endowment.”

Part 3: There is no special reason to believe that a singleton’s intentions would be benign. Bostrom discusses at length what might be the “final purposes” (his term; we might call them “ultimate goals” or “life purpose”) of such an all-powerful superintelligence, and how we might influence those purposes. This line of inquiry, which occupies most of the book, is a hash of game theory considerations and speculations about the nature of an AI and its capabilities. How might we, for example, prevent a singleton AI from converting the entire observable universe into paperclips if that were its final purpose?

Part 4: In the final chapters, Bostrom discusses what is to be done. How should we act in the face of what he considers the practical certainty that a superintelligence will be developed—if not within decades, perhaps within a century or two—whose motives might not be benign and whose ability to act on its motives might be unstoppable?

He advises us to, in effect, form a League of Extraordinary Humans whose purpose is to systematically and strategically discuss the emergence of a superintelligence. Not to utterly make fun of Bostrom’s approach, we might call this an Iron Rice Bowl (the Chinese term for occupation-for-life) for Philosophers.

What are we to make of Bostrom’s case?

In the first place, it is a serious argument. If we might in the relatively near future invent our cosmic replacement, then we are required, in the name of humanity’s cosmic endowment (which Bostrom calculates to comprise some 1058 real or virtual future lives), to give the matter some thought. And Bostrom is quite correct that this kind of problem might benefit from long study. But what are our chances of affecting the outcome?

The core problem is that the leap between today’s “intelligent” software and a superintelligence is unknown, and our temptation is to mystify it. Whether we are building brain emulations or pure AIs, we don’t understand what would make them “come to life” as intelligent beings, let alone superintelligent.

“Machine learning” software today uses a statistical model of a subject area to “master” it. Mastering consists of changing the weights of the various elements in the model in response to a set of training instances (situations where human trainers grade the instances: “yes, this is credit card fraud,” “no, this is not a valid English sentence,” etc.). Clear enough, but it just doesn’t seem very much like what our minds do.

And the path from this kind of “learning” (it is an anthropomorphism even to call it learning) to what “human-intelligent” agents do is completely unclear.

It might require nothing but simple scale. A small “machine learning” system may be subintelligent, and at some size, if we had enough computing power and enough elements in the model and enough training instances and enough support, intelligence might “emerge.”

This has certainly been the mantra of AI for some decades, and it may have been what technophiles hoped for when IBM’s Watson software beat two Jeopardy champions a couple of years back.

Sadly, Watson has not gone on to master, on its own or even with expert human help, any general corpus of knowledge. At a Watson showcase event last year, the demo apps were all mired in the swamp of endless training and re-training that I recall from my AI days in the ‘80’s. There was no indication that unleashing Watson on different domains and at different scales was going to lead to general intelligence, although one is free to hope.

Another path to general intelligence, as some Husserlians, such as Hubert Dreyfus or other more anthropologically-inclined researchers think, may involve human feelings, purposes, or drives. If the AI wanted something badly enough (not to be shut off, for example), the argument goes, then it would learn from its “experiences” and get smarter. Combine “desires” like this with natural selection at scale via a genetic-selection or evolutionary approach, and you might gradually enhance the intelligence of primitive agents. With machine speeds, this could happen quickly.

The problem with this approach has been coming up with a mechanical definition of “feelings,” “purposes,” or “drives.” We can write some software that is aimed at doing something, but it is missing something of what we associate with a drive: urgency, existential angst, whatever. Maybe we are confusing the qualia of purpose with the essence of it, and maybe a human-infused purpose can launch software on the road to agency. But at some point it has to have “its own” purposes, whatever that means.

A third approach has been to insist that there is something implicit in our brains that is unique, whether we call this uniqueness “embodied-ness” (with Dreyfus) or “bearing human motivational ancestry” (with Bostrom). Is there something implicit in the organization of our brains that renders us intelligent? If so, then emulating a brain should supply it, unless an emulated brain is like a silk flower. As Dreyfus remarked at one point, we don’t think that the software simulation of a thunderstorm should get us wet, do we? Why should the software emulation of a brain embody whatever makes us intelligent?

This “missing link” between AI software today and general intelligence tomorrow wouldn’t be so important if it weren’t at the heart of Bostrom’s argument about how to control emerging AIs. If intelligence emerges from scale or from endogenous machine “drives” or for embodied-ness, how can we hope to put a governor on the motives of machine intelligences? They would toss our flimsy moral strictures aside as easily as adult humans toss away Santa Claus.

But talking about children does give us some suggestions about an approach to making AIs moral. Sigmund Freud believed that children form a superego at an age when they are “impressionable” but not yet adult in their reasoning. A superego, in his theory, is a moral mechanism that functions imperfectly (filled with demons and fascists as well as avatars of light and Christ figures) but is good enough to guide most adults to a reasonable course of moral behavior. Maybe we can fashion a superego for our young AIs and give them enough guidance to allow them to muddle through when they reach adulthood without turning the entire universe into paperclips or destroying us so we don’t ask them tough questions.

That is Bostrom’s great hope, that we can issue a suitable instruction to emerging AIs (something along the lines of “do the best thing we mean for you to do, even if we can’t say it precisely”) that will constrain their range of possibilities when they become fully superintelligent. All of us would benefit.