Chuck Vest had the uncanny ability to make me feel smarter than I am. Although he undoubtedly knew more and had thought more deeply about any topic that I discussed with him, he always listened as if he were the acolyte and not the sage. He asked such perceptive questions and suggested such insightful implications that I would be convinced, at least for the moment, that I had released a flood of wisdom. My inchoate hunches, sloppy analogies, and gaps in logic would somehow be transformed into a coherent and compelling analysis. He would thank me for helping him understand the topic more clearly, and for the next day or two I would confidently spout opinions under the delusion that I was Chuck Vest’s policy guru.
Eventually my colleague’s blank stares and rolled eyes would bring me back to reality, and I had to admit that it wasn’t that they weren’t savvy enough to value my finely honed mind. Before long I would start hungering for another Chuck Vest fix. Even a brief interchange at the salad bar or in the elevator would get me high for a while. I would go to meetings where he was speaking hoping that he would say something that with sufficient effort I could trace back though six degrees of permutation to something I had said to him.
I am sure that I am not alone in this experience. And it’s not just us lowly Walter Mittys. A long line of presidents, cabinet secretaries, congressional committee chairs, and corporate CEOs lined up to have Chuck on their blue ribbon advisory panels. At some point I learned to look for Chuck’s name on the committee roster before deciding whether a report was worth reading.
Those of us who toil behind the scenes on National Research Council studies are not immune from twinges of spotlight envy. “I mean, I wrote the goddam report, why am I not the one appearing on the News Hour. I know this report better than any of the committee members and could explain it more cogently.” Unless Chuck was on the committee. Then we would willingly step aside, because without departing from the shared consensus, Chuck would transmute our pedestrian insights and turgid prose into eloquent gems of precision.
Well, Chuck is gone, and his absence will be felt from the lowliest policy dweeb to the U.S. president. We’ll be forced to untangle our own random thoughts, craft our own pithy summations, and earn the respect that Chuck granted us so generously. We can only hope to achieve half the clarity that he mastered and to convey it with half the grace and humility that he displayed.
The Zombie Enlightenment and Its Discontents
Political economy was the original development theory. In his classic The Wealth of Nations, published in 1776, Adam Smith proposed that people are most productive—both in terms of exercising their full capacities and benefiting society more generally—if their labour is rationally organized and not simply allowed to follow default hereditary paths, which in Smith’s day were largely protected by the law. Thus, if my father was a carpenter, I would be entitled to become one as well, regardless of my talent, disposition, etc. In effect, Smith was calling for a more proactive state whose functions went beyond simply keeping the peace. The state would intervene in people’s lives because “normal” was no longer presumed to be good enough. Those involved in the theory and practice of development aid still resonate to these sentiments.
But Smith’s idea of “state intervention” was not ours—in fact, it was almost the exact opposite. If the state intervenes to ensure that people are employed or otherwise categorised according to merit rather than entitlement, we presume that the state will, for example, provide for some education and administer some examinations. In contrast, Smith was much more liberal, if not “neoliberal.” He believed that creating markets where none had previously existed would smarten up humanity, as people are forced to make decisions about things that in the past would have been decided for them, if only by virtue of lack of choice. Thus, Smith was the great enemy of hereditarily protected trades whereby one would have to be born of a carpenter to become a carpenter. Instead he believed that anyone should be allowed to try their hand at a trade and potential consumers be left to decide the outcome. Caveat emptor!
Underwriting Smith’s liberalism was a fundamental faith that left to their own devices people can sort themselves out. In this respect, he was very much a child of the “Age of Reason.” Aspiring carpenters who fail to find enough customers will either try to cater to the market better or shift to a new trade. But make no mistake: For Smith the state and the market do not counterbalance but mutually promote each other. Today’s ideas of “state failure” and “market failure” (each requiring the assistance of the other) were not part of his vocabulary. A strong state is needed for markets to thrive, so Smith thought, if only so that hereditary privilege is not simply replaced by upstart oligopolies that can turn initial market success into a perpetual advantage. This is one of several of Smith’s lessons that Jeffrey Sachs, development economist and activist extraordinaire, never seemed to have learned, despite sharing most of Smith’s guiding intuitions.
The Sachs effect
Sachs has been the world’s most famous development economist for the past quarter-century. His stellar CV includes having been the youngest tenured professor at Harvard and head of the United Nations Millennium Project to eliminate global poverty. He was recently nominated by a coalition of developing world countries to run the World Bank, and is perennially cast (at least by the sort of people attracted to Ralph Nader) as a future third-party US presidential candidate. From the start of his career, Sachs has been well placed to improve the living conditions of various parts of the world in need of economic rehabilitation, including the former Soviet empire, and various nations of Latin America and Africa. Nevertheless, whatever success his policy advice has enjoyed, it has been very much against the spirit in which he offered it.
As The Idealist makes clear, Sachs sees himself—and has persuaded many others to see him—as the ultimate humanitarian, someone with unbounded faith in the ability of even the poorest of people to raise themselves, once afforded opportunities that Westerners can easily supply. On the other hand, were Sachs to die tomorrow, he would be mainly remembered as the person who persuaded various former socialist regimes to engage in drastic marketisation policies that ruined many people’s lives in the short term before a new economic equilibrium was found. Once another generation or two has passed, perhaps in the hands of some late 21st century Hegel with a taste for world-historic irony, Sachs may be hailed as a pioneer of globalised neoliberalism, a master of foresight. But it is clear that in the interim the so-called “Russian Oligarchs” already owe a debt of gratitude to Sachs for having enabled them to take full advantage of the fire sale on Soviet assets after 1989.
However, in the circles where the phrase “The Idealist” is taken non-ironically to encapsulate Sachs’ career to date, he is credited with the sort of inspirational bookkeeping that hovers over all development aid discussions— namely, that poverty could be eliminated simply with a 1-2% redistribution of the world’s wealth. That this has failed to happen is taken to be indicative of the greed and callousness of the rich. Depending on the preferred diagnosis, this in turn may be due to either cultural stereotypes that the rich may hold of the poor—feckless, undeserving, whatever—or more general evolutionary tendencies that bias aid toward those with whom one is in mutually beneficial relationships (for example, Israel, Egypt, Pakistan, in the case of the United States)—that is, not poor people in remote places with whom one has little chance of future contact. But whichever diagnosis one prefers, idealists like Sachs assume that the prescribed redistribution policies would do the trick. The problem is “simply” one of the donors stepping up to the plate, since once they do so the poor will respond accordingly to improve their standard of living.
Sachs and his entourage of conscientious celebrities such as U2’s front man Bono Vox (who penned the Foreword to Sachs’ best-selling The End of Poverty) and more sober academic fellow-travelers such as utilitarian philosopher Peter Singer appear never to have mastered the difference between what economists call “direct” and “indirect” costs. As a result, they fail to see that decisions are not simply triggers for action but actions in their own right that carry their own costs—in this case, on the one hand, to get potential benefactors to the point where they make appropriate donations, and, on the other, to get beneficiaries to the point that they receive, and then use, donations in the spirit in which they are intended. When Sachs’ colleagues question outright his economic competence, it is just this blindness to the pervasiveness of indirect costs that they have in mind. In The Idealist, Sachs’ most formidable critic turns out to be the co-author of Poor Economics, MIT’s Esther Duflo, who argues that Sachs never seemed to have learned that “development aid” is less about “aid” and more about “development,” the costs of which go well beyond the sheer transfer of wealth.
Lest one think that Sachs is being considered unfairly, a telling moment in The Idealist occurs in an exchange between Sachs and Paul Farmer, a famous medical anthropologist and founder of Partners in Health, whose secular piety rivals that of Sachs himself. In his exhortation to Farmer, Sachs declares that the problems of poor health care in Haiti require raising the funding ante from millions to billions of dollars. The reader is left with the impression that Sachs believes that the main problem here is a weakness of will on the part of potential donors— and not any resistance or perhaps deficiencies on the part of the recipients themselves.
Seen in historical perspective, Sachs’s enthusiasm for development aid combined with his obliviousness to its indirect costs mark him as a vestige of the Enlightenment in its original 18th century form. Indeed, Sachs and his fans promote a “Zombie Enlightenment” that fails to see that its premises are nowadays dead on arrival. By today’s standards, the original Enlightenment wits—not least Adam Smith—were bold and reckless. They were guided by a theological vision that was to be redeemed in very material terms, issuing in a “heaven on earth,” to recall the phrase used by the greatest modern American historian of this period, Carl Becker. Here we need to recall that over the centuries the Roman Catholic Church had been very effective in reminding humanity of its biblically fallen status to cast doubt on our capacity for self-determination. Yet at the same time, from the onset of Christianity, various heretical strands—most notably the one stemming from the fifth century Celtic lawyer Pelagius—have argued that humanity can pull itself up from its bootstraps, without any explicit help from God, to regain its divine entitlement. Indeed, if Pelagius is correct, God may even want it that way.
Generally speaking, the Protestant Reformation helped to advance the idea that “where there’s a will, there’s a way” with regard to salvation, but the Enlightenment took it one step further. Certainly many reformed Christians, not least the English Puritans whose forced exile to America resulted in the United States, disdained the profligate spending patterns of the largely Catholic monarchies of Europe. But the original Enlightenment wits believed that such consumption was itself a form of investment, the full returns of which could be realized only if ordinary people were released into a free labour market that allowed them to cater competitively to whatever new tastes the nobles may have developed as they learned more about what the wider world had to offer. Over time, so the wits thought, this would raise everyone’s level of civility as supply and demand became subject to greater discrimination, not least by consumers discovering post facto whether they received value for money.
The dark side of the Enlightenment
But there was a dark side to this Enlightenment optimism, which helps to explain how Sachs, now the great humanitarian saint, could have started his career by applying what his critics now call “shock therapy” to open up markets in formerly socialist regimes. In The Dialectic of Enlightenment, the foundational work of the Frankfurt School of critical theory, Theodor Adorno and Max Horkheimer argued that the Enlightenment released people from their hereditary social bonds only to force them to prove in a sink or swim fashion (as one might a scientific proposition) their fitness in the emerging liberal social order. In effect, people were legally stripped of the little humanity to which they had been entitled (via an ascribed social status) and forced to reapply for a potentially much greater sense of humanity but now under conditions of considerable uncertainty. The hope was that people would spontaneously discover their own special talent, or ‘comparative advantage’, and seek to maximize it in their newfound state of liberty. By implication, those who failed to secure employment in this environment failed to qualify as “human.” Of course, one could question the sincerity of the nobles to whom the Enlightenment wits made their pitch for free markets. (And Sachs himself has certainly complained that his political clients have failed to follow through on his advice.) But the wits themselves were clear that whatever subsidies were provided to these newly free subjects should be in the spirit of capital development—as opposed to charity, which the nobles had all too readily dispensed to pacify the poor, with the unintended consequence of arresting economic growth.
In other words, the difference between the Enlightenment’s original optimism and the more sober awareness that led Thomas Carlyle in the mid-nineteenth century to dub economics the “dismal science” lay in recognising the indirect costs of doing the work of development. Two types of indirect costs relating to development aid go beyond the value of the wealth that is transferred from rich to poor. First, there are opportunity costs—that is, the costs from, on the one hand, depriving benefactors of alternative prospects for investment and, on the other, depriving the beneficiaries of continuing with their current mode of existence. Second, there are transaction costs, some of which are calculated as “overhead” in budgets, which may be more important in terms of the ultimate efficacy of development aid. These include the cost of persuading the rich to part with their wealth and the cost of persuading the poor to accept the wealth, both in the right spirit—and more specifically, the cost of getting both to behave in the appropriate manner on a regular basis, especially in terms of inducing the poor to embark on their own voyage of “comparative advantage” discovery. Sachs’ unabated enthusiasm in the face of these challenges marks him most clearly as a latter-day Enlightenment figure in zombie mode.
In terms of opportunity costs, it is instructive to contrast China’s attempt to “buy the world,” to adapt a phrase from the British development economist Peter Nolan, with what is normally regarded as “development aid.” China provides enormous financial subsidies to Africans—more than the World Bank—but just enough to enable them to supply goods and services for the Chinese workers who are imported to mine Africa’s natural resources. Without demonstrating any concern for the benchmarks of Sachs’ Millennium Project, China aims to ensure that the Africans remain cooperative in the extraction of their resources. This is one rather ruthless but so far successful way for a benefactor not to suffer an “opportunity cost” by helping the poor. For the United Nations to exhort China to increase or even reorient its African investments would raise the spectre of transaction costs, something that normally inhibits big business from investing in countries with minimum wage laws and robust health and safety codes.
But an opportunity costs-based analysis equally applies to “the culture of poverty” that prevents the poor from seeing aid as the self-capitalisation scheme that the developers intend it to be. Here the poor’s resistance should be seen positively as a simple defence of their culture. While some of the poor may wish to trade out of their heritage, others may regard the loss of cultural identity as an intolerable cost and hence prefer to remain in an “undeveloped” state, adapting their aid packages to already existing needs without substantially transforming their mode of being. Poor Economics presents this situation as the main “cognitive” barrier to the efficacy of development aid, where “cognitive” implies that the authors believe that it would be in the poor’s long-term interest to adopt the new identity that the aid is designed to promote. Put bluntly, the poor must learn to think better. In the nineteenth and twentieth centuries, this attitude was dubbed “Imperialist” for presenting the “underdeveloped” with the stark choice of going forward with the rest of humanity or staying behind in their cultural backwater. Such Imperialism—and its ironic offspring World Communism—is basically how the Enlightenment continued to be promoted once it was mugged by reality in the form of the negative unintended consequences of the French and Industrial Revolutions, both of which had been inspired by policy advice given during the Enlightenment.
This brings us to the transaction costs of enabling both the potential benefactors and the beneficiaries to stay the course required for either party to realize that their investment is worthwhile. The level and duration of investment goes beyond the showcase development projects to which Sachs has drawn much media attention, which are often the product of a spike in donations in a relatively small space over a relatively short period. A little known precursor of modern economists, John Rae, advanced as early as 1834 a “sociological theory of capital” that proposed “anticipation” and “abstinence” as the moral qualities necessary for promoting long-term economic development. Taken together these qualities could override certain default behavioural patterns—encapsulated in the phrase “selling short”—that prevent people from acquiring the long-term vision and staying power required of sustained prosperity. Nowadays economists deal with these matters under the rubric of “time preference theory,” which forms the intellectual core of Poor Economics’ case against Sachs.
In short, Poor Economics accuses Sachs of underestimating the extent to which those most in need of development “discount the future” because, no matter the good fortune that development aid temporarily brings, the poor continue to believe that they will live for roughly the same forty years that their ancestors have lived and for which their culture and institutions have been designed. Simply telling them that the science and technology is now available to double their life expectancy is likely to met with the same incredulity as the TED talks that regularly tell us in the developed world that we will soon be able to double our own life expectancy to 150-200 years. Moreover, in both cases, the resistance of the target beneficiaries is sufficient to give pause to potential benefactors who are worried about the viability of their investments. Here Poor Economics makes some quite plausible but expensive proposals for scaling-up development aid successes. These, it turns out, are not so different from what enabled Imperialism to work as well as it did, if “Westernising” the non-Western world is understood as the goal. Thus, the migration of talented Westerners to the developing world, the deep recruitment of promising non-Western natives to the cause, and a vigorous ideological campaign aimed at both the would-be developers and developed were all involved in the Imperialist effort to meet the transaction costs entailed in the transfer of wealth from the developed to the developing world.
But even then, as historian Niall Ferguson has ruefully observed, Imperialism failed not because it was failing to have the desired long-term effects, but mainly because after the Second World War its most active promoters (including Winston Churchill) decided that it was no longer affordable. (Witness India, since its inception, the world’s largest democracy.) The matter boiled down to the likely rate of return on any future investment. A similar judgement probably awaits development aid on the heroic scale promoted in both The Idealist and Poor Economics. In the end, the only real difference between Sachs and the critical authors of these two books is that the latter have much better bookkeeping skills, representing the harder face of an Enlightenment mugged by the reality of transaction costs. Whether that is sufficient to unleash the political will and economic resources worthy of an Imperialism 2.0 is very much an open question. But the long-term prospects for development aid may depend on it—that is, unless, of course, the Chinese succeed in teaching the world how to be proper neoliberals.
Archives – Winter 2014
Two sculptures by Los Angeles-based artist Liz Larner adorn the newly opened Edith O’Donnell Arts and Technology Building at the University of Texas at Dallas. The pieces were commissioned by the Nasher Sculpture Center for T its citywide exhibition Nasher XChange in celebration of the museum’s 10th anniversary. The exhibition runs October 19, 2013 through February 16, 2014.
Larner created two versions of the piece titled X for the Nasher XChange: a wood version of the work is located inside the O’Donnell Building and a mirrored, stainless steel version is located in the building’s courtyard. The X-shape of the sculpture is described by Larner as continuing “an investigation into the open form and the use of line to create volume.” The piece has been developed over several years and was created with digital modeling technology.
“Larner’s work is a wonderful example of the intersection between new technologies and the traditional, three-dimensional sculptural form,” said Bonnie Pitman, distinguished scholar-in-residence at the University of Texas at Dallas. “Larner’s experience of incorporating technology into her work made this pairing a natural fit with the Arts and Technology (ATEC) program.”
Larner has exhibited at the Museum of Contemporary Art, Los Angeles; the Smithsonian American Art Museum, Washington, D.C.; the Museum of Contemporary Art, Chicago; and the Galleri Nordanstad-Skarstedt, Stockholm.
My Brain is My Inkstand
Drawing as Thinking and Process
My Brain Is in My Inkstand: Drawing as Thinking and Process is an exhibition debuting at the Cranbrook Art Museum, Bloomfield Hills, Michigan, that brings together 22 artists from around the world to redefine the notion of drawing as a thinking process in the arts and sciences alike. Sketches on paper are the first materialized traces of an idea, but they are also an instrument that makes a meandering thought concrete.
Inspired by the accompanying exhibition The Islands of Benoît Mandelbrot, the exhibition uses multiple sources to show how drawings reveal the interdependency of mark-making and thinking. It brings together artists and scientists, basketball coaches and skateboarders, biologists and Native Americans to show how tracing lines is a prerequisite for all mental activity.
Featured artists include David Bowen, John Cage, Stanley A. Cain, Oron Catts, Benjamin Forster, Front Design, Nikolaus Gansterer, legendary basketball coach Phil Jackson, Patricia Johanson, Sol LeWitt, Mark Lombardi, Tony Orrico, Tristan Perich, Robin Rhode, Eero Saarinen, Ruth Adler Schnee, Carolee Schneemann, Chemi Rosado Seijo, Corrie Van Sice, Jorinde Voigt, Ionat Zurr, and many more. It also integrates work from the collections of the Cranbrook Institute of Science and the Cranbrook Center for Collections and Research.
A live performance by artist Tony Orrico took place on November 16 and 17 during which he explored his own body and its physical limits as he created a drawing that remains in the museum for the duration of the exhibition. Artist and composer Tristan Perich installed a live Machine Drawing that uses mechanics and code to cumulatively etch markings across a museum wall.
The title of the exhibition derives from a quotation by philosopher, mathematician and scientist Charles Sanders Peirce, whose work involving the over- and under-laying of mathematical formulas with pictographic drawings is presented for the first time. The exhibition is on view November 16, 2013, through March 30, 2014. An exhibition catalog My Brain Is in My Inkstand: Drawing as Thinking and Process, edited by Nina Samuel and Gregory Wittkopp and published by Cranbrook Art Museum, is available.
From the Hill – Winter 2014
Congress passes budget deal, launches frenetic appropriations activity
After a contentious few months that saw a two-week government shutdown, a narrowly-averted debt crisis, and continuing politicking over the size and shape of federal expenditures and deficits, Congress has begun to tentatively dip its collective toe in the waters of compromise. The October 17 continuing resolution that ended the shutdown and ensured government would remain open through January 15, 2014, also established a conference committee to bridge the large gap between the House and Senate budgets. That committee, led by Rep. Paul Ryan (R-WI) and Sen. Patty Murray (DWA), managed to find common ground and reach a limited deal on December 10. The House approved the deal by a 332-94 margin, and the Senate approved it with 64-36 vote.
For the science community, the key part of the deal is its provisions on discretionary spending. The Ryan/Murray deal would establish discretionary spending targets of $1.012 trillion in 2014 (a nominal increase of about 2.6% above 2013) and $1.14 trillion in 2015. For 2014, this would mean about a $45 billion increase above sequester-level spending, or a rollback of about half the cuts required under sequestration, split between defense and nondefense. The rollback for 2015 is a bit less ambitious: Discretionary spending would rise by only about $19 billion above sequester-level spending. This means about 75% of the spending reduction required under sequestration would remain in effect.
The deal addresses only overall spending targets, not the budgets of individual agencies, but according to recent AAAS estimates, it could serve to boost R&D by as much as $8 billion or more over the next two years above sequester levels. Although it is a welcome development that eases the strain of sequester on science and innovation budgets, the deal does not address the big issues such as taxes and entitlement reform that are driving the deficit debate, and it leaves in place most spending reductions under sequestration through 2021. If the sequestration budget limits remain in effect, it will likely mean tens of billions of dollars in lost R&D funding and the continued decline in federal R&D as a share of the economy.
The focus now shifts back to appropriators, who will have a limited time to complete the work on FY 2014 appropriations started months ago. No doubt, at least some science agencies will see a funding increase above sequester levels as a result of the deal, but the size, shape, and focus of appropriations is yet to be determined. It is possible that appropriators, by choice or necessity, will resort to passing another full-year continuing resolution like that passed for FY 2014. Such a step would finalize funding but would also somewhat hinder agencies’ ability to start new programs or make changes to existing ones.
The appropriators have only 4 weeks to work out the details. Sen. Barbara Mikulski (D-MD), chair of the Senate Appropriations Committee, and Rep. Harold Rogers (R-KY), chair of the House Appropriations Committee, will lead the effort. The current deal certainly does not mean that pressure to trim many programs will ease. For example, Sen. Thad Cochran (R-MS), the second-ranking Republican on the Senate Appropriations Committee, is contending with a primary challenge from Chris McDaniel, who is backed by the fiscally conservative Club for Growth.
The America Creating Opportunities to Meaningfully Promote Excellence in Technology, Education, and Science Act, or the America COMPETES Act (P.L. 110-69), was first signed in 2007 by President George W. Bush. The legislation was intended “to invest in innovation through research and development, and to improve competitiveness of the United States.” The bill was reauthorized in 2010 (H.R. 5116) and is up for reauthorization again.
Currently, there are three drafts circulating Capitol Hill. The House Democrats released a draft America COMPETES Reauthorization Act in late October, with a revision in December. The House Republicans are considering two separate discussion drafts, which were both released in early November: The Enabling Innovation for Science, Technology, and Energy in America (EINSTEIN) Act, which addresses only the Department of Energy’s Office of Science, and the Frontiers in Research, Science, and Technology (FIRST) Act, which deals with the National Science Foundation (NSF), the Office of Science & Technology Policy, the National Institute of Standards and Technology, and science, technology, engineering, and math education. It is important to emphasize that these are discussion drafts only; they have not been formally introduced, and all are subject to change.
Although each of these bills aims to improve U.S. competitiveness and innovation, their content varies and it is difficult to draw comparisons. The House bills crafted by the Republicans of the Science, Space, and Technology Committee do not include funding levels for federal agencies, whereas the Democrats’ draft would authorize five-year funding increases (over sequestration levels), averaging nearly 5% per year, before adjusting for inflation.
The FIRST Act generated the most attention from the scientific community, eliciting concern about a few of the provisions included. For example, the bill would require NSF to produce written justification for accepted grant applications indicating how they satisfy one or more goals outlined in the draft (e.g., national defense), and the justification would have to be publicly available before the grant is awarded.
Furthermore, it would require that researchers certify the veracity of their research results if published and would ban primary investigators from receiving federal funding for 10 years if they are found guilty of misconduct.
The New Democrat Coalition, a group of moderate, pro-growth Democratic representatives, did not release a bill, but it has published a “reauthorization agenda” for America COMPETES that outlines principles for improving U.S. innovation. These include supporting basic research, providing a stable source of funding for R&D, supporting small businesses, and expanding public-private partnerships, among others.
Congress in brief
• On December 5, the House passed the Innovation Act (H.R. 3309) by an overwhelming vote of 325-91. Six higher education groups co-signed a statement articulating their opposition to portions of the House bill, expressing concern that changes to the litigant fee system could have a negative impact on researchers’ collaborative efforts.
• On November 18, the House passed the Digital Accountability and Transparency Act (H.R. 2061) by a vote of 388-1. Earlier in November, the Senate Homeland Security and Government Affairs Committee passed its version of the DATA Act (S. 994), which may now be sent to the Senate floor for a vote. Both bills seek to improve transparency of federal spending on contracts, loans, and grants by requiring the establishment of government-wide data standards and reporting requirements for data posted to USASpending.gov. However, the House bill, unlike the Senate bill, includes a provision that essentially codifies Office of Management and Budget (OMB) federal travel restrictions, with additional reporting requirements. As with the OMB rules, for example, it would reduce an agency’s total travel budget by 30% below its FY 2010 spending levels. However, unlike OMB, the House bill would also place a cap of 50 federal employees for a single international conference. In addition, it would require all federal employees participating in conferences to make public all conference materials associated with their attendance (e.g., slides, oral remarks, and video recordings).
• On November 21 Rep. Chaka Fattah (D-PA) introduced the America’s FOCUS Act, which would establish a new Treasury fund from corporate fines, penalties, and settlements. A third of the fund would go toward investments in science, technology, math, and engineering education and youth mentoring, and another third would go to the National Institutes of Health. The Justice Department has reportedly collected billions in corporate fines and settlements, and the money goes to the General Fund of the Treasury when not designated for a specific purpose. Says Fattah: “This bill presents an opportunity to intentionally direct sums from settlements between the federal government and corporate and financial institutions to programs that can improve the life chances of Americans and allow our country to maintain its economic competitiveness.”
• In November Congress sent a bill to the president that would lift a congressionally mandated $30-million cap on how much the National Institutes of Health could spend to retire and care for retired federal research chimpanzees. NIH will now be able to continue supporting chimps at Chimp Haven, the Louisiana-based federal chimp sanctuary, and move forward with its plan to retire all but 50 of its 360 research chimps.
• On October 29 the House Oversight and Government Reform Committee approved the Grant Reform and New Transparency (GRANT) Act (HR 3316), which seeks to enhance transparency in the federal grant process. AAAS and other scientific and university groups have expressed their misgivings about provisions in a previous version of the bill that would mandate the public disclosure of full grant applications and peer reviewers. In an interview with Science, sponsor Rep. James Lankford (R-OK) indicated he is open to making changes to the bill in response to the concerns of the research community.
Agency updates
• On December 5, the White House released a presidential memorandum that increases the amount of renewable energy that each federal agency is required to use. The memorandum states that “20 percent of the total amount of electric energy consumed by each agency…shall be renewable energy” by FY 2020. The memorandum also requires that federal agencies update their building performance and energy management practices in order to better manage energy consumption.
• The White House recently announced a new $100-million initiative to find a cure for HIV. The project will not require new funds; rather, the money will be re-directed from existing funds, such as expiring research grants.
• The Department of Homeland Security is inviting input into the development of the National Critical Infrastructure Security and Resilience Research and Development Plan. For the purpose of the plan, critical infrastructure includes both cyber and physical components, systems, and networks for the different sectors outlined in the presidential policy directive (PPD-21) on Critical Infrastructure Security and Resilience. That directive called for the development of this R&D plan by February 2015. The call for input includes specific questions pertaining to sector interdependencies; articulation with state, local, and other non-federal issues and responsibilities; prioritization of research areas; and essential elements for the plan.
• On November 21, the Obama Administration outlined its strategy for maintaining what it describes as the U.S. global leadership role in spaceflight and exploration in the new National Space Transportation Policy. The policy reinforces several previously stated administration priorities; however, it differs from prior versions by placing a strong emphasis on accelerating development of commercially built and operated rockets. In order to achieve this, the policy calls on federal agencies to continue supporting the development of private U.S. spaceships to transport astronauts to and from low-Earth orbit, and directs the National Aeronautics and Space Administration to continue working toward a heavy-lift rocket for further travel. Overall, the policy reflects congressional desire to boost commercial-space ventures and protect funding for longer-term, deep-space exploration plans.
• The Obama Administration issued a new rule on November 8 to require health insurers to handle copays, deductibles, and benefits for mental health conditions and substance abuse in the same way that they do physical ailments. The rule “breaks down barriers that stand in the way of treatment and recovery services for millions of Americans,” said Health and Human Services Secretary Kathleen Sebelius. “Building on these rules, the Affordable Care Act is expanding mental health and substance use disorder benefits and parity protections to 62 million Americans.” The long-awaited rule implements the Paul Wellstone and Pete Domenici Mental Health Parity and Addiction Equity Act of 2008. The Obama Administration emphasized that issuing the rule is part of its approach to reducing gun violence.
• The Environmental Protection Agency has released draft climate change adaptation implementation plans for each of its ten regions and seven national programs. Adaptation will involve anticipating and planning for changes in climate and incorporating considerations of climate change into many of the agency’s programs, policies, rules, and operations to ensure they are effective under changing climatic conditions. Public comments are due January 3, 2014.
• On November 1, President Barack Obama issued an executive order to help federal and state agencies prepare infrastructure to withstand extreme weather events caused by climate change. The order sets up a new interagency Council on Climate Preparedness and Resilience, which replaces the task force set up in 2009, and establishes a Climate Preparedness and Resilience Task Force comprised of federal, state, and local officials who will make recommendations to “remove barriers, create incentives, and otherwise modernize federal programs to encourage investments, practices, and partnerships that facilitate increased resilience to climate impacts, including those associated with extreme weather.”
• The Food and Drug Administration (FDA) has announced two new actions to prevent shortages in drugs used to treat patients. The first is the development of a strategic plan that describes upcoming agency actions to improve responses to potential shortages and addresses manufacturing and quality issues that are often at the root of drug shortages. The second is a proposed rule, with a public comment period of 60 days, requiring manufacturers of medically important prescription drugs to notify the FDA of events likely to disrupt drug supply.
• On October 25, the Office of Science and Technology Policy (OSTP) released a Biological Incident Response and Recovery Science and Technology Roadmap to help ensure that decisionmakers and first responders are equipped with the tools necessary to respond to and recover from a major biological incident. The Roadmap aims to strengthen the national response by categorizing key scientific gaps, identifying specific technological solutions, and prioritizing research activities to enable the government to make decisions more effectively. The Roadmap, which was developed by the interagency Biological Response and Recovery Science and Technology Working Group under the National Science and Technology Council’s Committee on Homeland and National Security, complements the National Biosurveillance Science and Technology Roadmap that was published in June 2013.
Greenhouse Gas Emissions from International Transport
International transport, which includes ocean shipping and aviation, is among the fastest-growing sources of human-generated greenhouse gas emissions. Between 2009 and 2010, carbon dioxide (CO2) emissions from international transport grew faster— I at 7 and 6.5%, respectively—than those from China, which grew by 6%. Although 2010 was a year of especially rapid growth as global trade and travel bounced back from the 2009 recession, emissions from this activity are expected to grow to between two and three times their current level by 2050. This growth will start from a small but substantial base: If the sector were a country, its current emissions would be roughly the size of those of Japan or Germany.
Rising emissions from international transport could dilute hard-won reductions in other sectors, such as the switch from coal to wind and solar electricity. To see how, consider the case of the United Kingdom. In 2010, it emitted about 500 million tons of CO2. Domestic and international flights departing from the United Kingdom in that year emitted 33 million tons, or about 7% of the total. The United Kingdom has instituted a legally binding commitment to reduce its annual greenhouse gas emissions in 2050 to one-fifth of their level in 1990. This means that in 2050, the United Kingdom ought to emit a mere 120 million tons of CO2. The UK.. Department of Energy and Climate Change has forecast that under current policies to control their rise, CO2 emissions from aviation in the United Kingdom will rise to about 50 million tons, or an untenable 42% of the total.
The unchecked growth of emissions from transport is therefore inconsistent with the drastic reduction in the overall production of greenhouse gases that is required to forestall dangerous climate change. The Kyoto Protocol to the United Nations Framework Convention on Climate Change (UNFCCC) calls for the International Civil Aviation Organization (ICAO) and the International Maritime Organization (IMO) to put in place mechanisms to limit the contribution of international transport to global warming.
Who is responsible?
Given the nature of global transport, it is difficult to allocate its environmental impacts to any one country. Consider a ship that is registered in Liberia, operated by a Danish shipping line, and making a voyage from Shanghai to Los Angeles carrying products made in China by a European firm for sale in North America. How and to whom should the emissions from this voyage be allocated, and who should be assigned responsibility for reducing them? Questions such as these have proven to be politically intractable.
One reason is that the UNFCCC has traditionally operated on the principle of common but differentiated responsibilities. This principle suggests that developing countries have made a smaller historic contribution to environmental problems than have developed countries, and may not have the wherewithal to tackle them. Therefore, developing countries have argued that they ought to be exempt from taking on legally binding commitments as part of any program to curb global greenhouse gas production.
Conversely, the ICAO and the IMO have operated on the principle of nondiscrimination. This is the notion that regardless of its nationality, an aircraft or ship performing an international voyage ought to be subject to the same rules and standards. Developed countries argue that in the interests of effectiveness and efficiency, this principle is sacrosanct. That is, if developed countries take on legally binding obligations as part of a deal to reduce the environmental footprint of aviation and ocean shipping, then so must developing nations.
THE RESEARCH COMMUNITY SHOULD TAKE THE INITIATIVE TO ENSURE THAT ALL DOCTORAL AND POSTDOCTORAL TRAINEES RECEIVE INSTRUCTION IN THE ETHICAL STANDARDS GOVERNING RESEARCH.
Tools available, but dull
Progress at both the ICAO and the IMO has been sluggish. In 2011, the IMO defined an efficiency standard for new ships. It came into effect in 2013 and will be progressively tightened. For existing ships, the IMO published guidelines for voluntary energy management plans. It forecasts that this combination of measures is likely to reduce emissions from shipping by 180 million ton by 2020, or by 9 to 16% relative to business as usual. By the IMO’s own (conservative) estimate, operators would save money by adopting this standard.
The IMO admits that its measures would fall far short of compensating for the increase in emissions due to burgeoning international trade over the next few decades. It has recommended that a market-based mechanism be put in place to augment the measures adopted so far, but has not published details of how this mechanism would work.
For its part, the ICAO in 2011 asked all of its 191 member states to submit plans for greening their aviation sectors. By June 2013, 61 countries, representing about 80% of the world’s international air traffic, had done so. The ICAO reported in September 2013 that some of these plans were too sketchy for it to be able to estimate their impact on emissions.
The European Union, facing the same dilemma as the United Kingdom (that is, stringent economy-wide targets undermined by rampant growth in transport emissions), announced that it would include aviation in its Emissions Trading Scheme from 2012 onward. In particular, the European Union said that any flight, domestic or international, that departed from an EU airport would fall under the purview of its scheme.
Although the impact on airfares of the EU proposal would have been modest (in 2012, about $2 per passenger per round trip flight between New York and London) there was international outrage at the European Union’s proposal to act unilaterally. Critics pointed out that only the ICAO had the authority to impose an environmental charge on international flights.
The European Union agreed to defer implementation to give the ICAO time to develop an alternative. In September 2013, the ICAO declared that it would propose a market-based mechanism to reduce greenhouse gas emissions from international aviation by 2016 and implement it by 2020. It outlined three plausible variants of such a mechanism. The first variant was to require airlines to buy credits each year if their emissions exceeded a predefined threshold. The second was to require airlines to buy credits and also to generate revenues by applying a fee to each ton of carbon emitted. The third was to set a cap on emissions within the sector, and allocate or auction credits equivalent to this cap. Operators that exceeded such a cap would be required to buy additional credits from others who had come in under it.
The ICAO is also working on developing an efficiency index for aircraft. However, the organization has not yet set mandatory targets for the efficiency levels that current or future aircraft must reach.
Tools may be useful anyway
The measures that the IMO and ICAO have suggested so far could go some way toward addressing the problem. For instance, as a first step in implementing the proposed market-based mechanisms for both industries, accurate data on fuel burn will need to be collected. For shipping, it is not clear that sufficiently detailed data are logged at all. For aviation, these data are not made publically available even if they are logged. The availability of accurate fuel burn data, even in aggregate form, should improve the quality of debate and policymaking even before the schemes themselves have any effect.
In the absence of regulation, even improvements that are economically viable may not be made. For instance, ships are often owned and operated by different entities. The benefits of higher efficiency may accrue to whoever charters the ship. Owners would have to bear the upfront cost of a more efficient ship. The premium that they receive on chartering out these more efficient ships is often not large enough to make up for the extra initial cost. Sometimes owners may not know about the technologies available to them. Or they may not have access to finance to pay for improvements, even if they thought that they could recover their costs over time.
The fuel efficiency of air travel in the United States has improved more than that of any mode of transport in the past 30 years. And yet, recent analysis of the market showed that there was a wide gap in the performance of airlines on this measure. Moreover, the correlation between an airline’s efficiency ranking and its profitability was very small. The most profitable airlines were those that served niche markets with little competition, and so did not have a strong incentive to operate as efficiently as possible.
The IMO’s standard could provide the impetus for ship owners and operators to ensure that at least those modifications that are likely to produce environmental benefit and pay for themselves over time will be adopted. The same is true of the nascent efficiency standard for aircraft.
As such, efficiency standards can be useful. For shipping, there is scope to make the existing standard more ambitious. For aviation, the ICAO should work on developing and enforcing a standard to augment the proposed market-based mechanism.
Toward an efficient mechanism
The potential of standards is limited by the fact that after a point, reducing emissions from shipping and aviation becomes very expensive. Analysis by the IMO indicates that by 2020, annual CO2 emissions from shipping could be cut by 250 million tons using methods that would save operators money in the long term. Beyond this level, the cost of reducing each additional ton of emissions would escalate rapidly, and further cuts would become uneconomical, given current technology.
In aviation, there is some enthusiasm for the use of sustainable alternative fuels. Analysis by researchers at the Massachusetts Institute of Technology suggested that even if the feedstock could be grown on land that would otherwise have been left fallow, reducing CO2 emissions by switching to biofuels produced by currently available technology would cost $50 per ton of emissions avoided. If biofuels from soybean oil were used instead, the cost would be $400 per ton of emissions avoided.
Because the cost of making large cuts in emissions within international transport is probably prohibitive, it is economically efficient for the industry to pay for cuts to be made in other sectors, where they are cheaper to make. Imagine that the international transport sector implemented a global emissions trading scheme in which the right to emit one ton of CO2 over a certain threshold traded at $30. Analysis published in 2013 and led by Annela Anger, then at the University of Cambridge, suggested that under such conditions, net emissions from international transport would be 40% lower than they would otherwise have been. Only about 2% of this drop would come from reduced emissions in the sector itself. For the rest, airlines and ship operators would buy credits generated by the Clean Development Mechanism, developed under the Kyoto Protocol, which allows a country with an emission-reduction or emission-limitation commitment to purchase certified emission-reduction credits from developing countries. Because these purchases would produce benefits in developing countries, the net impact on global economic output would be slightly positive.
The impact of an emissions fee on airfares is likely to be small. Given that demand for international air travel is relatively insensitive to price, it is unlikely to restrict the movement of people. The cost would primarily be borne by those who are already wealthy enough to fly. This could make it palatable to developing countries, which have argued that taking on costly obligations to reduce the environmental impact of their growth would hurt their poorest citizens.
Analysis by the UN Secretary General’s Advisory Group on Climate Finance showed that putting a price of $45 on each ton of CO2 emissions from marine transport would have a minimal impact on the prices of commodities. For low-value commodities such as jute shipped from Bangladesh to Europe, the price would rise by about 2%. For high-value commodities such as coffee, the rise in price would be about 0.2%.
Even the international airline industry, as represented by the International Air Transport Association and others, has expressed support for a global scheme that allows the industry to offset its emissions by buying credits from other sectors.
Transport as test bed
The governing bodies of the ICAO and the IMO (which represent developing and developed countries) and the international transportation industry have all acknowledged the need for a mandatory global mechanism to curtail or offset the growth of planet-warming emissions from the sector. The ICAO and the IMO have long had a joint working group on harmonizing aeronautical and maritime search and rescue. Their responses to the greenhouse gas challenge have so far been developed independently. They should consider a similar group on greenhouse gas emissions, especially given that they already have converged on a similar basket of measures. They are likely to face similar problems in implementing these measures, and each should learn from the other’s experiences. For instance, the ICAO has published details of how different types of market-based mechanisms might work in the aviation sector, and the IMO could use these as a template for its own proposal. The IMO’s experience of implementing an efficiency standard for new ships could usefully inform the ICAO’s fledgling efforts to devise and roll out a similar benchmark.
Even though the impact on the global economy of attaching a price to the CO2 emitted by international transport is likely to be small, it could still be painful for some small countries, such as those whose economies rely heavily on international tourism. These countries might ask for exemptions from any global scheme, but excluding them would reduce efficiency and effectiveness. Indeed, if airlines or shipping lines routed journeys through countries that were exempt, total emissions could rise.
Auctioning credits or applying a fee to international sales of fuel oil for ships, called bunker fuel, could generate revenues for the Green Climate Fund that was proposed at the Cancun Climate Change Conference. This fund could compensate countries whose economies are disproportionately hurt, thus providing an economically efficient way to reconcile the principle of common but differentiated responsibilities with that of nondiscrimination.
Efforts to get an economy-wide, global deal on reducing greenhouse gas emissions have so far been frustrated. The IMO and ICAO have produced solutions to environmental problems such as acid rain–producing emissions from ships and noise from aircraft. All of their members have agreed to implement these solutions. International transport is an activity that clearly operates in the global commons, and where it is understood that some pooling of national sovereignty is essential.
The sector is small enough that it could buy offsets from existing sources of carbon credits, such as the Clean Development Mechanism, and that the impact on the global economy of taxing pollution from it would be small. And yet, implementation of such a policy would require policymakers to address all of the problems associated with an economy-wide solution: monitoring emissions, ensuring near-universal participation, and compensating countries that are hardest hit, as well as generating and recycling revenues for climate change mitigation and adaptation.
In addressing the specific problem of emissions from international transportation, policymakers have a test bed suitable for pioneering and evaluating innovative strategies and institutions to solve more general problems in the collective control of global climate change. This opportunity should not be squandered.
Parth Vaishnav ([email protected]) is in the Department of Engineering and Public Policy at Carnegie Mellon University in Pittsburgh, PA.
The doctrine of materialism, dating back to the ancient Greeks and Chinese and providing background for Descartes and Marx, argues that all phenomena found in nature can be explained by causal material factors. Because materialism is assumed to apply to all observed phenomena, it is also assumed that materialism can be applied to explain the behavior of life and systems of living things. This assumption forms a basis for the study of animal and human biology, as well as the study of ecological and social systems.
Is this so? Are life and living systems amenable to materialist explanations? Are such explanations poorly understood or are they fundamentally elusive? Does life exhibit the regularity that allows for the application of mathematics? Does the reduction of living systems to enable more precise mathematical treatment oversimplify them to the point of rendering them untrue to what they are? At some granular level, might life and living systems rely on the events occurring within an irreducible decision box that remains unpredictable?
Unlike in the physical sciences, description, more than explanation, continues to occupy most life scientists. Better description of ailments constituted much of medical practice until the beginning of the 20th century. A history of disciplined observation of the regularities found in living systems has yielded great insights (such as the germ theory of disease and immunization through vaccination) and delivered enormous health benefits in terms of increased longevity and prevented suffering. The advent of better diagnostics that enable more precise (and even dynamic) description of biological parameters continues to improve the delivery of health services to patients. Long-term statistical studies benefit large populations. Nonetheless, for the individual patient, the ability to associate symptoms with physiological mechanisms and predict health outcomes suffers because of the small sample size.
Because protecting and promoting human life remains fundamental to human society, medicine is always necessary whether or not it derives from a complete understanding of how the human body works. The patient is sick and must be treated. Honest practitioners will say, though, that despite the advanced diagnostics, a partial understanding of very basic mechanisms of how the human body works continues to be the case. Drugs that have the effect of aggravating cardiovascular problems for the same reason they are effective in reducing joint inflammation offer a case in point.
Although some proponents argue that DNA analysis will offer personal “customizeability” in future health care, the knowledge of sequence has yet to lead directly to knowledge of outcomes. The structure of the DNA molecule is known, but the syntax (and thus the meaning) of the genetic code remains mysterious. The structure itself is not deterministic. The weakness in the current knowledge of the mechanisms leading to disease is also evident at the level of organisms and their habitat, as science remains far from achieving a definitive characterization of the pathways and toxicology of the brew of synthetic chemicals that cloak the environment. In practice, the material chain of events leading to the diagnosis, treatment, and outcome of a human patient will remain uncertain. Statistical data and physiology and patient behavior, as well as physician patience and judgment, all contribute to treatment decisions. The ability to generate predictions based on statistical analyses worsens in moving from simple organisms to more complicated systems. Science can describe microbes better than it can describe adolescent girls, and describe girls better than the functioning of a modern city. Applying materialism to human social activity requires identifying parameters to measure and using those measurements to predict. Measuring the data and trusting that it can be used to predict the future responds to very practical needs. The fact that rational frameworks can be applied to describe human societies appeals to bureaucrats, businesspeople, and scientists alike. Mathematical models remove bias. The abstraction provided allows for nonideological decisionmaking.
Models as justifiers
Government bureaucrats, seeking objective explanations to justify expenditures, encourage the use of statistical models to describe the processes at work in societies. Based on model results, scientific rigor is invoked, as is the claim to objectivity, when determining how to direct public resources. Commerce itself of course benefits handsomely from the predictability of a reliable, mechanistic world. When Cornelius Vanderbilt offered regularly scheduled ship and rail service, commerce followed. Both bureaucrats and businesspeople rely on an orderly world where society operates according to rules. Mechanistic models offer an ideal, despite their lack of any consistent ability to predict.
Arguably, the scientific enterprise betrays an innate preference for systems that exhibit regularity most of all. That regularity gives meaning to a scientific description of reality that relies on the existence of fixed relationships between variables. The need for regularity may even undermine objectivity. For example, breeding strains of laboratory mice with rapid reproductive cycles may expedite orderly data generation, but it may also introduce bias into the subject population that becomes embedded in the analysis. Only by assuming regularity can sociologists and ecologists isolate single variables and attempt to describe their effect on a society or ecosystem.
What harm could come from the expectation that all features of life and living systems can be counted and understood? How would society benefit from revisiting the suitability of so strictly applying materialism to predict outcomes for life and living systems? Despite the flaws of the materialist approach, does it not ensure the greatest amount of objectivity? Does it not provide the most benefit to the largest number of people? Why should society question a strictly materialist model of life for social decisionmaking?
Blind adherence to the materialist idea that today’s best mathematical models should always provide the basis for social policy poses several problems. New biases are introduced, or perpetuated, by relying too heavily on materialist approaches. As computers become more powerful, society may be limited to considering variables that can be captured or counted (i.e., digitized or “datafied”) so that they can be modeled mathematically. The drive to digitize all information can force crude approximations of the factors that influence life and living systems. Modern society winds up restricting its interests to data suited to the binary format of current digital computers.
Many human factors may lie outside that format. For example, the quest for greater efficiency will move health care even more toward an exercise in matching diagnostic codes and treatment codes. These codes already drive the system more than responding to its needs. Code-matching naturally follows as the best response in a world where it is possible to handle essentially unlimited amounts of data. Once the framework is established, data definitions become entrenched. Subsequent policy evolution locks in early decisions about what codes to use, what data fields to populate, and what budget factors to consider in conducting cost/benefit analyses. Legacy data definitions drive the governmental and industrial responses, limiting the future range of possible actions.
Unspoken assumptions
When formulating broader social policy, unspoken assumptions abound regarding what constitutes the “greater good.” Here, too, the desired objectives, and the means to reach them, will favor measureable data. The data can be used to advance any number of policy agendas that may objectively reflect the interest of their proponents but remain partial. The drive to quantification favors economic analysis and the necessary valuation of public goods. Conveniently, dollars offer an eminently measurable variable, a common convertible currency that captures the value of livelihoods and lives, playgrounds and prisons, and all things of value to society. Using economic models, the policies of the 1950s and 1960s that presaged civic decline and suburban sprawl offered the most promising solutions to the social engineers and business interests that promoted them at the time.
The materialist approach influences not only how the United States sees itself, but how it sees other societies as well. The notion that aggregate wealth offers the best proxy for measuring social progress is not universal. Other cultures may aspire to a more equitable wealth distribution, greater national prominence, recognized technological prowess, or the exalted glory of God. These social goals remain important to societies around the globe and influence national-level decisionmaking in much of the world. The successes of neoliberalism notwithstanding, seeing the world through a strictly materialist lens may systematically underestimate the importance of the religious and cultural forces that motivate societies.
Perhaps the most troubling consequence of considering the best current modeling efforts as constituting the definitive materialist approach (that is, the rational understanding) is that the tail wags the dog more and more. In a digital age, model results are used to set priorities, and social goals that may hide what is in plain sight. The overwhelming attention to the modeling of climate change serves to diminish the attention paid to other, equal and even greater, environmental concerns such as municipal water systems, childhood disease, and urban air pollution, as well as social concerns such as public safety.
Things easily modeled receive the most attention in the social sphere whether they convey or obscure the relevant scientific parameters. Climate offers a clear case of modeling exercises used to advance political agendas by choosing which data to focus on and how to tweak the (literally) hundreds of parameters in any given model. Whether by design or default, the model tends to vindicate the modeler; for instance, the modeler that selects which natural mechanisms to include and which to neglect when modeling the annual global flux of carbon. Models, and policies to be based on them, ignore the consequences of climate change mitigation strategies, such as costly regressive electricity rates that force even middle-class people to scavenge the forest for fuel, or the benefits of global carbon fertilization. What becomes obscured is the fact that a self-consistent description useful for numerical modeling may not faithfully represent reality, whether physical or social.
Models offer an abstraction, a common basis for dialogue. For example, global initiatives such as the ongoing international activity beginning with the Earth Summit in Rio de Janeiro in 1992 were inspired by and continue to derive their relevance from model results. In trying to describe social and environmental problems, much effort is expended in modeling global inequity or evidence of environmental crisis. The effects of changing consumer attitudes that drive rising living standards and regional political realities such as war and lawlessness typically do not find their way into the analysis. Still, a vast enterprise continues to operate under the assumption that model refinement will always lead to greater accuracy in describing socially dependent natural phenomenon and that such accuracy will lead to better remedies for problems. Such expectations derive from the fact that materialist assumptions go unchallenged.
Adding needed perspective
What can be done? Given the pervasiveness and attractiveness of materialism and its centrality to Western thought, no simple list of policy recommendations can correct for its undue influence. Several steps in how the nation and society treat the results of strictly mathematical descriptions of social phenomena may help put things in better proportion from the public perspective.
One step would be to demand greater transparency in models used as evidence to formulate social policy. Transparency in the assumptions and limits of validity for studies involving large complicated systems would offer government and society a better understanding of the instances where quantitative analysis is and is not appropriate. Such stipulations might be alien not only to those who use models to justify their political agenda, but to scientists trying their best to create self-consistent digital versions of observed phenomena. Such transparency would expose the latent bias and the poor understanding of mechanism manifest in many mathematical descriptions of living (and nonliving) systems. Nature can never be proved wrong, but the errors of those who claim to understand it are legendary.
A further step involves actively incorporating ground-truthing from practitioners, not only from experts, when investigating the effects of proposed changes in public policy. Those with the common sense that is born of experience (such as patient caregivers, field scientists, engineers, and local officials) should be allowed to reclaim a stronger voice in public decisionmaking. Using protocols that treat expert analysis or computer simulations as sacrosanct in all cases should be reexamined.
As in the case for life and living systems, at the thermodynamic ensemble level, the description of physical systems also relies on statistics. The main difference between living and nonliving systems is that in nonliving systems, the units lack volition (i.e., will), a property found in the units that make up living systems. The debate is old, and the contention here is that despite their regularities, humans and human societies make choices. They are choices because they can, and do, defy prediction, even if the choices may seem inevitable, or at least explainable, in hindsight. Should life be modeled to the point of deliberately ridding it of the very drama that makes it dear? Stripping life of its serendipity to fit a model may not only be an assault on the soul; it may simply substitute one type of bias for another.
Iddo Wernick ([email protected]) is research associate in the Program for the Human Environment at The Rockefeller University.
Water
Internationally renowned Canadian photographer Edward Burtynsky’s latest body of work, Water, explores the course, collection, control, displacement, and depletion of this vital natural resource. The exhibition is the second initiative of the New Orleans Museum of Art (NOMA)-Contemporary Arts Center (CAC) programming partnership and features 60 large-scale photographs that form a global portrait of humanity’s relationship to water. The exhibition runs October 5, 2013, through January 19. 2014, at the CAC in New Orleans.
Burtynsky has long been recognized for his ability to combine vast and serious subject matter with a rigorous, formal approach to picture making. The resulting images are part abstraction, part architecture, and part raw data. In producing Water Burtynsky has worked across the globe—from the Gulf of Mexico to the shores of the Ganges—weaving together an ambitious representation of water’s increasingly fragmented lifecycle.
“Five years in the making, Water is at once Burtynsky’s most detailed and expansive project to date, with images of the 2010 Gulf oil spill, step wells in India, dam construction in China, aquaculture, farming, and pivot irrigation systems,” said Susan M. Taylor, Director of the New Orleans Museum of Art. In addition, Water includes some of the first pure landscapes that Burtynsky has made since the early 1980s. These archaic, almost primordial images of British Columbia place the structures of water control in a historical context, tracing the story of water from the ancient to the modern, and back again.
Although the story of water is certainly an ecological one, Burtynsky is more interested in presenting the facts on the ground than in declaring society’s motives good or bad. In focusing on all the facets of people’s relationship with water, including ritual and leisure, Burtynsky offers evidence without an argument. “Burtynsky’s work functions as an open-ended question about humanity’s past, present, and future,” said Russell Lord, Freeman Family Curator of Photographs at the New Orleans Museum of Art. “The big question is: Do these pictures represent the achievement of humanity or one of its greatest faults, or both? Each visitor might find a different answer in this exhibition, depending upon what they bring to it.”
The exhibition, organized by Russell Lord, is accompanied by a catalogue published by Steidl with over 100 color plates from Burtynsky’s water series. It includes essays by Lord and Wade Davis, renowned anthropologist and Explorer-in-Residence at the National Geographic Society. More information can be found at www.edwardburtynsky.com.
Book Review: Lighting the way
Lighting the way
A Short Bright Flash: Augustin Fresnel and the Birth of the Modern Lighthouse by Theresa Levitt. New York: W. W. Norton & Co., 2013, 288 pp.
Jody A. Roberts
In A Short Bright Flash: Augustin Fresnel and the Birth of the Modern Lighthouse, Theresa Levitt wastes little time in revealing just how bad things were for sailors in the 19th century. She begins with the grisly tale of la Méduse, a ship run aground off the coast of West Africa in 1817 and the abandonment, murder, and cannibalism that followed. Of the nearly 150 individuals who took refuge on a makeshift raft adrift in the Atlantic Ocean, only 15 survived the 15-day ordeal before being rescued. Not every shipwreck ended so dramatically, but with hundreds of boats lost each year (the British insurer Lloyd’s of London put the number at 362 in 1816 alone), the event and its awful ending struck a sensitive chord with an anxious public.
Thus, the scene was set for Fresnel’s invention of his eponymous lens, which proved to be a miraculous feat of mathematics, optics, and engineering. Lighthouse engineering held that a brighter light could be generated only by increasing the quantity of light available (more oil, more wicks) and reflecting that light with larger reflectors. Fresnel, a French physicist and engineer, challenged this approach by first arguing that the amount of light lost in the system needed just as much attention as the amount of light produced and reflected. That is, by examining the behavior of light and understanding how to maximize it, it would be possible to create a lamp that not only shone brighter and farther, but theoretically could do so with less oil. In turning this theory into reality, Fresnel challenged not only the status quo in lighthouse operations; he grounded his approach within the contemporaneous debates then raging within scientific circles about the nature of light.
Fresnel’s suggestion that light possessed wave-like properties kept him firmly on the outside of received wisdom. He was not alone in his approach to light, but his careful studies and experiments demonstrating wave properties of light before the scientific elite of France made him a hero of the scientific avant-garde challenging the entrenched authorities in the debates about the nature of light. More importantly for Fresnel, the experiments demonstrated the theoretical possibility of his approach to new lighthouse technologies: the secret was in the lens, not the light source.
Fresnel’s design, based as it was on mathematical precision, required massive lenses carefully constructed through the ordering and placement of each individual piece of glass. Defects in the glass or parts placed at a wrong angle would lead to a scattering of the light and a loss of the focusing power that made the lens work. The craftsmanship required for lens construction resulted not only from the nature of the precision needed for the glass but also from the effort required to cut glass of this size. The introduction of steam power meant lathes could operate faster, yielding more lenses and more lighthouses equipped with the Fresnel system.
Once made, these lenses needed to be installed—a feat that required transport of delicate glass parts to remote ends of the country (and eventually the world), installing them in giant towers often placed precariously on a nearly inaccessible outcropping of rocks, and into a room scores of feet in the air. And yet somehow it all worked.
New class of engineers
Levitt presents Augustin Fresnel as an unlikely hero of this era. But Fresnel was a product of a radical shift in education happening in France in the 19th century. The creation of the new elite engineering schools in France made possible this rise from obscurity to national hero. Indeed, Fresnel took part in a larger national experiment that not only focused on technical training; it also tied engineering to governance and political power. Engineering for the state was also engineering of the state, a fact embodied in the perhaps even more unlikely rise of a young ballistics and artillery engineer named Napoleon Bonaparte to ultimate power in France (and much of Europe).
France deployed its engineers across the country in the service of the state— building infrastructure, surveying, training its military. Fresnel was one of this new class emerging in France (and indeed spent most of his time overseeing the construction of roads and other infrastructure, a job he absolutely despised). Being an engineer meant the state supported you, but it also meant you supported the state. As Fresnel’s new system found its way across the country, the light stood as a glowing example of French engineering and not just the genius of Fresnel. Indeed, installation of his lighting system at expositions of engineering in Paris (following Fresnel’s early death attributed to consumption) was taken to be an example of the power of France and its new engineers.
Lighthouses and Fresnel’s lens meant more than just safety for sailors; they constituted physical symbols of the expansion of commerce. The loss of a ship of happy travelers would have been tragic indeed. But the loss of a commercial fleet was expensive and disruptive to the national economy. Lighting the coast did not happen all at once; the lighthouse commission in France set priorities based on safety and strategic importance of the ports. Once the coast was lit (a massive and thorough undertaking by the French government, overseen by its engineers), lighthouses with Fresnel lenses began appearing in more remote—but equally strategic— locations: Corsica, Algiers, and Gibraltar among them. Lighthouses equipped with Fresnel lenses became part of commercial infrastructure.
Though Levitt spends much time documenting the resistance by some people and groups in the United States, when the lenses did arrive, they, too, were prioritized by their commercial importance. When gold was found in California at the close of the 1840s, it took a mere two years for San Francisco to boast new lighthouses using Fresnel lenses—an amazing feat given the distance from the center of manufacturing in France and the demand for lenses at the time.
In a telling tale of the strategic importance of the lighthouses and the power of these lenses, Levitt documents the efforts taken by the Confederacy at the start of the U.S. Civil War to impose a blackout along the southern coast. Remarkable, however, is the unbelievable care taken by state authorities (and even raiding parties) at the onset of war to carefully dismantle the lenses for safekeeping in hidden locations. Although some lighthouses saw their hardware simply smashed into a thousand unusable bits, much of the hardware remained undamaged (if far from its original location) and found its way back to Federal authorities at the end of the war.
Lessons for today
In her telling of the historical emergence and evolution of the modern lighthouse, Levitt digs deep into the technical construction of the first lenses and the methodical placement of lamps as they began to dot the coasts of empires big and small. But for all of the detailed historical description that populates her careful depiction of the Fresnel lens and its production in the 19th century, the book lacks a compelling narrative or even larger context within which this feat can be fully appreciated. Despite that absence (or perhaps in lieu of Levitt’s efforts), it is possible to draw some ideas from the book that may compel further conversation.
To fully understand what happened as these events unfolded and why it was so amazing, it is necessary to understand the scientific debates and technological challenges, as well as the pressing social and political and economic needs, of the time. To focus on any one of these elements without the others is to miss the much bigger picture this story is trying to tell.
The lens was just one part of a larger system; and in this regard the lighthouse is not a singular object, but part of a larger infrastructure of the state. When viewed from this perspective, it is easier to understand why France and the United States took such different approaches to the installation of these new technologies. In fact, it is not only easier, but essential for taking one of the main points from this book. In the largely centralized and technocratic state of France, the institutionalization of new lighthouses equipped with Fresnel lenses followed a “rational plan.” In the United States, factors such as the role of open markets, the status of scientists and engineers, and the reluctance to use (or opposition to) federal funding of large state projects left efforts to update the then-current system stuck in a bureaucratic trap and with inadequate funding.
Sound familiar? It should—and that is one of the main lessons of this book. Just think about the debates in the United States today over nuclear power, funding of research, and the role of the university versus the corporation as engines of innovation. The landscape today did not suddenly appear. Treating this terrain of comingled science, technology, politics, and cultural identity with more attention could go a long way toward helping policymakers and stakeholders to appreciate the unique character of these systems. And a better understanding of how these systems came to be can go a long way toward helping us to create alternative possibilities for moving forward.
In all, A Short Bright Flash is a wonderful reminder of just how much effort goes into the construction of the nation’s largely invisible (and crumbling) infrastructure. Perhaps more discussions of this sort might yield a deeper appreciation for the efforts that need to be made to build and maintain an infrastructure for the 21st century.
Jody A. Roberts (jroberts@chem heritage.org) is director of the Center for Contemporary History and Policy at the Chemical Heritage Foundation in Philadelphia, Pennsylvania.
Book Review: The end of the wild, wild Net
Regulating Code: Good Governance and Better Regulation in the Information Age by Ian Brown and Christopher T. Marsden. Cambridge, MA: MIT Press, 2013, 288 pp.
Rex Hughes
Who regulates the Internet? A decade ago, posing this question would have been considered heretical by the majority of those people and groups charged with maintaining the core principles and norms that govern the Internet. However, as Ian Brown and Christopher T. Marsden succinctly chronicle in Regulating Code, the Internet no longer operates in an unregulated space, thanks to an expanding web of technological innovation, market power, legislative agendas, pressure groups, and regulatory authorities. In writing what can be broadly categorized as an Internet regulatory scholar-practitioner book, Brown (a computer scientist) and Marsden (a lawyer) seek to improve the study and practice of Internet regulation by integrating more directly the technical principles and social norms associated with the Internet since its early ARPANET (Advanced Research Projects Agency Network) days. The authors also look to public-private mechanisms of “co-regulation” as necessary means of achieving better Internet regulation.
Given the increasing need for more technically informed regulatory analyses and practices that stay true to the Internet’s unique principles and norms, this book makes a significant contribution to the study of 21st century Internet regulation. In casting their interdisciplinary technical-legal gaze over the past 10 years of major battles arising in the United States and the European Union (E.U.) over Internet policy, Brown and Marsden show how even the most well-intentioned Internet regulation can experience major failure when its principal architects lose sight of what the Internet is really about.
In addressing the book’s central thesis of how to devise a more robust analytical framework for producing better Internet regulation, the authors make their case via five well-researched case studies. The first three case studies— in chapters titled “Privacy and Data Protection,” “Copyrights,” and “Censors”—focus on issues of what the authors consider “fundamental rights with economic implications.”
Beginning with privacy and data protection, the authors chronicle several of the most salient regulatory clashes in the United States and the European Union since 2002. As the authors note, the European Union in particular has been debating data protection policies for 20-plus years, and they argue that current regulatory logjams can best be alleviated if Brussels lawmakers and regulators apply technical engineering principles such as “interoperability” when constructing a new regulatory regime.
Brown and Marsden argue for a similar technically informed approach to Internet regulation in their case study of copyrights. They say that U.S. and E.U. lawmakers made a substantial error in trying to construct a digital copyright regime around the premise of “regulating the machine” rather than the market behavior made possible by global network distribution of digital intellectual property. Further, lawmakers failed to adequately allow for future technological and business innovation when authoring the Digital Millennium Copyright Act (DMCA) and the European Copyright Directive (ECD). Thus, both laws fell well short of their framers’ goal of constructing a regulatory regime that balances the power of rights holders with a new generation of digital consumers, or “prosumers,” as Brown and Marsden like to call them. Failing to understand emergent prosumer behavior (in what Jonathan Zittrain, a professor at Harvard University and an expert on Internet law, calls the “generative Internet”) made the public policy goal of reaching a proper balance between the rightsholder and the prosumer in either the DMCA or ECD nearly impossible.
In their case study of censors, the authors chronicle the ongoing struggle that U.S. and E.U. authorities have had in trying to impose limits on sensitive Internet content. They cite the WikiLeaks saga as an instance where the U.S. government failed to block the Internet distribution of over 250,000 classified documents.
Brown and Marsden selected the final two case studies, presented in chapters called “Social Networking Services” and “Smart Pipes,” because they provided “the most innovative platforms to develop new markets and protect those fundamental rights.” Regarding social networking services such as Facebook, LinkedIn, and Google+, they make a convincing case that U.S. and E.U. competition authorities have failed in their mission to design a new regulatory regime that sufficiently balances the interest of providers of these services and their customers. They see severe deficiencies in both the objectives and approach of U.S. and E.U. regulators. Although the authors admit that the rapid innovation associated with social networking services make traditional legal definitions of transparency and enforceability difficult, they call attention to a growing number of areas that leave a new generation of prosumers without adequate protections. Once again, the authors call upon transatlantic regulators to apply the interoperability principle to provide for greater user transparency and ownership.
In their case study of smart pipes, the authors confront the thorny public policy question of net neutrality. Here again they show the moral and economic hazard that national regulators create when they allow Internet service providers to deploy so-called smart filters that risk breaking the Internet’s longstanding end-to-end principle. In the authors’ words, “The pace of change in relation between architecture and content on the Internet requires continuous improvement in the regulator’s research and technological training.”
Brown and Marsden are to be commended for tackling a complex dynamic topic in a mere 267 pages. Their case studies offer clear empirical data that demonstrate that the future of the Internet is indeed intertwined in the high-priced regulatory and lobbying battles in Washington and Brussels. In applying their interdisciplinary technical-legal analysis and in-depth knowledge of historic Internet principles and norms to their analyses, they show the utility of bringing a technically informed interdisciplinary approach to the study and practice of Internet regulation. They also signal the need for a more balanced approach between European-style co-regulation and U.S.-style self-regulation. Had such a technically informed balanced approach been brought to bear with the creation of the DMCA and the ECD (two of the most consequential regulatory acts for the Internet economy), how many millions of dollars in contentious rights litigation could have been avoided?
The same principle holds true for the transatlantic data protection debates of the present. How many policymakers truly understand the technologies they regulate? What are the universities and professional bodies responsible for regulatory education and training doing to alter this critical calculus? Regulating Code is a step forward in challenging the core assumptions that guide the principal stakeholders involved in crafting 21st century Internet regulation.
Nobody’s perfect
But even as the book succinctly accomplishes its main analytical goals and normative aims, there are a few areas open for improvement. Although the book is not positioned as a pure scholarly work, the chosen methodologies and theoretical frameworks applied in the case study analyses could have benefited from some further explanation and context for readers not familiar with orthodox theories of computer science and regulatory studies. In some sections of the book, case study issues too easily bleed into one another. For example, there are elements of the chapter on social networking services that could have been integrated with the chapter on privacy and data protection (a classic problem when confronting such a converged set of technologies and issues).
Also, even though the book is written from a European-rooted transatlantic perspective, it would have been helpful to have had some additional discussion on how other non-European authorities are confronting similar issues. The so-called BRIC countries (Brazil, Russia, India, China) will be home to much of the next billion-plus Internet users. How are these countries helping or hindering the classic transatlantic club of Internet regulation? Perhaps issues for a future Brown-Marsden collaboration.
In summary, Regulating Code makes a significant contribution to Internet regulatory studies, and it would benefit anyone seeking a thorough account on the rise of the Internet regulatory state since 2002. For better or worse, the unregulated Internet is no more. As has been historically the case with other disruptive technological innovations that become mass communications mediums, the Internet is now enmeshed in some of today’s most pitched public policy battles. However, as Brown and Marsden skillfully remind us, keeping the public Internet true to the principles and norms that its ARPANET founders sought to embed in its core protocols and applications will require more technically informed regulatory stakeholders. Increasing technically informed analysis in the quest for better Internet regulation will require institutional change in both universities and regulatory bodies. And although the book does not offer an exact roadmap for making such institutional fixes, it does show the advantage of interdisciplinary collaboration when confronting the complex human-machine systems that span the multiple jurisdictions and cultures of Internet cyberspace.
Rex Hughes (rex.hughes@cl.cam.ac.uk) co-directs the Cyber Innovation Network at the University of Cambridge Computer Laboratory and is a visiting professor at the University of Toronto Munk School of Global Affairs.
All Adaptation Is Local
Attention to the political context of coastal communities will be necessary if the United States is to improve on its current storm-by-storm approach to climate adaptation.
Decades of climate science and years of public policy research came together last year on the losing side of a 4-1 vote approving a rural development along Virginia’s Chesapeake Bay shoreline. For anyone working on adaptation to rising sea level, that one decision crystallizes the issues involved.
A developer wanted to put a few hundred homes, a $40 million hotel, 34,000 square feet of retail, and a marina on a piece of soggy coastal land at the end of a peninsula. The land had been designated for conservation/open space use, and the developer needed the Board of Supervisors to change that zoning and allow him to build along the shoreline rather than on the adjacent upland parcel that lacked waterfront views and access.
The developer claimed that the planned community would, “…create significant employment, provide significant economic stimulus and tax base, honor the Maritime Heritage of Northumberland County, honor local architecture, promote tourism for all of Northumberland County, provide educational programs to school children and all residents, provide services to the retirement population and other residents of the county, and provide waste water capacity to some neighbors.” These hyperbolic claims have been made for decades by people seeking to build on coastal land, and now we’ve ended up with pretty ordinary coastal developments.
For decades, developers and shoreline communities alike have seen these coastal projects as cash cows, producing the highest-value homes and generating the highest real estate taxes. Now, however, sea level rise threatens to turn these developments into money pits for localities, because future flooding mitigation costs will exceed property tax revenues.
Our group, Wetlands Watch, argued against this development proposal, saying that even at historical rates of sea level rise (measured as 1.5 feet per century since monitoring began in 1927), the project would be increasingly subject to flooding from above by storm surges as well as flooding from below as the perched water table rose into the development. Projected sea level rise at more than twice current rates would hasten this outcome. Given that a house will last 100 years or more with proper maintenance, we argued that the board of supervisors should take these centennial rates into account and calculate the taxpayer liability for adaptation measures required by this subdivision in the future. We argued that the Board of Supervisors needed to conduct a “life-cycle” cost assessment before proceeding.
We argued, using all the facts available from the body of work on sea level rise effects, and captured a solitary vote, losing the decision to the alignment of interests that have fueled coastal development unabated since World War II.
I am sure the county supervisors read the letter from the developer promising that utopian future emerging from this subdivision. I doubt that the supervisors had read the latest report from the Intergovernmental Panel on Climate Change (IPCC). Nor had they used any of the proliferation of adaptation “tool kits” being cranked out for coastal communities by academic institutions and government agencies, participated in the numerous Webinars dealing with sea level rise adaptation, attended the National Oceanographic and Atmospheric Administration (NOAA) workshop on coastal resilience, or read the U.S. Global Change Research Program’s Synthesis and Assessment Project 4.1 Report, Coastal Sensitivity to Sea-Level Rise: A Focus on the Mid-Atlantic Region.
These are regular people, with full-time jobs outside of government, whose main task on the Board of Supervisors is keeping their municipal government running through the end of the fiscal year. Their time and ability to seek out the growing body of work on sea level rise adaptation are limited. Unfortunately, the ability or interest of those producing this body of work to bring it down to local-level decisionmaking seems just as limited.
Many of those involved in the science and public policy of climate change envision a decision process in which research results carry the day and drive action, and national-scale data underlie uniform national policy. Between that dream and the reality of development decisions such as this one, democracy rears its ugly head. Local elected officials trend less toward Nobel laureate climate scientists and more toward your Uncle Bobby with his 2 years of community college and 15 years of running a wholesale plumbing business. Oh, and by the way, Uncle Bobby and his colleagues on the county board also happen to be in charge of adaptation decisions regarding climate change effects such as sea level rise, a condition of reality that the Nobelists haven’t managed to integrate into their climate models.
Local governments control private land-use decisions, issue business permits and occupancy permits, fund and build secondary roads, build and run schools, operate fire and emergency services—in short, control most of the factors that allow people to live and work on the land. Frustratingly for those who seek uniform adaptation policy, few federal regulatory statutes currently reach through to a local government’s land-use decisions. Only federally mandated floodplain plans, emergency management plans, wetlands permitting, and a handful of other statutes affect those decisions. Even more frustrating to those of us seeking restrictions on coastal development, local governments have wide discretion in implementing and allocating funds from an array of federal and state programs dealing with economic development, transportation, health and welfare, and the like. Without precautionary restrictions on implementation, localities can spend program funds without regard for future climate effects that are all but inevitable.
True, some of those state and federal laws and regulations have explicit prohibitions and restrictions about using the programmatic authority or funding in high-risk areas. For example, federal programs require many precautions and analysis of alternatives if a proposed project is in a 100-year floodplain. However, no federal law or regulation requires localities to anticipate future conditions in these precautions. Estimates of risk (i.e., the area of the 100-year floodplain, the intensity of storms, the recession rate of shorelines, and so on) are retrospective and based on a record of past occurrences. The only mention of future climate change risk in any operational federal program is an engineering guidance by the U.S. Army Corps of Engineers that requires that agency to use a prospective sea level rise formula when constructing military buildings along the tidal coast.
So when those county supervisors were considering the proposal to develop that parcel of soggy coastal land, only a citizens’ group and a few environmentalists were saying “No.” All the state and federal agencies involved in that development saw no problem with the proposal and were blind to any danger from sea level rise.
The Veterans Administration and the Department of Housing and Urban Development will guarantee any mortgage in the subdivision, regardless of the home’s elevation. The county’s Community Development Block Grant funds from the U.S. Department of Commerce can be used to pay for infrastructure in the community. The U.S. Department of Transportation will pay for any transportation segments eligible for federal cost-share payments. The Environmental Protection Agency will permit the sewage plant, lacking any authority to deny a permit based solely on future flooding risk. Even the National Flood Insurance Program run by the U.S. Federal Emergency Management Agency will offer flood insurance to every homeowner in this development based on current, not projected, measures of mean sea level to define floodplains and compute risk and premiums.
On and on, every federal and state government program aligns with coastal development interests, as if nothing has changed, to continue the status quo. Every federal and state agency program that touched this development proposal on soggy coastal land gave it a green light.
For some agencies, such as the U.S. Department of Commerce, this situation is especially puzzling. On one side of Commerce, in NOAA, much time and effort is spent in educating coastal communities about the need to adapt to sea level rise and other climate effects. On the other side of Commerce, the Economic Development Administration (EDA) keeps doling out development dollars to coastal communities without any mention of sea level rise, no requirement for evaluating future climate change impacts, and no restrictions on the use of these funds based on those future impacts.
When the county board considers a development proposal, Uncle Bobby can either take a position based on a range of climate-model projections from one part of the Department of Commerce, or he can take a position based on the willingness of another part of the Department of Commerce to provide unrestricted funding for the proposal. He can upset the developer and perhaps anger his neighbor who owns the land in question, because of a climate tool kit coming out of NOAA. Or Uncle Bobby can avoid acrimony and agree with the EDA that this development is an idea worthy of federal taxpayer investment.
In current efforts to slow coastal development, it is folly to expect localities to go against the developer’s promise of jobs, a higher tax base, and more tourism when these positions are supported and underwritten by the state and federal governments. It is folly for anyone to expect an outcome different from the 4-1 decision made by the county board on the development we were opposing.
A thought experiment
Imagine for a moment that the county Board of Supervisors was directly exposed to the body of work on sea level rise. Imagine a metaphorical conversation between the Nobel laureates at the IPCC and your Uncle Bobby, county supervisor. What if Bobby agreed with the Nobelists and with NOAA and all the agencies issuing warnings, and felt that climate change was real and needed to be accommodated in local government policy?
Bobby would be presented with a range of projections, reflecting a range of possible responses to climate change by global-scale natural systems and a range of actions to be taken by the global community in reducing greenhouse gases. Should he look at the latest Summary for Policymakers report from the IPCC, he could clearly see for himself what to expect:
“Global mean sea level rise for 2081-2100 relative to 1986–2005 will likely be in the ranges of 0.26 to 0.55 m for RCP2.6, 0.32 to 0.63 m for RCP4.5, 0.33 to 0.63 m for RCP6.0, and 0.45 to 0.82 m for RCP8.5 (medium confidence). For RCP8.5, the rise by the year 2100 is 0.52 to 0.98 m, with a rate during 2081–2100 of 8 to 16 mm yr (medium confidence). These ranges are derived from CMIP5 climate projections in combination with process-based models and literature assessment of glacier and ice sheet contributions (see Figure SPM.9, Table SPM.2).”
Recognizing that Uncle Bobby and his peers are unlikely to act on the basis of that language (or even make any sense of it), a communications expert from NOAA will tell him to expect between one and three feet of sea level rise globally by this century’s end. However, the expert will also tell him that this parcel is located at a specific point on the globe and that the rate and range of sea level rise there, on that property, involves a range of other factors.
Virginia is experiencing the highest measured rate of relative sea level rise on the Atlantic coast, with land subsidence contributing as much to the gradual inundation as the actual rising seas. Also at issue is the apparent slowing of the Atlantic Meridional Overturning Circulation, known to Uncle Bobby as the Gulf Stream. All of this taken together leaves the soggy parcel with between 4 and 6 feet of relative sea level rise expected by the end of this century.
What spoiled policymakers have come to expect from the science and technology (S&T) community is certainty, not a range of estimates. (The S&T community is complicit in these expectations, having sought over the years to broaden its involvement in and impact on public policy decisions by promising useful information in return for research support.) Should the county board ask the S&T community to help pick the right number within that 4- to 6-foot range, they would be told that it is a policy decision, not a scientific one. Further, the S&T community would say, where sea level rise eventually ends up within this range of estimates is complicated, since we are dealing with large global systems. Also, eventual effects will be determined by larger policy decisions such as whether greenhouse gas reduction actions will be taken by Beijing and . . . on and on into the nuanced body of work on climate change effects and mitigation.
For the local government officials, picking the “right” number is critical. Do they act on this development proposal or not? If they deny the development, can they defend their actions, possibly in court, since consideration of prospective sea level rise effects is not in any underlying legal authority? If they approve it, do they require additional freeboard (elevation of living space an additional increment above the minimum required by floodplain ordinances) on structures in this development? At what elevation do they set the freeboard? Do they need to amend their floodplain ordinances or building codes to incorporate these sea level rise projections? How do they design utilities and road segments in this development to address projected sea level rise? What engineering standards do they use for that work?
As this conversation drags on, we’ve again lost Uncle Bobby, who realizes that he will be long dead before anyone can narrow the uncertainty surrounding this development proposal. Each adaptation decision facing local government involves additional political effort and financial cost.
Although that additional cost may be a fraction of the costs avoided in the uncertain future, it is an utterly certain price paid by today’s taxpayers, all of whom vote in Bobby’s next election campaign.
A recent conversation with a storm water engineer in a coastal Virginia city illustrates these challenges to adaptation. The engineer was in charge of a $20 million contract for installing a storm water line. The low-lying city is challenged by sea level rise and the elevation of shallow groundwater tables. The engineer asked the contractor what it would cost to build the system to accommodate the current (1.5 feet per century) regional rate of sea level rise. The answer was an additional $5 million for pump stations and related hardware.
The engineer knew that it was not politically possible to ask for a 25% increase in the cost of the project, all borne by city taxpayers, based on projected effects that would occur decades hence, years after the current city council members had retired. Lacking any requirement for sea level rise adaptation by state or federal environmental agencies, any engineering guidance, or any additional cost-sharing for the adaptation actions, the project went in the ground as originally designed.
The challenge
In fairness, much of the challenge lies not with climate scientists narrowing the range of estimated effects, or even in communicating those risks more effectively. The challenge lies in getting policymakers adapted to living in the new reality of climate change, when they never even adapted to the old reality of gradual sea level rise. In this new reality, decisions must be made on the basis of estimated effects with wider ranges of variability or even using scenarios rather than quantifiable projections. The “spoiled policymakers” referenced above must now live with uncertainty, gradually moving toward more-precautionary strategies as they learn over time from the failures of early, smaller, incremental adaptation approaches. They must learn to live in a world in which the past is no longer prologue and retrospective views of past conditions no longer provide guidance for the future. They must extend their time horizons well beyond the next election.
These adjustments will be hard, especially hard given our lack of experience with climate change impacts such as sea level rise. For most of the past 5,000 years, we have enjoyed— on geologic time scales—atypically stable climate and sea levels. As a result, we have nothing in our literature, law, architecture, engineering, or any other discipline that addresses changes of the order that we will be experiencing in the future. In western Judeo-Christian culture we have two references to what we face: the tale of Noah’s Ark and a children’s story about a Dutch boy preventing the failure of a dike. Not much on which to base major social change. (Although to be fair, the Dutch do take the preservation of their dikes very seriously.)
This work will be made harder by the expense and disruption it will generate. The work we envision will be expensive: learning prudent precautionary levels of adaptation the hard way, storm by storm; buying out properties, even whole communities; paying full actuarial rates on insurance for the coastal risks we face; stacking up rock, sand, and concrete— millions of cubic yards of concrete—to block the waves; withdrawing public support for entire classes of coastal activities, stranding property owners along the shore; and enduring expensive lawsuits as we take these steps, struggling to shape law and policy to fit the new reality. All of this over coming decades will cost trillions of dollars. There will be big losers and, perhaps, a few winners as we unwind our existing relationship with the shore. Of course, doing nothing will cost even more and make everyone losers in the end.
Progress on adaptation will also be conditioned on the reaction of the private sector, a fragmented confederation of interests that is largely being left outside of adaptation conversations. Attempts have been made to include them at higher levels in the dialogue, with large corporations, global reinsurers, and the like expressing concern at national and international conferences. At Uncle Bobby’s level, with the local chamber of commerce or regional business association, there is little to no private-sector voice in support of caution.
As a result, when adaptation measures are discussed, the private-sector reaction at the local level is driven by those who are directly and immediately affected, a sector of businesses dominated by real estate sales, development, and contractor interests. Most of these companies have planning horizons that extend into the future precisely to the point of sale of a property. Any actions that affect the cost of construction of the property or lower the appeal and price of the property will be opposed. Falling into this category of action are most prudent sea level rise adaptation options such as additional floodplain restrictions, properly priced private and federal flood insurance coverage, and public identification or designation of future flooding areas. Actual restrictions on development or redevelopment in those future flooding areas will be strenuously opposed. This has been illustrated in negative reactions to initial attempts at sea level rise adaptation, from the Outer Banks in North Carolina to the San Francisco Bay region of California.
Acting against all of this seemingly insurmountable resistance is the inevitability of the changes we face along the coast. Gradually the private sector will shift its position as risk gets priced into coastal communities, actuarial reality overcomes inertia, and impacts pile up. Coastal communities will find themselves inundated with costs, complaints, and water—lots of water. The public’s relationship with the shoreline will shift from “live on the water,” to “live with the water,” to “move away from the water and come back for a visit from time to time.” Government programs at all levels will withdraw support for further coastal development. With each storm and recovery, low-lying communities built along beaches, strand roads, and at the end of peninsulas will be left on their own and slowly fade away. The life-cycle cost of our changed relationship with the shore will finally be calculated.
This is the messy reality we face, with Uncle Bobby and his peers in charge of adaptation decisions across hundreds of coastal communities. This is the outcome that looms behind the rationality of tool kits, Webinars, conferences, and expectations by Nobelists that facts alone can change behavior in time to avoid the worst.
Clark Williams-Derry of the nonprofit Sightline Institute lays out our challenge well:
“Convincing people that you’re right about an issue— say, the scientific consensus about the threat posed by global warming—can seem vitally important, but in the end may be somewhat beside the point. In the long run, you have to move the debate beyond beliefs, and into incentives: lining up the economic and social incentives such that the right choices are the easy, natural ones. To do that, we need smart and effective policies. Appeals to people’s reason may help, but rational belief alone won’t carry the day.”
We’re back to the decision on that soggy piece of coastal land in rural Virginia and our misalignment of policies and incentives that made that 4-1 decision the easy, natural, and even rational one. We need to look at these individual decisions, pick them apart, speak to local decisionmakers, develop those “smart and effective policies,” and then generate support for them in coastal communities, one by one.
For years, we have acted in ignorance, before we could clearly see the permanence of coastal change. Or if not ignorance, then denial, as we dumped sand on beaches and moved lighthouses and historical homes farther inland from the eroding coast. Today we seem to be acting out of indifference, believing in our ability to continue as we have for decades, hoping all of this is not true. Soon we will be acting out of inevitability, making different choices because there is no other option.
Yet each storm presents a teachable moment, an event that causes those who live on and make decisions about the local lands to rethink where their true interests lie, and gives ever-stronger voice to those who are advocating for adaptation. The gamble we have engaged is that our short-term interests will outweigh the long-term costs of failing to adapt. Storm by storm, the odds on this gamble will grow longer, but meanwhile how many more new coastal developments are going to be approved and how many old coastal developments are going to be drowned?
The trick is to move more rapidly toward the inevitability of action and minimize the greater expense and disruption that comes from having started too late. That will require many hours of conversation at the local diner’s corner booth between Uncle Bobby, the Nobelists, and government policymakers, in hundreds of municipalities along the nation’s coasts. It will also, unfortunately, involve far too many more storm and flooding events as conversation starters.
William “Skip” Stiles ([email protected])is executive director of Wetlands Watch, an environmental nonprofit that has been working statewide in Virginia for over six years to help localities adapt to sea level rise. Before this work, he spent 22 years in a number of staff positions in the U.S. House of Representatives, as chief of staff to the late Congressman George E. Brown Jr., and as legislative director for the House Science Committee.
A New Era
This edition of Issues in Science and Technology marks the beginning of a new era. Arizona State University is joining with the National Academies and the University of Texas at Dallas as a co-publisher. ASU’s participation will be led by its Consortium for Science, Policy, and Outcomes (CSPO), and CSPO co-director Daniel Sarewitz will assume the title of Editor. We are thrilled by the opportunity to work with ASU, CSPO, and Dan.
During the past ten years under the leadership of President Michael Crow, ASU has been among the fastest growing and most innovative universities in the country. We are all familiar with the rhetorical device in which a speaker announces that a particular program or institution has three admirable goals but then explains that the goals are inherently contradictory so that it is necessary to choose only two. President Crow must have been checking his email at that point in the speech because ASU has managed to achieve the seemingly incompatible goals of enhancing excellence among faculty and students, broadening participation and achievement of underrepresented groups, and reducing the per student cost of education. At the same time, he has instituted a hurly burly restructuring of academic programs to create truly interdisciplinary and transdisciplinary approaches to vexing scientific and societal problems.
CSPO, which was founded at Columbia University in 1998, moved to ASU in 2003 and has grown to become one of the largest and most diverse science and technology programs in the country. Like many other ASU programs, it is the antithesis of an academic silo. Its core faculty is drawn from many disciplines, and it not only works actively with many ASU departments and institutes across the sciences and engineering, humanities, design, and law, but has active collaborations with domestic and foreign universities, with science museums, and with nongovernmental organizations.
Dan Sarewitz was the founding director of CSPO and continues as one of its intellectual leaders. Dan’s most recent book is The Techno-Human Condition (MIT Press, 2011; co-authored with Braden Allenby). Since 2009 he has also been a regular columnist for Nature magazine. Other published work includes Frontiers of Illusion: Science, Technology, and the Politics of Progress, (Temple University Press, 1996), Living with the Genie: Essays on Technology and the Quest for Human Mastery (Island Press, 2003; co-edited with Alan Lightman and Christina Desser) and Prediction: Science, Decision-Making, and the Future of Nature (Island Press, 2000; co-edited with Roger Pielke, Jr., and Radford Byerly, Jr.). Dan brings to Issues a probing and skeptical mind, a sophisticated knowledge of science and technology policy, a determination to rigorously assess the impact of science and technology, and a relentless commitment to challenging the science, engineering, and medical communities to take seriously their social and political responsibilities.
The infusion of fresh ideas and new energy will be a boon for Issues. Planning has already begun on an improved website that will be updated regularly with news items and links to relevant additional information, a calendar that will list important upcoming events, an expanded job board, links to other networks of which ASU and CSPO are a part, such as the Future Tense collaboration with the New American Foundation and Slate magazine. Discussion has also begun about a redesign of the magazine. ASU shares our commitment to presenting art that uses, explores, and challenges science and technology, and we will be looking for ways to make the art and text more engaging and more effective.
What excites us most, however, is the intellectual boost that Dan and his ASU colleagues will bring to the magazine. Issues has published many articles by ASU faculty over the years, and we will continue to do so. Even more important will be their network relationships that span the nation and the globe and that will help us find new authors that will bring rigor and creativity to addressing a wide range of science and technology policy concerns.
ASU helped us in the past in an experiment that paired young scientists with professional writers to produce articles that applied a narrative structure to policy topics. We look forward to expanding that experiment in the future. Lee Gutkind is directing a second round of the training program called To Think, To Write, To Publish, and we are planning to publish some of the articles that emerge from that program. ASU’s Center for Science and the Imagination aims to stimulate collaboration among scientists, engineers, artists, and creative writers. One current project links scientists and engineers with science fiction writers to encourage the production of science fiction that is founded on real scientific and technological trajectories. We plan to publish some of the work that emerges from that effort.
Issues is very fortunate to have such a rich institutional foundation. The National Academy of Sciences, National Academy of Engineering, and Institute of Medicine incorporate a long tradition of excellence and service to the nation. They have earned their reputation as the scientific establishment and respected advisors to government. The University of Texas at Dallas and Arizona State University bring the fresh ideas and new approaches of what Michael Crow calls the New American University. These institutions are not completely outside the establishment; they have their Nobel laureates and Academy members. But they are not content to be mere imitations of the nation’s traditional elite universities. They are developing a new institutional model less dependent on traditional disciplinary structures and more open to educating a broader and more diverse student population. They are at the cutting edge of a new direction in higher education, and we look to them for new approaches to science, technology, and health policy. This mix of excellence and experimentation is an ideal recipe for a stimulating and influential policy magazine.
Forum – Fall 2013
Energy for global development
In “Making Energy Access Meaningful,” Morgan Bazilian and Roger Pielke Jr. (Issues, Summer 2013) raise important questions about what we mean by access to electricity. As they note, the World Bank and its 14 partners who designed the Global Tracking Framework (GTF) to measure progress toward the three goals of the Sustainable Energy for All (SE4ALL) initiative, have come up with a five-tier definition of access. They argue that even the GTF’s top Tier 5 household electricity access, which includes the ability to use high-power appliances, translates into a comparatively low level of household consumption at just 2,121 kilowatt- hours (kWh) per year.
The multi-tier framework was developed precisely to counteract a tendency in some quarters to set the access bar too low by counting a solar lantern or a small solar home system as equivalent to 24/7 grid power. By differentiating among these solutions, the multi-tier framework allows off-grid solar to be acknowledged as a step toward but not the final destination of energy access.
A comparison of minimum household electricity consumption of 2,121 kWh a year at Tier 5 with average household consumption shows it to be about right. It’s about half of the average household electricity consumption in Greece (3,512 kWh), Spain (3,706 kWh), Germany (3,788 kWh), South Korea (4089 kWh), Bulgaria (4,650 kWh), and Japan (4,826 kWh) and nearly the same as that in Italy (2,527 kWh). It is about twice the level of power consumption of connected households in India (901 kWh) and China (1150 kWh).
The developed-country figures cited by the authors refer to overall per- capita electricity consumption for residential and nonresidential purposes, including that for cooking, productive uses, and community requirements. This cannot be compared with GTF benchmarks for household residential electricity consumption. To reflect these other energy needs, the GTF report includes a framework for measuring access to energy for cooking. It also acknowledges the importance of access to energy for productive uses and community applications and commits to developing similar multi-tier frameworks for them as well.
I share the sense of justice that animates the authors’ contention that an electricity access goal of modest ambition would reflect a “poverty management” over a “development” approach. But their contention is misplaced. The level of ambition for SE4ALL goals in each country needs to be defined by governments, in consultation with civil society, entrepreneurs, developmental agencies, and the public. The GTF’s multi-tier framework for access seeks to facilitate this process so that each country can define its own electricity access targets.
The chasm between high ambition and unfeasible goals must be filled by pragmatically designed intermediate steps. Such intermediate steps include interventions that would allow children to study at night, village businesses to stay open after dark, and rural clinics to provide basic services to those who heretofore have had none. These intermediate steps take us closer to the ultimate goal of full energy access. They are worth pursuing, and they do not exclude pursuit of the ones that lie beyond them.
Morgan Bazilian and Roger Pielke Jr. get the essential point right: that meaningful access to modern energy services must go beyond lighting to other productive uses, such as water pumping for irrigation. Like many observers, however, they seem daunted by the scale of investment required, which they estimate at $1 trillion to achieve a minimal level of energy access and 17 times more to reach a level comparable to that in South Africa or Bulgaria.
Those numbers are very large compared to the amount that might plausibly be available through conventional development assistance, but that is the wrong lens to use. Electricity is a commodity that even very poor people are willing to pay for. Indeed, they are already paying more than $37 billion a year for dirty, expensive fuels (kerosene for lighting and biomass for cooking), according to an International Finance Corp. report. With the right financing, solar energy in rural areas is cheaper than these sources or diesel fuel for generators. The availability of energy is a spur to economic development that can quickly become self-sustaining.
Providing access to modern energy services should thus not be seen as a burden for governments to bear, but as a multi-trillion-dollar business opportunity, and there is plenty of capital available for such investments, prudently made. The best way for the world, through national governments, “to ensure that the benefits of modern energy are available to all” is to create safe environments for private investment and to use limited public funds to reduce the political risks to investors and the cost of borrowing. Facilitating this pathway is one of the principal objectives of Sustainable Energy for All, the farsighted initiative launched by United Nations Secretary-General Ban Ki-moon and now co-led by World Bank President Jim Yong Kim.
AN IMPORTANT GOAL FOR THE COMING FEW YEARS IS TO DEVELOP A TRUE SUPPORT SYSTEM SO THAT COMMUNITIES, UTILITIES, AND MINISTRIES CAN COUNT ON THESE MINI-GRIDS TO DELIVER AN EXPANDING SET OF SERVICES.
The central message of the paper by Morgan Bazilian and Roger Pielke Jr., at least to me, is to highlight the explosion of demand and the diverse modes of energy consumption that are possible and should be anticipated as energy access (and in particular electricity access) is expanded. This is an important observation that ties together many stories: (1) the value of energy access for both basic services and economically productive activities; (2) the need to analyze and to plan around unmet demand, so that a small taste of energy services does not lead to unrealized expectations and then dissatisfaction; (3) the complexity of building and planning an energy system capable of providing services reliably once the “access switch” has been turned on.
The question is not the value of energy access or the need for interactive “organic” planning of the emerging electricity systems to be as resilient as possible against surges in demand, technical problems in delivering electricity, or even the problems of managing the market (payment, theft, etc.). These are key issues, but all energy systems deal with them.
What is unresolved, and where readers of Bazilian and Pielke’s paper need to keep a watchful and innovative eye, is on the tools that energy planners use to build adaptive energy networks. Although “simply” plugging into the grid may be the ideal (or in the past has been the aspirational goal), the record of the past decades is that this has not been technically, economically, or politically easy. National grids have not expanded effectively in many nations, in terms of coverage or service reliability or cost, so new models are needed.
Micro- or mini-grids have gained tremendous popularity because although they do require more local knowledge, they are faster to install, more flexible, and suffer less from the “tragedy of the commons,” where people just tie in and feel (culturally or economically) less responsible for being good citizens. For example, walking through the Kibera slum in Nairobi in the early morning is an adventure in “energy fishing,” as people who have illegally tapped into the distribution system unhook their fishing lines from the overhead wires.
Some mini-grids work very well, providing service and responding to local needs. A great many, however, are in technical disrepair or the tariff assessment and collection scheme is not working. The lesson from these mini- grids is not that they do not work or can’t provide the range of services (not just lighting, but energy for schools, clinics, and in many eyes most critically businesses) but that engagement, planning, and service quality must be brought to these systems.
In some of the mini-grids I have been involved in designing and assessing in Kenya and Nicaragua, the lessons have been spectacularly good. Community engagement in the planning and operation of these grids means that they have been able to flexibly respond to changes in demand, and formerly powerless villagers have ramped up their demands and expectations.
The key issue for groups such as Sustainable Energy for All, researchers, and nongovernmental and public officials is to find ways to support this new mode of energy access. An important goal for the coming few years is to develop a true support system so that communities, utilities, and ministries can count on these mini-grids to deliver an expanding set of services. My laboratory at the University of California ), Berkeley, is engaged in efforts ranging from publishing journal papers, to creating wikis, to running training efforts in off-grid and recently connected communities. Needed will be a large community working together on all of these issues, and establishing goals for technology standards, data sets on different market and tariff schemes, and a list of new hardware needs to increase services and service quality in this burgeoning field.
DANIEL KAMMEN
Class of 1935 Distinguished Professor of Energy
Energy and Resources Group
University of California, Berkeley
Berkeley, CA
Morgan Bazilian and Roger Pielke Jr. provide a valid long-term perspective on the energy needs of the developing world, but the critical question is what practical difference does it make to think in the more ambitious, longer-term way that they propose? We don’t do that for any of the other United Nations Millennium Development Goals such as those for health, education, and water. Why, then, should we do so for energy? What investment choices or policies would we approach differently?
The authors suggest that it would make a big difference, but they do not provide the detail or analysis necessary to understand what changes would result. A related concern that they do not consider is that their effort to emphasize the enormity of the long-term challenge could make the task seem so daunting that it will discourage the development agencies from taking the smaller steps that must be taken now to put the developing nations on the path that will ultimately lead to an adequate energy supply. Thinking about the trillions of dollars that will be needed over many decades rather than the billions of dollars that can make a difference now could be paralyzing.
Marshaling the resources to make incremental improvements has been hard enough. For example, the effort to improve the performance of simple cookstoves has yielded good results but could use additional resources to fulfill its potential. Until this can be accomplished, is there any point in worrying about what it will cost to provide every one with an electric stove?
One could approach this question from another direction by examining the most successful examples of electrification and energy modernization such as that in China. Was their success the result of focusing on an ambitious long-term vision? Or did they progress one step at a time by addressing immediate needs and achievable goals, and then setting new goals that built on each accomplishment?
Louis S. Jacobson and Robert J. LaLonde (“Proposed: A Competition to Improve Workforce Training,” Issues, Summer 2013) have led the development of accountability systems since the 1970s. They began their work in the heyday of employment and training programs. At that time, their focus was on increasing the accountability of Comprehensive Employment and Training (CETA) programs. In those days, the state of the art in this field was to use short-term training programs to assist individuals in dealing with employment challenges. Jacobson and Lalonde realized that “second-chance” training programs such as CETA weren’t sufficient to confront the challenges that displaced workers and low-income individuals faced in finding employment. Instead, it was more important to provide individuals with an adequate first chance that prepared them to find and maintain stable employment in high-demand fields.
Since the days of CETA, we have experienced a shift away from short-term training programs toward educational solutions to promoting employment. This shift has been driven mainly by the skill-biased technological change in the economy. Over the past several decades, technology has been automating repetitive tasks and activities on the job. As a result, more and more jobs left to people are nonrepetitive and require skills beyond those produced by a high-school education. The resultant increasing entry-level skill requirements for work have made postsecondary education and training the gatekeepers for access to jobs that pay middle-class wages.
In truth, CETA never had the horsepower to accomplish its objectives. The $2 billion to $5 billion spent annually on CETA programs is minuscule compared to the over $300 billion that is now spent just on postsecondary education.
The essence of Jacobson and Lalonde’s work on connecting education and training with labor market outcomes has always stretched the boundaries of the state of the art in accountability in education and training and is now receiving greater attention in the wider discussion. As they point out, the surest way to efficiency and maximum choice without interference in complex institutional and consumer-driven decisions is transparency in measured outcomes. Yet, although some progress has been made in enhancing the accountability and transparency of programs at for-profit institutions, this model needs to be expanded to all of postsecondary education and training.
All the necessary data for the implementation of college and career information systems already exist. This information just needs to be interconnected and made accessible to prospective students and trainees in a form that they can understand and use to make better decisions. This information also should be made available according to the program of study, for as Jacobson and Lalonde point out, there are vast differences in the costs and outcomes of different postsecondary career and technical education programs, and individuals are often not well equipped or sufficiently supported to make good choices in this regard. The Student Right to Know Before You Go Act introduced by Senators Ron Wyden (D-OR) and Marco Rubio (R- FL) is the legislative gold standard for making this type of information widely available to the public. In no small part, this effort is a result of Jacobson’s and Lalonde’s work in promoting transparency and accountability in educational outcomes.
Hal Salzman (“What Shortages? The Real Evidence About the STEM Workforce” Issues, Summer 2013) ably punctures several myths about the scientific and engineering labor market, but his thoughtful analysis does not address whether U.S. students in general are learning science and math well enough to prepare them for good jobs. As Salzman points out, the claims of extensive science, technology, engineering, and mathematics (STEM) worker shortages are hard to reconcile with engineers and scientists experiencing only average wage growth and with the number of science and engineering graduates rising as fast as the number of job openings. Science Ph.D.s take nearly eight years of graduate study to complete their degree, and then many languish for years in modestly paid postdoctoral positions, hoping for one of the few openings in university professor positions. Another much heralded shortage—of high-school math and science teachers—is apparently a problem of high attrition and is not due to low absolute numbers of newly qualified math and science teachers.
Still, engineers and scientists earn well more than double the average level of earnings. Mean earnings for most science and engineering occupations are as high as the mean earnings of lawyers, although well short of the mean earnings of physicians. Thus, even though shortage claims about engineers and scientists lack convincing evidence, most individuals are likely to achieve high rates of return on their investments in attaining those degrees.
Salzman’s analysis leaves open a key question: Would doing a better job of teaching STEM subjects increase U.S. productivity growth? Here the research is less clear, especially for intermediate- level jobs that do not require a BA. Employers looking for workers who qualify as technically competent machinists or welders sometimes ground their complaints of shortages in terms of weak academic skills. Improving STEM education, especially through career and technical education programs and apprenticeships, might increase the job opportunities and enhance the careers of many young people.
For workers attaining advanced science and engineering degrees, the impact of an expanded supply is not entirely clear. It is no coincidence that Israel, boasting one of the largest numbers of scientists and engineers per capita and highest shares of gross domestic product spent on R&D, is also at the forefront of innovation and high-technology entrepreneurship. But the connections may not be supply- driven. Instead, it may be that added R&D spending is creating the demand for an increased supply of STEM- trained workers, many of whom in turn spur innovation. By implication, a good way to encourage more young people to major in STEM subjects and potentially increase innovation is to raise both public and private R&D spending.
Finally, I want to lend my full support to Salzman’s position on immigration. Rather than focus visas on temporary workers who work for specific firms in the information technology industry, U.S. policies should promote a balance in terms of the skills of new immigrants on a permanent basis. Because the family unification strategy already attracts low-skill workers, the remaining programs should provide adequate places for medium- and high-skill immigrants.
The STEM workforce often inspires extreme assertions. In 2007, Microsoft’s Bill Gates testified that there is a “terrible shortfall in the visa supply for highly skilled scientists and engineers” and asserted that “it makes no sense to tell well-trained, highly skilled individuals—many of whom are educated at our top universities—that they are not welcome here.” Gates urged Congress to eliminate the 65,000-per- son per year H-1B visa cap. At the other extreme, University of California, Davis, Professor Norm Matloff says the “H-1B [program] is about cheap labor.” Foreign workers tied to a particular U.S. employer for up to six years, and hoping to be sponsored for an immigrant visa by their U.S. employer, are young, “loyal,” and cheaper than older U.S. workers.
Conventional wisdom, according to economist John Kenneth Galbraith, is “commonplace knowledge” that the public and experts believe to be true but may not be true. Galbraith used the term to highlight resistance to new ideas in economics, but it also applies to claims of labor shortages in agriculture, health care, and STEM occupations, where employers and blue-ribbon commissions warn of shortages and offer solutions that include admitting more guest workers and immigrants.
Hal Salzman and Lindsay Lowell are empirical sociologists who have examined the data and found that the conventional wisdom about STEM labor shortages is wrong. Consider three facts. First, the United States produces plenty of graduates with STEM degrees. Only one of every two graduates with STEM degrees is hired into a STEM job, and only two of three computer science graduates are hired in information technology. Second, STEM careers do not promise high lifetime earnings to high-ability students. STEM college courses require ability and discipline, but many STEM occupations offer neither financial nor employment stability, as advanced degree holders in science often fill a series of low-paid postdoc positions before getting “real jobs,” and many engineers face industry-wide layoffs that make re-employment in engineering difficult.
Third, labor markets work. Economics textbooks do not include chapters on “shortages.” Instead, they discuss how changes in prices bring the supply and demand for goods into balance, and changes in wages balance supply and demand in the labor market. Not all markets respond instantly, and labor markets may respond slowly if training is required, but people do respond to market signals, as is evident today in the rising number of U.S. petroleum engineers. On the other hand, jobs offering wages that hover around the minimum, few work-related benefits, and seasonal and uncertain work explain why over three-fourths of U.S. farm workers were born in lower-wage countries.
The United States is a nation of immigrants that has welcomed millions of newcomers to the land of opportunity. In recent decades, employers have asked for guest workers who lose their right to be in the United States if they lose their jobs. Whether phrased as overcoming brain or brawn shortages, admitting guest workers to fill labor shortages is government intervention that slows what would otherwise be normal labor market adjustments. In the case of agriculture, rising wages would probably reduce the demand for labor via mechanization and imports; in STEM, rising wages would attract and keep more U.S. workers in STEM occupations.
Hal Salzman’s article questions the prevailing view that America has a shortage of STEM workers. Even a narrow definition shows an annual supply of STEM graduates 50 to 70% greater than the demand. Similarly, labor market data are not compatible with shortages: STEM salaries have been stagnant since the 1990s, and unemployment has been rising.
The pervasive public view that the United States has a serious STEM shortage is due in part to employers’ very successful public relations campaign. It obviously would not be politically acceptable to argue for large numbers of temporary foreign workers (TFWs) to suppress wages or to avoid raising wages to overcome labor shortages (as Salzman shows petroleum engineers’ employers have done). TFW advocates obfuscate their real motives by arguing that foreign workers strengthen competitiveness, which they define as lowering labor costs by reducing wages rather than by increasing productivity and quality, which clearly would be better for workers and the nation.
Advocates buttress their case for more TFWs with such assertions as:
(1) There are not enough qualified Americans; without admitting that serious efforts have not been made to recruit Americans or that employers resist raising wages or training domestic workers if TFWs are available. The presumption that successful business leaders know what they are talking about gives them unwarranted credibility on this issue.
(2) TFW advocates often cite the real advantages of immigration without revealing the sharp differences between indentured TFWs and immigrants who have the right to freely change employers and become citizens, which TFWs cannot do. TFW advocates rarely propose more legal permanent residents, and the companies hiring the most TFWs sponsor few of them for permanent residency.
(3) The quick exhaustion of annual H-1B quotas is commonly cited as evidence of STEM shortages, although all it really shows is a demand for indentured TFWs who can legally be paid below-market wages.
(4) The absence of reliable data, research, and agreed-upon definitions and methodologies for calculating shortages enables these questionable claims to persist despite fairly consistent evidence to the contrary.
With globalized labor markets and aging populations, TFWs and immigrants can boost productivity, growth, and living standards provided that they fill real shortages, receive market-based wages, and complement U.S. workers. It might even be in the national interest to temporarily suppress wage increases for highly skilled workers in short supply. But these decisions should be transparent and made on the basis of evidence, not interest-based assertions. Otherwise, the importation of foreign workers could depress wages, divert Americans from STEM careers, distort labor markets, undermine labor market institutions, and generate social conflict.
An independent professional advisory commission is needed to provide acceptable definitions, better data and research, and objective evidence-based recommendations to the President and Congress about the number and composition of temporary and permanent foreign workers to be admitted each year to promote value-added development. We can learn much about how to structure such a commission from other immigration nations, especially Canada, Australia, and the United Kingdom.
RAY MARSHALL
Professor Emeritus
Economics and Public Affairs
University of Texas at Austin
Secretary of Labor, 1977-1981
Austin, TX
MOOCs plus
Thank you for publishing the William B. Bonvillian and Susan R. Singer article, “The Online Challenge to Higher Education” (Issues, Summer 2013). They provide needed perspectives that clarify the rapidly developing pace and place of online education in postsecondary education and, by extension, K-12. Cyber-enabled or online learning environments, built on carefully considered, evidence-based design principles drawn from the learning sciences, are places where new and promising learning ecologies can be found. As Bonvillian and Singer remind us, the structures, delivery, assumptions, and habits of education are changing.
Along with my colleagues, Sarah Michaels (Clark University), Brian Reiser (Northwestern University), and Cynthia Passmore (University of California, Davis), I am involved in the design of what Bonvillian and Singer call a “blended learning” environment. We call our blended model the Next Generation Science Exemplar PD System, or NGSX. Our particular environment is intended for K-12 teachers of science as well as pre-service science education students. NGSX participants have 24/7 access to a highly resourced Web-based platform that supports and supplements 30 hours of face-to-face learning sessions. In these face-to-face sessions, tablets, notebooks, or smart- phones are used to connect to the NGSX Web platform and the instructional units contained in it. Each face- to-face session blends highly interactive physical and virtual space using the NGSX environment. Learning goals target strengthening teachers’ understanding of science content and the epistemic practices of science, such as making one’s thinking public, model- based reasoning, and using the language of science to begin to transfer both science knowledge and practices to their classrooms.
NGSX comes in response to at least two learner and learning realities of the 21st century. First, we access, visualize, learn, and share information in vastly different ways and for different purposes than we did even a decade ago. Second, the expectations for workforce skills and abilities to support our current knowledge-centric society have changed. As Bonvillian and Singer suggest, knowledge is no longer just acquired; it is acquired with the expectation that an action will follow, whether that is acumen in solving problems, reasoning from evidence, designing models, or undertaking critical assessment. The junction of this knowledge-to-action, action-to-knowledge interface provides fertile ground for envisioning various models of online learning (blended or not).
I agree with Bonvillian and Singer that science or the STEM subjects are a good bet for beginning this envisioning process. There the knowledge-to- action dynamic is more apparent, more visible than in the humanities or social sciences. Virtual learning environments can serve the aims of STEM well with promising functionalities for interactivity, visual representations, data collection and retrieval, model building, and space for “figuring things out.” At the same time, in our knowledge- centric world, the humanities, social and behavioral sciences, health sciences, and communication sciences along with other discipline areas are needed in these envisioning conversations. Correctly, Bonvillian and Singer write, “online technologies alone do not improve learning outcomes. Outcomes depend on how the technology is used and placed in a larger learning context.”
“Time for a Government Advisory Committee on Geoengineering Research” by David E. Winickoff and Mark B. Brown (Issues, Summer 2013) is a welcome contribution to the geoengineering debate. It not only provides a concise overview of the main issues raised generally and from a governance perspective, it is one of the few articles that addresses the institutional side of geoengineering governance and elaborates its rationale for a specific proposal. The following comment is intended to provide food for thought for the further development of these ideas.
The proposal for a standing advisory body is made from a U.S. perspective, while acknowledging that geoengineering raises international issues. Adding international governance to the picture could facilitate acceptance, while an appropriate vertical division of labor between the national [and European Union (EU)] and international levels could address concerns about international micromanagement.
At all levels, academic and political discussion on geoengineering governance should be based on explicit objectives and criteria that any proposed governance arrangements are meant to pursue, balance, and fulfill. For instance, the Oxford Principles mentioned in the article do not include or address the established concept of a “precautionary approach.” From a different EU perspective, this approach might well be one of the values to be considered, not despite, but because of, the different connotations and implications it might have from the U.S. perspective. The potential need for tradeoffs between the criteria and objectives pursued also has to be considered.
Regarding the scope of potential governance, not all concepts currently discussed as geoengineering might require an elaborate governance structure or institutional anchoring at this stage. At the present stage of knowledge and existing governance, solar radiation management techniques deserve priority attention, also regarding the international level.
In terms of the mandate and output of the proposed committee, Winickoff and Brown stress the purely advisory function of the proposed committee at the national level. It is interesting that, in apparent contrast, the proposal envisages that the committee could “build norms” in the context of international communication and coordination. This would call for further clarification.
An advisory function makes sense in terms of preserving the political legitimacy of and responsibility for subsequent decisions. Scientific input should in principle be separate from political decisionmaking, as it is essentially a political decision whether pursuing climate protection can justify the potential and actual risks posed by geoengineering activities. This separation is not undermined by the authors’ argument that the input provided should take into account considerations that go beyond a mere balancing of safety and efficacy.
With interest have I followed the dialogue on the linear model of innovation between Venkatesh Narayanamurti and colleagues (“RIP: The Basic/Applied Research Dichotomy” Issues, Winter 2013, and Forum, Summer 2013) and Neal Lane (Forum, Spring 2013). Both parties provide sociological insight regarding the obsoleteness (empirically if not rhetorically) of the linear model and also in their discussion of an alternative model for guiding national decisionmaking for research policy in the areas of energy, health, basic science, defense, and more broadly U.S. competitiveness. It has been refreshing to see what historically has been the most important question for research policy revisited and addressed so directly and thoughtfully. But the discussion thus far, while valuable sociologically (and mostly in a Kuhnian way, addressing discrepancies between the linear model and how innovation actually occurs in the lab), provides no new insight for research policy design and implementation.
This is a fair criticism for two reasons. First, both parties ignore the bulk of the academic literature on the sociological obsoleteness of the linear model (see for example Nelson and Winter, Kline and Rosenberg, Rip, Etzkowitz, etc. in Research Policy, Science & Public Policy, and Science, Technology, & Human Values). Moreover, both parties call for government “experiments” in organizing and managing scientists and engineers in ways that acknowledge the discovery/invention dynamic they promote and ignore the fact that such “experimentation” has long been underway in the national mission agencies.
One only need look at the National Science Foundation’s (NSF’s) Research Applied to National Needs Program (implemented during the Nixon administration), the NSF Engineering Research Center (ERC) program’s three-plane strategic planning model (which is neither hierarchical nor linear despite how it sounds), and more recently efforts by the National Institutes of Health to map biological systems at the nanoscale (such as their Nanomedicine Development Centers), NSF’s I-Corps and DOE’s Energy Innovation Hub programs (both designed to create regional networks of innovation), and DOE’s Energy Frontier Research Centers (which employ a model very similar to ERC’s).
Although different, what these (and other) U.S. research policies have in common is that they shun the linear model and attempt to coordinate diverse sets of scientists and engineers from across institutions, disciplines, and sectors to address difficult socioeconomic problems requiring nonhierarchical discovery and invention. Accordingly, the most important task for research policy scholars such as Narayanamurti et al. and Neal Lane becomes not moving from rational to descriptive models of innovation but rather developing a predictive understanding of when to support individual investigators versus boundary-spanning research centers or networks and, in the case of the latter, how to get the incentives right to ensure innovation in the national interest.
P. CRAIG BOARDMAN
Associate Director, Battelle Center for Science & Technology Policy
Associate Professor of Public Policy, John Glenn School of Public Affairs
Last year, 8,411 science and engineering journals published just over 1.1 million peer-reviewed articles. Another 190,000 papers were published in 3,016 social science journals. This works out to more than two peer-reviewed articles being published every minute of every hour of every day for the entire year. These staggering numbers should change how we think—and talk—about both science and scientists.
Consider that the smallest field, marine engineering, published 564 articles across 14 journals in 2013 alone. In this single field it would be difficult to keep abreast of the research. It is all but impossible for materials science, which had over 61,000 papers. After the Philosophical Transactions of the Royal Society became the world’s first scientific journal in 1665, it took about 200 years to reach 3,000 journals. We’ve added almost that many in just the past 10 years.
So what does it now mean to be a scientist? When it involved a few European men studying a handful of topics, it may have made sense to treat science as a coherent idea. Not anymore. Is it fair to think of theoretical physicists and ecologists in the same way when scientists in the same discipline often don’t even overlap?
At meetings of the American Geophysical Union, it always struck me that soil scientists are completely separated, physically and intellectually, from space physicists. Even within space physics, those of us studying near-Earth objects did not interact much with the folks studying Mars.
Sure we were all geophysicists. But I can’t tell you the first thing about soil science, and I suspect soil scientists would say the same about my research. So how much do different groups of scientists really have in common? How much do we understand beyond our own specialty?
The dilemma only grows when we look outside academia. We tend to think of science as the abstract pursuit of knowledge conducted at a university. Again, this picture may have been true at some point. Today it’s a lot more complicated.
We now have environmental science, science for international development, disability research, pedagogical research, science for policy, and science of policy. We use science to improve air quality in the United States and to produce cleaner cookstoves in Africa. Universities, government labs, nongovernmental organizations, foundations, and private companies all play a role.
Looking at how diverse scientific research has become, it’s hard to understand what common phrases like “the scientific method” and the “scientific way of thinking” mean. Consider what should be a straightforward question: Does science involve experiments? At some point we all learned that scientists use experiments. But is that always true?
Consider space physics. My colleagues and I often argued that you cannot experiment with the Sun because space conditions change continuously. We instead focused on constructing models, making observations, and collecting and analyzing data. To this day some of my friends insist that we never ran experiments. To them, space physics is an observational science only. That’s a pretty powerful claim worth repeating: Practicing space physicists believe they do not conduct experiments.
So saying that science or the scientific method involves experiments doesn’t make any sense. Some fields of science run careful, repeatable experiments. Areas such as atomic physics come to mind. This type of research, where every parameter can be diligently controlled, is how we usually think of science. But some fields cannot do this.
The phrase “science proceeds by testing falsifiable hypotheses” is similarly imprecise. Sometimes hypothesis testing requires double-blind controlled trials. Other times it requires computer simulations or observations. Is a double-blind trial including real people anything like a computer model of a simulated future? Sometimes we precisely monitor all variables and make repeated measurements. At others we control just a few variables and do not repeat. Some hypotheses are clear and are clearly falsifiable: I hypothesize that this solution is acidic rather than basic. Others depend on so many different branches of science, bodies of data, and physical models that the relevant scientists cannot agree on a test, and falsifiability is clearly not possible: Did global warming intensify the last hurricane?
In this vein, consider the phrase “how scientists think,” as if in some way we all think alike. As described in journalist Chris Mooney’s book Storm World, the data-driven climatologist Chris Landsea, at the National Hurricane Center, weighs observations more than theoretical calculation and is skeptical that humans can detect a link between global warming and stronger hurricanes. MIT’s Kerry Emmanual, attacking the same problem, uses the opposite approach and concludes that there is a strong link. This divide between emphasizing observation versus theory goes back to the founding of meteorology. Even scientists in the same field wrestling with identical questions do not think the same way.
And then there’s “the purpose of science,” perhaps the most perniciously misleading phrase of them all. There is no one purpose to science. Scientists have purposes. They are as complicated and varied as all human purposes. Some scientists want to explore nature, some want to prevent disease, some want to create technology, some want to educate children, some just want to do their job, get paid for it, and go home. None of these goals are more worthy than the others.
It appears that thinking like a scientist, testing a hypothesis, and conducting an experiment can have a different meaning depending on the research and the scientist in question. By themselves, these phrases are vague and uninformative. Yet they are used in public all the time as if they communicate something specific and essential to science, as if they add up to a single “purpose.” But they don’t.
The world is a very complicated place, and we can’t expect scientists to apply the same rules and procedures to the millions of questions they ask. Scientists need intellectual and methodological flexibility. Certain tools and methods are appropriate for atomic physics, others for space physics.
The problem is that these differences are rarely discussed. Scientists instead typically give the opposite impression, presenting science as uniform and monolithic. We promote the scientific method instead of scientific methods. We discuss “how science works” rather than emphasizing that science is too diverse to work in just one way.
When have you ever heard a scientist publicly acknowledge that “the scientific method” is just a generic phrase that doesn’t tell you how to approach a specific question, and may mean something entirely different for a subatomic particle physicist and for an evolutionary biologist? Or that not all scientists conduct experiments? Or, to go back to my previous example, that observational and theoretical meteorologists think differently about the same problem?
Addressing the public
Given this diversity in scientific methods, how should scientists approach public communication? To begin to answer this question it might be helpful to first consider how we speak and think about any large category. There are two important principles to keep in mind. First, broad overviews do not always help you understand particular situations. Even more strongly, a specific claim can contradict a general one without undermining its truth. The fact that Orange County is very conservative does not undermine the generalization that California is a liberal state. These ideas can simultaneously exist without conflict because they speak at two different scales. The truth of one does not negate the other; it only complicates it.
Second, the members of any category share differences as well as similarities. All 50 U.S. states share common features. But there are also differences between Alabama and California, between northern and southern California, and even between Palo Alto and East Palo Alto.
Whether we emphasize similarities over differences, or whether we speak in terms of generalities rather than specifics, depends on the issue at hand. A comparison between U.S and British politics will use national generalizations and ignore the local distinctions between San Francisco and San Jose. A housing search will take the opposite approach.
SCIENCE IS NOW TOO BIG AND TOO DIVERSE, AND ABOVE ALL TOO DEEPLY WOVEN INTO AN ARRAY OF SOCIETAL ACTIVITIES EVERY BIT AS DIVERSE AS SCIENCE ITSELF, TO BE CONSIDERED ONLY “SCIENCE.” THERE IS NO SCIENCE ANYMORE, THERE ARE ONLY SCIENCES.
I suspect we all instinctively grasp these principles. We have all discussed categories at different scales. We all know that statements about red and blue states do not pertain to everyone within the state.
In my experience, though, we scientists tend to neglect these principles in our public communication. We overemphasize the broad generalizations and do not spend enough time explaining the local distinctions. Science is now too big and too diverse, and above all too deeply woven into an array of societal activities every bit as diverse as science itself, to be considered only “science.” There is no science anymore, there are only sciences.
Nevertheless, there will always be occasion for academic scientists—even those, like me, who left academia after getting a Ph.D.—to explain their research to nonscientists. And these occasions may require discussing “science.” When we find ourselves in this situation, our use of language must be meaningful and precise. Our words should transmit coherent thoughts, and there should be no doubt about what we are trying to say. In short, what we as scientists say in public should at least be consistent with our own ideals, if for no other reason than that we cannot expect the public to do so if we do not. Though we exhort the public to use evidence, to value truth, and to not distort, exaggerate, or cherry-pick examples, we often violate these principles when we discuss “science.”
Consider again that standard nostrum: “Science is about testing hypotheses.”
How should someone interpret this phrase? Is it that all scientific discoveries occur because a scientist is testing some hypothesis? Well, we know that isn’t true. Many discoveries have happened by pure luck. Scientists can’t test a hypothesis they don’t even know exists. We also know that some research can involve nothing more than observations and data collection without any conscious hypothesis testing.
Perhaps we mean only scientists test hypotheses? But we know that isn’t true either. Plumbers also test hypotheses: They hypothesize that Draino will fix the problem and modify their belief based on the result. You could argue that we all do so sometimes: I hypothesize that restarting my computer will get rid of the glitch in the behavior of my mouse.
So if everyone tests hypotheses at some point, and scientists do so only part of the time, what’s the big deal? Why bother emphasizing it at all? And since a “test” in geophysics is so different from one in atomic physics, it makes even less sense to use a single phrase to explain all scientific explorations.
And what’s with “is about”? All the professors I know spend most of their time applying for grants, managing them, and sitting on committees. In academic science at least, it seems much more accurate to say “science is about grant-writing and committee-sitting.”
Finally, how can “science” do anything on its own, much less test a hypothesis? Science must be done by scientists— by actual human beings.
A more precise version of the above might be: “Among their dozens of activities, some scientists—along with many other people—sometimes test hypotheses of various forms in many different ways to accomplish their goals.” This version is both accurate and understandable. Unfortunately, it is not very interesting.
How can scientists paint a more accurate and interesting picture of science? The answer is by not communicating “science.” Imagine that sportscasters spent most of their time discussing “sports” and nothing else. We would be left with nothing but clichés: Sports are about hard work and teamwork! The keys to the game are hustle and good defense! Fans rightly tune out such commentary. We are enlightened, however, by deep, insightful analysis of a specific game. We want to know how an injury will change team strategy, and when they should run the ball instead of passing it.
Intelligent science communication should emulate intelligent sports communication: low on generic phrases, high on detail and particulars. In this aspect, our public communication should emulate our research communication: precise, clearly defined, and modest. When we have to make generalizations, we should do so carefully and reluctantly, with many caveats and as few clichés as possible. We should acknowledge, privately and publicly, that any statements about science as a whole will often be overly simplified and not very useful.
INTELLIGENT SCIENCE COMMUNICATION SHOULD EMULATE INTELLIGENT SPORTS COMMUNICATION: LOW ON GENERIC PHRASES, HIGH ON DETAIL AND PARTICULARS. IN THIS ASPECT, OUR PUBLIC COMMUNICATION SHOULD EMULATE OUR RESEARCH COMMUNICATION: PRECISE, CLEARLY DEFINED, AND MODEST.
Communicating about anything as vast and heterogeneous as either science or sports can be done only by glossing over distinctions and muting differences. But at least in sports we know not to take these clichés too seriously. We also have phrases that present a more complex and nuanced image. We hear that professional sports are about money and greed as well as teamwork.
No one feels the need to choose between these two views of what sports is “about” because we understand that complex systems must be analyzed from different vantage points and that there is no single way to encapsulate all of sports in a few sentences. Professional sports are both a business and a game. They involve both greed and hard work. Our appreciation would diminish if we forgot that these traits exist simultaneously.
Scientists, on the other hand, do not provide such competing images. We don’t hear that science is about writing grants as much as it is about hypothesis testing, that in some ways science is objective and value-free, while in others it is not. We don’t recognize sentences with “science is,” “science is about,” “science involves,” “the scientific method,” “the scientific way of thinking,” or “how science works” for the vague, broad generalizations that they are. We don’t see that any attempt to explain “science,” as opposed to one specific area of science, will often resemble bad sports commentary.
To a certain degree, it’s understandable why scientists speak like this. Categories exist for a reason, and at times it can be very important to stress the differences between science and nonscience. For all their differences, atomic physics, space physics, and ecology have more in common with one another than with acting and literary criticism. At times it may be appropriate to speak of these disparate activities as a whole. Because the authority of science is often abused and misused, it can be important to stress a few general, even overly general, attributes. But it can be dangerous to take this approach too far. Almost by definition, a big-picture view of science will elide details and hide more than it reveals. Perhaps most important, these generalizations have contributed to making scientific authority more vulnerable to attack than would a more honest portrayal of the richness and diversity of the scientific world.
Consider climate change, where a childishly simplistic model of falsification has been so powerfully deployed to attack the scientific consensus. Imagine a world where scientists did not continually intone phrases like “science proceeds by falsification” and “scientists change their mind when the evidence changes.”
Perhaps in that world the public would know that sometimes falsification is straightforward and sometimes it is not. And that in any case the very term “falsification” is a broad concept that must be applied to a specific research field. Perhaps in that world the public would know that there are distinctions between falsification in analytical chemistry and climate science. And that scientists don’t always change their minds in response to every paper but instead look at the full body of research. Perhaps in that world, the latest paper on global warming would be viewed in context rather than as one shot “proving” or “disproving” global warming.
Why doesn’t that world exist? In no small part it is because we in the scientific community have fought its creation. And so we see the same dangerously simplistic model of science invoked in endless debates over uncertainty about the risks of nuclear power or the effectiveness of various educational or social policies. Politicians and the public seem to expect that epidemiology or sociology can create the same sorts of knowledge and levels of certainty that we see in experimental physics. We have told them that science is science, and they believe it. And since we in the scientific community do nothing to elucidate the very real and significant differences among the sciences, we are often powerless to combat misrepresentations.
It would help to acknowledge our limitations as scientists. I am not qualified to discuss condensed-matter physics even though I’ve taken a few classes on the subject and have a Ph.D. in applied physics. For any field of science outside my own, I always hesitate, speak carefully, and qualify my expertise. So how did I ever claim to know the process of “science”? How does anyone?
I know how strange this idea sounds. I understand how hard it will be to swallow. Somewhere along the way we all cultivated a false confidence in our knowledge and understanding. Something about our training makes us believe we can speak for and explain “science.” No one taught us that in the year 2013, individual scientists are a minuscule part of a $1 trillion, 5-million-person global enterprise. No one reminds us that we contributed to only a few of the over one million papers published this year.
To get a sense of how we might approach this problem constructively, it might help to take the sports analogy even farther. Perhaps we should consider ourselves scientists in the same way basketball players are considered athletes. Michael Jordan rarely spoke for all of basketball, much less for soccer, cricket, or all of sports. Whatever his accomplishments, his opinion was just that—his opinion. For all his greatness, Michael Jordan was a small part of something much bigger. We all would have a cramped and deeply flawed image of sports if we forgot that there are hundreds of sports, all with different rules and conventions, requiring athletes with different skills and abilities.
Each scientist too is just a small part of something much bigger, offering only one individual’s opinion among many. And as with sports, we should not forget that there are hundreds—thousands—of sciences, with different rules and conventions, requiring scientists with different skills and abilities, using different methods, standards of proof, and types of evidence. Any one of us can provide only a single perspective.
So when speaking to nonscientists, rather than grandiose proclamations about the scientific enterprise or the process of science, try to make simpler, more specific, and more human ones about your own research. Your research, the particular scientific methods you use, the nooks and crannies of your work, your personal journey to your own small corner of science are wonderful and awe-inspiring by themselves. They are the corner of science that, if you’re fortunate, you love, and that you know well enough to explain in a way that is compelling because it is your own.
If science is “about” anything, it is about scientists. It is a profoundly human story. It is your story. If we remember that, then we can all help the public gain a deeper, richer understanding of science.
From the Hill – Fall 2013
Congressional budget gridlock
With the appropriations cycle stalled since July—and with little real hope of a completed appropriations cycle to begin with—Congress has now resumed the political gamesmanship around continuing resolutions and debt ceilings, which is becoming the new normal.
At the end of September, the House passed an initial continuing resolution (CR) that sets FY 2014 spending at FY 2013 levels through December 15 to avoid a shutdown, but it added the poison pill of defunding the Affordable Care Act. In response the Senate passed its own version of a CR that maintains health reform funding and funds government through mid-November, again at FY 2013 levels. The House rejected the Senate bill, and members of Congress devoted themselves to a heated exchange of accusations about who is to blame while waiting for the government to reach the day when it hits the debt ceiling and no longer has access to the funds necessary to pay its bills. By the time this issue is published, Congress is likely to have done something to avoid default.
It’s not clear where this leaves full- year FY 2014 appropriations, which will still have to be negotiated and passed after a CR is adopted. Under the spending caps established by the Budget Control Act, overall discretionary spending is slated to drop by 2% below FY 2013 levels, though the bulk of this reduction would come from the defense spending side. Democrats and some Republicans would still like to see the discretionary spending caps lifted from current levels; many Republicans would also like to see further reductions in nondefense funding and increases in defense funding. But for the moment, negotiations over the fiscal situation have cooled considerably, and any movement on discretionary spending, or R&D in particular, is likely to be limited for now.
Likewise, the current debate leaves the long-term fiscal picture very fuzzy. As the Congressional Budget Office has pointed out recently, even as discretionary spending drops to all-time lows, mandatory spending, especially entitlements, will continue to rise. In the past few years, the bulk of deficit reduction has been achieved through cuts in discretionary spending, including R&D, whereas the main drivers of federal spending in the coming decades have hardly been addressed.
House holds climate hearing
On September 18, the House Energy and Commerce Committee’s Energy and Power Subcommittee held a hearing entitled “The Obama Administration’s Climate Change Policies and Activities” in an effort to understand the ramifications of the president’s climate initiative. Environmental Protection Agency (EPA) Administrator Gina McCarthy and Energy Secretary Ernest Moniz testified.
Conservative members were primarily concerned about the EPA’s pending carbon emissions rules, which were released days after the hearing, and their potential effects on the coal industry. They expressed concern that the carbon capture and storage (CSS) technologies necessary to reduce carbon emissions are not yet commercially viable and that the regulation would prevent the construction of new power plants. Rep. Ed Whitfield (R-KY), subcommittee chairman, remarked that power plants are already closing due to EPA regulations and expressed concern that combating climate change would cost too much and eliminate jobs.
McCarthy responded that CSS is, in fact, already available and that the EPA has no intention of preventing construction of new power plants. She noted that when the government required coal plants to install scrubbers that reduce acidic gas emissions, the coal industry was able to do so without detriment.
Committee members were also eager to ensure that the EPA does not overstep its legal boundaries; McCarthy confirmed that the new Climate Initiative allows the EPA to use only the authorities that have already been granted by Congress. She also vowed to work closely with other agencies such as the Department of Energy and the State Department.
Congress in brief
On August 19, the Environmental Protection Agency (EPA) responded to a subpoena issued by House Science, Space, and Technology Committee Chairman Lamar Smith (R-TX) to force the agency to relinquish the underlying data from two studies used to inform regulations under the Clean Air Act. One of them was a seminal study known as the Harvard Six-Cities Study, which followed a cohort of over 8,000 participants for 17 years to assess the effects of air pollution. In the late 1990s this study came under congressional scrutiny when it was used as the basis for strengthening air quality standards, and some members of Congress called for access to the underlying data. The battle over the study’s underlying data led to an independent assessment conducted by the Health Effects Institute and a change to OMB Circular A-110 governing federal grants to allow for access to certain research data that is used in federal regulations.
This latest debate over access to research data included a set of heated letters between the committee’s ranking member Eddie Bernice Johnson (D- TX) and Chairman Smith. Although no details were provided about the type of documentation provided by the EPA to the committee, on September 3 Smith issued a letter in response stating that the agency had not provided any new data and hence stood in default of the subpoena. The new deadline for complying with the subpoena is now September 30.
On September 18, a House Science, Space and Technology Committee panel held a hearing on methamphetamine (meth) addiction. Witnesses included the head of a neuroimaging lab, an epidemiologist studying trends in substance abuse, and the director of an addiction research center. In connection with the hearing, Science Committee Chairman Lamar Smith (R-TX) stated that the National Science Foundation “will play an integral role towards a more complete understanding of this problem. Hypothesis-based data-driven social science research can be used to understand the behavior science behind addiction.”
On September 18, the House passed the National Strategic and Critical Minerals Production Act of 2013 (H.R. 761). The bill would authorize the Departments of Interior and Agriculture to enhance mineral exploration and streamline the process for receiving mining permits for rare-earth minerals and other minerals necessary for national defense, economic security, and to support the nation’s energy infrastructure.
Reports and publications
Congressional Research Service
Climate Change and Existing Law: A Survey of Legal Issues Past, Present, and Future
Changes in the Arctic: Background and Issues for Congress
Rare Earth Elements in National Defense: Background, Oversight Issues, and Options for Congress
Is Biopower Carbon Neutral?
Earthquakes: Risk, Detection, Warning, and Research
Government Accountability Office
America COMPETES Acts: Overall Appropriations Have Increased and Have Mainly Funded Existing Federal Research Entities
Education Research: Preliminary Observations on the Institute of Education Sciences’ Research and Evaluation Efforts
Intellectual Property: Assessing Factors That Affect Patent Infringement Litigation Could Help Improve Patent Quality
Global Manufacturing: Foreign Government Programs Differ in Some Key Respects From Those in the United States
The Future of Meat
On August 5, 2013, the first hamburger grown from stem cells in a laboratory, and not in a cow, was served in London. This event was not merely a milestone in the development of the scientific and technological capability to produce factory-grown, or cultured, meat; it was a proof of concept for a foundational emerging technology. If this technology continues to evolve and is deployed at scale, it will have significant social, cultural, environmental, and economic implications. How ought a democratic society begin to understand and prepare for such changes?
Despite the high level of uncertainty regarding the outcomes of technology choices, economic winners and losers, ethical debates, and so forth that are associated with any radical new technological pathway, it is by no means premature to begin a systemic effort to explore possible future consequences of the development of factory meat. The aim of such work, however, should not be to try to develop accurate predictions of what will actually occur as this technology matures, which is probably impossible. Rather, it is to develop and play with scenarios that can enable more adaptive and responsible policy and institutional responses to the unpredictable and far-reaching social consequences of a transition to the production and consumption of factory- grown meat.
Indeed, with the first meat-production facility, or “carnery,” probably only a few years away, an optimistic scenario might suggest that rapid public acceptance of its products could attract investors and soon lead to expanding industrial capacity for producing factory meat. The shift of meat production from field to factory could in turn significantly reduce global climate change forcing and lessen human impacts on the nitrogen, phosphorous, hydrologic, and other cycles, while reducing the land required to produce animal feed could mean more land for producing biofuels and other biological feedstocks for, for example, plastics production. All of which would, of course, be accompanied by an equally rapid realization of unintended consequences. Yet an opposite scenario is, at this point, equally tenable: that for a number of reasons such as inability to reduce costs of production to a competitive point, opposition from threatened economic interests, or simply a society-wide rejection of food produced in such a manner for reasons of aesthetics or subjective preference, cultured meat might be rejected outright. Such a choice would also carry consequences; it might, for example, commit a world that is rapidly increasing its consumption of meat to an ever-expanding environmental footprint of food.
During the August 5 tasting event, which was widely covered by print and video media, Mark Post, the tissue engineer who created the cultured hamburger, said that it took about 3 months to grow the tissue for that particular burger which, he is quick to point out, is faster than raising a cow. (For comparison, one life-cycle assessment estimated that calves sent directly to feedlots in the United States require about 10 months to mature.) Nonetheless, he believes we are still at the beginning of the development process and have a lot of work to do to scale up the production process while maintaining the quality of the tissue cultures and ensuring the sterility and safety of the final products. Some of the remaining challenges include optimizing synthetic (animal-free) nutrient growth media, designing scaffolds (structures to which muscle cells can adhere that mimic the in vivo environment), and facilitating cell exercise in order to impart a familiar and acceptable texture, as well as identifying cost-effective and environmentally appropriate technology options for each stage of the process (environmentally appropriate options are necessary because a significant societal and economic rationale for the technology is its environmental advantages over current production methods). Dr. Post remains confident, however, that these technical issues can be resolved. Some estimates put commercial availability at 10 to 20 years from now. The Missouri firm Modern Meadow has an even shorter time horizon for a similar tissue engineering process aimed at producing leather (making cultured skin is simpler than producing meat). It has said in a Txchnologist article reprinted in Scientific American in 2013 that bioengineered leather products will be commercially available by about 2017.
From an economic perspective, cultured meat is still an experimental technology. The first in vitro burger reportedly cost about $335,000 to produce and was made by possible by financial support from Google cofounder Sergey Brin. Of course, first-of-a-kind technologies are often ridiculously expensive; one 2008 European study, however, concluded that the production costs are likely to eventually be competitive with those of unsubsidized chicken meat. But the technology processes are still under development, and their future makeup, and costs, cannot yet be projected with any certainty, nor can their broader environmental and social implications. Accordingly, any such prediction should be taken as no more than an educated guess. Moreover, the eventual shape of demand and supply curves, and product differentiation possibilities, are also unknown; depending on consumer response and market evolution, for example, there is no reason why very expensive “designer” or “boutique” brands might not be commercially viable even if in vitro burgers never, or only very slowly, become a mass consumption option.
Although the development path of in vitro meat techniques remains uncertain, the basic steps required for initial industrial-scale production seem clear. The first step will be the extraction of a tissue sample from a donor animal that remains otherwise unharmed. From that sample, stem cells of interest will be isolated and, with the addition of nutrients and growth factors, the culture will proliferate and increase in overall mass. The cells will then be induced to differentiate into edible skeletal muscle cells. Along the way, the cells will be exercised via mechanical, electrical, or chemical stimulation in order to achieve a familiar and palatable texture. Finally, vitamins, minerals, and flavors will be added as the tissue is ground into the final product and packaged for shipment to grocery stores and restaurants. In this form, cultured meat will not have the larger-scale structures of fat deposits, blood vessels, and connective tissues that provide familiar cuts of meat with their characteristic appearance and taste. Accordingly, farther in the future, bioprinting techniques may be used to enable the production of meat that mimics more familiar cuts such as steak, roasts, and pork chops, and further differentiation could lead to more- affordable basic cuts as well as high-end products designed to meet specific taste and nutritional profiles. Precisely controlled fat content as well as unique flavors and supplements could yield branded, designer delicacies with much greater variety than animal meats can currently provide. At the scale of the agricultural system, any reduction in total farm animals could also reduce the propensity for diseases to cross the species barrier to humans and, because less prophylactic application of antibiotics would be needed, less bacterial resistance to antibiotics may result, with consequent benefits to human health. Asceptic growth environments could meanwhile prevent food-borne illness.
Once the factory production system is in place, the product—meat—will itself become a design space, and genetic or protein manipulation, changes in production technology, and the integration of other types of nutrients and food products will continue to diversify food away from the familiar forms it has today. At some point in the farther future, cultured meat production may well be coupled with pharmaceutical technology, and the rapid growth of individual genomic mapping, to create food that is designed for particular genomes or that supports healthy personal microbiota ecologies.
Or not. Of the many factors that might influence the pathway to such a future, one is the question of whether people will, at least in the short term, continue to expect meat to look, taste, and feel like, well, meat. Food is a culturally charged domain, and the technological evolution of meat may well outpace cultural acceptance of radically new food production technology. Nonetheless, people may eventually look at a T-bone steak with the nostalgia they feel for the Apple IIe: It was an important contributor to technological evolution and economic productivity, but no one would choose it over an iPad.
Indeed, the scientific and technological challenges to creating a factory meat industry are likely to be no greater than the environmental, economic, and social ones. For example, we have run focus groups that indicate that some consumers have a negative visceral reaction to the thought of lab- grown meat. Yet others believe that such technologies herald the next generation of environmentally friendly and hunger-reducing food technologies. Will environmental groups that campaign hard against genetically modified crops decide instead to lend strong support to cultured meat? Even in the most predictable of worlds, consumer preferences can be capricious, and if cultured meat does not offer early benefits in either taste or cost, will its novelty be sufficient to stimulate the demand necessary to allow the industry to grow?
But the complexities of demand patterns are not the only economic uncertainty. The growth of a cultured meat industry could create new economic winners and losers as food production leaves the ranch in favor of the bioreactor. As the technology scales up, would ranchers and farmers fight hard to stop it? Whereas the U.S., with its enormous factory farms, accommodated genetically modified crop varieties with barely a political ripple, perhaps the threat to the meat industry, and the mythic national symbols of the rancher and the range, will trigger strong opposition to factory meat? In contrast, perhaps the European Union, which has been so suspicious of GMOs, would welcome factory meat as a boon to landscape preservation—especially given that it was first developed in a European university, rather than by a U.S. corporation. New technologies may often generate surprising political, economic, and social realignments.
Such possibilities can help inform rich scenarios for exploring the future of meat. The value of such scenarios, in turn, is to help anticipate the sorts of policy challenges that may emerge. For example, cultured meat will undoubtedly shift the vulnerabilities inherent in the food system. Water and supply chain management techniques may give carneries a significant advantage over conventional meat production processes in coping with variations in rainfall, and allow them to better attenuate subsequent price fluctuations. Such capabilities may enhance global food security. Yet perhaps factories for the mass production of meat, which could be sited in any environment, would displace feedlots and ranches that require certain environmental conditions, to the detriment of the economies of nations that now depend on the production of meat from animals. Few of these effects cannot be mitigated through appropriate policy tools; this is easier to accomplish if they can be anticipated and spotted early on.
The intersection of global hunger and poverty with cultured meat technologies presents a particularly complex challenge. Intuitively, it seems that factory-grown meat designed to be inexpensively produced, and perhaps used as an input to integrated algal/insect/factory-meat products, could constitute an inexpensive source of complete protein for those who are malnourished in developing nations. However, this view not only assumes affordability but also makes the familiar mistake of characterizing hunger as a problem of food scarcity. The world already produces enough food to meet the individual energy requirements of every person on Earth [2,831 calories per person per day in 2009, according to the United Nations Food and Agriculture Organization (FAO)]. Global hunger today is a consequence of many factors, including poverty, natural disasters, failed states, and war, not simply a lack of food production capacity. The development of a cultured meat industry will not address the problems of political power, infrastructure inadequacies, economic inequity, and geopolitics that underlie global hunger. Moreover, perhaps the growth of a bioengineered meat sector will undercut the economic prospects and cultural cohesion of some developing countries by allowing a new shift of economic potential from agrarian economies back to industrialized ones, thus exacerbating the hunger problem. Again, we offer the outlines of such scenarios not to predict, but to suggest the sorts of discussions and analyses that need to begin now in order to develop a suite of possible response options that can enable effective policymaking as the system unfolds in real time.
As with economics and social patterns, cultured meat can be expected to have substantial implications for environmental systems. Over the past century, the onset of industrial agriculture and the Green Revolution (more fertilizer, better pesticides, modern management techniques, better irrigation methods, and more productive cultivars) kept pace with a growing and increasingly urbanized human population of 7 billion people and made a mockery of popular environmental books such as The Population Bomb by Paul Ehrlich (1968) that were confidently predicting mass famine and death by the 1980s. Yet modern agriculture has also contributed to water scarcity, greenhouse gas emissions, increased perturbation of the nitrogen and phosphorous cycles, and other environmental problems. (For example, a 2006 report from FAO found that livestock are responsible for about 18% of annual anthropogenic greenhouse gas emissions, 8% of water withdrawals, and 30% of land use.) For some, cultured meat and associated bioengineering techniques mean that the environmental problems associated with industrial agriculture can be addressed, at least in part. One analysis performed by researchers at the universities of Oxford and Amsterdam and published in Environmental Science & Technology in 2011 concluded that, “In comparison to conventionally produced European meat, cultured meat involves approximately 7-45% lower energy use (only poultry has lower energy use), 78-96% lower GHG emissions, 99% lower land use, and 82-96% lower water use depending on the product compared.” By enabling tighter controls on emissions and the recycling of nutrients that are not directly embedded in the final product, cultured meat could be a critical mechanism for managing increasingly severe human impacts on the nitrogen and phosphorus cycles.
The long view
The potential future implications of cultured meat must also be understood in a broad historical context. As with the Neolithic Revolution 10,000 years ago, and industrial agriculture 150 years ago, bioengineering is poised to once again transform farm landscapes. The potential impacts of factory-grown meat mentioned so far merely represent some of the most obvious and easily anticipated trends. In reality, human food production is highly integrated with other environmental, economic, and social systems in a web of complex global cause-and-effect relationships that are difficult to understand and impossible to control. These complexities will be further compounded if food, pharmaceutical science and technology, and human genomic medicine become an integrated design space. For this reason, it is important to develop anticipatory practices that can be systematically applied to interconnected global systems as new technologies such as cultured meat are introduced and expanded. The hamburger served in August may become merely a footnote in the narrative of sweeping changes that biotechnology-enabled food production might bring, but it is an important reminder that better evaluation and assessment methodologies are needed, and soon. These in turn should be integrated into scenario games that enable stakeholders and policymakers to practice agile responses to the challenges and opportunities such technological evolution will no doubt spawn in abundance.
Yet it is difficult enough to consider near-term possibilities. Since humans began developing agriculture thousands of years ago in many places around the globe, food has been defined in terms of the production technology. To date, such production technologies are determined by what nature has provided—cows for beef production, pigs for pork production, plants for corn and soy production—sometimes tweaked with genes and chemicals from other species. But food is now morphing into a design space, where factory production systems, coupled with genetic manipulation, liberate food from any need to rely on a particular species. How might the ethical dimensions of this transition evolve, as animals become decreasingly necessary as a food source? Might factory food thus facilitate the extension of full human rights to all sentient species? In contrast, a 2008 article in the Journal of Agricultural and Environmental Ethics wondered how much of a moral problem eating factory meat sourced from a human stem cell (effectively creating safe, victimless cannibalism) would be. Or again, in an age when individuals carry around their complete genetic profile in easily accessible form, it may be possible to custom-design food for particular genomes, as food design and preventative medicine merge. Factory food may also become a critical means to help humans manage the carbon, nitrogen, and phosphorous cycles of an increasingly anthropogenic planet.
Such scenarios may seem ridiculous, but equally radical, if currently unimagined, changes are likely as emerging technologies such as factory food scale up, and we should practice thinking about “radical” scenarios just as we practice thinking about more incremental ones. Powerful technologies, such as railroads, automobiles, and the Internet, change the world in profound ways that antecedent generations could not have predicted and often failed even to imagine. Automobiles were clean, resource-efficient, low-emission vehicles compared to the horses they replaced, but a billion automobiles on the road today mean that cars are now changing the evolution of our atmosphere through anthropogenic greenhouse gas emissions. But, of course, had there been no substitute for horses, the modern world could not have evolved, since (among other things) it would be impossible to grow enough food to supply, not to mention process all the waste produced by, horses and other animal forms of transportation in a world with a population and an economy such as ours. The consequences of important emerging technologies are not additive; rather they create significant perturbations of a complex adaptive system, and the world that that subsequently evolves is fundamentally different from what it was before. From the structure of our economies to the evolution of our environment to our ethical standards, a world whose protein supply is significantly provided by factory-grown meat technologies will probably be different in kind from a world without these technologies. Indeed, factory meat is perhaps best understood as a planetary engineering technology, and to pretend otherwise can become just a subtle way of avoiding ethical responsibility for the consequences of our own creations.
Broader implications
For this reason, cultured meat technology is not just of interest in itself, it is also an ideal case for exploring broader questions about how emerging technologies, with all their unpredictability, uncertainty, and potentially substantial impacts in numerous domains, can be usefully studied and understood, even at very preliminary stages of their development, to improve societal capacities to manage their development, diffusion, and consequences. All foundational emerging technologies—the printing press, the steam engine, railroads, computers, and so on—destabilize existing economic, institutional, environmental, social, and cultural assumptions and interests. Despite their potential to transform human and environmental equilibria, and despite the fact that such technology-driven transformations seem inseparable from human evolution itself, systemic evaluation of early-stage technologies with significant potential for societal transformation is not a well-developed body of knowledge and practice. Creating this area of study is a formidable intellectual challenge not just because of the complexity of the systems involved, but also because, by definition, emerging technologies seldom have well-identified characteristics and behaviors, so traditional analytical tools, such as industrial ecology or life-cycle analysis methods used to identify and assess environmental considerations, have at best limited and speculative application. Efforts to develop methods, tools, and institutional structures for evaluating the social implications of emerging technologies are also under way, but progress is halting and investments have been at best modest. In 1990, the Human Genome project, for example, began directing some of its funding into an Ethical, Legal, and Social Implications (ELSI) program, which was intended to identify and examine social issues related to the main research activity. The Center for Nanotechnology in Society headquartered at our home Institution of Arizona State University, and the Synthetic Biology Project at the Woodrow Wilson International Center for Scholars in Washington, DC, seek to explore the social implications and potential governance of the rapidly evolving areas of emerging foundational technologies. Europe houses several small efforts to actually build such capabilities into government R&D enterprises, including the Danish Board of Technology and the Rathenau Institute in the Netherlands. Of course the U.S. Congress chose to eliminate its own fledgling effort in this regard when it eliminated the Office of Technology Assessment in 1995.
Economic tools for technological assessment tend to be the most sophisticated, because countries and firms have long had to make technology choices, and economic considerations have been the most important and immediate input to such choices. Similarly, environmental issues have been analytically bounded and assessed through predominantly scientific and quantitative methods, and environmental analytical techniques such as industrial ecology are also reasonably well developed. The assessment of social impacts of technology, especially when the technology is in its earliest stages, remains the least developed, in part because of the complexity of the systems involved and in part because social assessment is, inevitably, a normative process in which the results of the analysis often reflect values as much as quantitative observations. Of course this is also true for economic and environmental assessments, yet as our research has proceeded, we have been struck by the gap between the availability and sophistication of economic, engineering, and environmental analytical tools, and the relative paucity and inadequacy of tools to enable modeling and quantification in the social and cultural domains. And while it is true that results of social assessments seem particularly contingent given the high levels of uncertainty and nascent state of the technology itself, this is no less true for economic and environmental contexts. So the large gap in practice seems as much to do with a bias toward the quantifiable in assessment methods rather than the intrinsic complexities of the domains, and increasing our capabilities in the social assessment of technologies is a clear challenge to future researchers.
Moreover, existing technology assessment tools tend to have specific disciplinary foci and a resulting set of biases: industrial ecology and its toolbox tend to emphasize environmental perspectives; life-cycle accounting methodologies and related tools focus on economic issues. All too frequently, biases in the evaluation of complex systems such as emerging technologies are not introduced intentionally, but because of limits in the tools available to analyze such systems and the lack of robust integrative analytical frameworks that are able to not only place quantitative results in proper perspective, but identify substantive gaps in the evaluation process. Thus, for example, reliance on an environmental tool such as life-cycle assessment will produce quantitative results that, however uncertain, can bias decisionmakers toward the prioritization of environmental values over others, simply because decisions tend to reflect available information, especially if that information is quantitative and therefore appears robust and definitive. A further research challenge is therefore to provide an integrated framework for technology assessment across disciplinary domains.
Such an integrated approach must start with good cases, and part of our purpose here is to present factory meat as an example of the type of nascent technology that can provide a rich source of scenarios for exploring future societal transformations, with an eye toward understanding not just their particular implications but the broader lessons they can help teach about adaptation to technological evolution. A world where meat comes mostly from factories instead of ranches and feedlots might be a world better able to deal with challenges of food security, the environment, and natural resources, but at this point such a future is hypothetical. We may be only one in vitro hamburger into the age of factory meat, but it is not too early to begin exploring the implications of this potentially transformational technology, both to support more agile and effective responses to unexpected emerging consequences of a potentially radically shift in our food production system and to provide a model case study for how to approach and better understand and manage other emerging technologies, now and in the future.
Does Education Pay?
Higher education is one of the most important investments that people make. Whereas most academics emphasize the nonpecuniary benefits of higher education, most students making this investment are seeking higher wages and good careers. For example, in the latest Higher Education Research Institute survey of incoming first-year students at four-year colleges and universities, 88% agreed that the most important reason to go to college is to get a good job. And increasingly, government policymakers who vote on the billions of dollars of subsidies that support higher education are also asking about the return on taxpayers’ investment. Concern for labor market returns may infuriate many academics, but it is today’s reality.
Therefore, collecting data on wage outcomes for graduates of higher education programs has become ever more important. The American Institutes for Research and the Matrix Knowledge Group decided to form an independent organization called College Measures that would focus on collecting and analyzing data, especially wage data, to inform education leaders and prospective students and thus drive improvement in higher education outcomes in the United States.
Surprises in the data
In a major effort launched in 2013, College Measures (with support from the Lumina Foundation) has worked with five states to link postsecondary student-level data with wage data for those graduates and to make the results easily accessible to the public. The five states are Arkansas, Colorado, Tennessee, Texas, and Virginia. Examining the data reveals four key patterns that are likely to surprise anyone who spends most of his or her life thinking about and working in elite institutions and strong research departments.
Some short-term higher education credentials are worth as much as long-term ones. Although most people probably think of a bachelor’s degree when they think of a college degree, in 2013 the nation’s system of higher education, mostly through community colleges, granted almost as many shorter-term credentials—including associate’s degrees and occupationally oriented certificates—as bachelors’ degrees (see Table 1). And the number of sub-baccalaureate credentials awarded is growing far faster than either the number of bachelor’s or master’s degrees awarded.
More than 1 million students earned associate’s degrees in 2013, making it the second most common postsecondary credential granted in the nation. Community colleges, the public institutions that produce most associate’s degrees, have dual missions: preparing some students who are planning to transfer to four-year institutions and preparing others to enter the job market. Among the five states in our study, Virginia best exemplifies the double role: It explicitly labels courses of study in its community colleges as either “bachelor’s credit” or “occupational/technical credit.” Texas recognizes associate’s degrees as “academic” or “technical,” and Colorado offers the transfer-oriented associate of arts/sciences degree as well as the career-oriented associate of applied sciences degree.
TABLE 1
Numbers of credentials awarded in the U.S., 2008 and 2013
What is striking is that in four of the five states in our study, the average first-year earnings of associate’s degree graduates are higher than the earnings of bachelor’s degree recipients. In Tennessee, which does not distinguish between technical and academically oriented degrees, associate’s degree graduates earn over $1,300 more in their first year after graduation than do bachelor’s graduates. In Texas, Colorado, and Virginia, where we can identify which track each graduate took, the wage premium for technical associate’s degrees is even greater. Texas graduates with technical associate’s degrees earn in excess of $11,000 more in the first year after graduation than do other bachelor’s graduates statewide. In Colorado, graduates with associate of applied sciences degrees out-earn bachelor’s degree graduates by over $7,000 statewide. The gap in Virginia is smaller, only $2,000, but remember that the technical associate’s degree is faster and cheaper to earn than a bachelor’s degree, so even a $2,000 gap implies a better return on investment.
In contrast, graduates from transfer-oriented associate’s degree programs in the job market after completion lag both their peers graduating from technical programs and bachelor’s degree graduates. For example, students in Colorado who earn associate of arts/sciences degrees lag technical/career completers by $15,000 and lag bachelor’s graduates by $8,000. In Virginia, the gap is smaller but still substantial: $6,000 between technical associate’s graduates and bachelor’s credit graduates, and $4,000 between bachelor’s graduates and bachelor’s credit associate’s graduates. The biggest gaps are in Texas, where over $30,000 separates the two types of associate’s graduates, and $19,000 separates academic associate’s graduates from bachelor’s graduates.
In short, technical/career-oriented associate’s degrees can help launch graduates into well-paying jobs. For students who are trying to use the associate’s degree as a pathway into a bachelor’s program but are in the labor market, the value of the degree is far less.
Even as the value of the technical associate’s degree is becoming clear, community colleges are granting an increasing number of even more career-oriented credentials in the form of certificates. In 2013, more than 600,000 certificates were awarded. Given the ballooning costs of college and an uncertain job market, it is probably not surprising that students are enrolling in these programs in growing numbers. Certificates, which often cost less than an associate’s degree, promise success in the job market, according to a number of studies.
Despite the rapid growth of certificates, the federal government has not yet caught up with the growing importance of this credential. For example, whereas the nation has in practice agreed that an associate’s degree encompasses an average of 60 hours of study and a bachelor’s degree encompasses 120 hours, certificate programs can last a few months to two years and cover such diverse areas as cosmetology, construction trades, and aircraft mechanics.
The data we have gathered from the states can help shed light on some of the questions surrounding certificates. Perhaps the most interesting comparison is between certificate holders and associate’s degree graduates. One argument often put forward in support of certificates is that they can produce high earnings for completers while requiring less time than a traditional associate’s degree. We find some evidence of this, but much of the truth of this statement depends on the type of associate’s degree and the length of the certificate being compared.
In Colorado, for example, holders of both long- and short-term certificates have higher first-year earnings than students with the transfer-oriented associate of arts/sciences degree who are in the labor market. Similarly, in Virginia, students with a certificate in mental and social health services and allied professions have higher earnings than students who graduated with a bachelor’s credit associate’s degree. In Texas, certificate holders earn almost $15,000 more on average than graduates of academic associate’s programs, but about $15,000 less than students with technical associate’s degrees. In Tennessee, students with long-term certificates out-earn associate’s degree graduates by approximately $2,000, but short-term certificate holders earn about $4,500 less.
In short, certificates of longer duration (1 to 2 years) may represent a viable alternative to an associate’s degree. This is particularly true when comparing certificates with academic transfer-oriented associate’s degrees.
Although longer-term certificates, on average, have market value, there is considerable variation in their value depending on the field in which they are granted. Across the states, certificates in manufacturing, construction trades, and health-related fields generate the most earnings. In Virginia, for example, certificate completers in industrial production technologies ($38,000) and precision metal working ($40,000) have higher first-year earnings than bachelor’s degree graduates ($36,000). Similarly in Arkansas, students completing a certificate in airframe mechanics and aircraft maintenance technology on average earn $8,000 more than the average bachelor’s graduate ($41,000 versus $33,000). In Tennessee, students completing a certificate in construction trades have among the highest average earnings ($61,000) of any program of study we identified in the state. In Texas, students completing certificates in radiography and in hospital/health care facilities management had average earnings of more than $69,000, compared with $40,000 for bachelor’s graduates. In contrast, students completing certificates in cosmetology or culinary arts tended to have far lower salaries.
Where a student graduates from has an impact on earnings, but less than usually thought. There is a whole world of higher education beyond the Ivy League and the state flagships. And although our study has no information on the earnings of Ivy graduates, the state flagship universities are included in the data—and at least judged by earnings, students who do not win admission into these big-name schools need not despair. Of course, it is important to keep in mind that the state flagships do send more students to professional schools and graduate work than do the regional campuses, but most students do not go on beyond the bachelor’s degree, and far more students are educated in the regional campuses than in the flagships.
Several consistent messages emerge from looking at the wages of graduates across institutions. One is that graduates’ first-year earnings range widely. In all five states, at least $18,000 separates the schools where bachelor’s graduates earn the most from schools where graduates earned the least during their first year on the job. The difference between master’s graduates from different institutions ranges from more than $10,000 in Arkansas to more than $40,000 in Tennessee and Texas.
However, each state has schools whose graduates fall far below their peers and, conversely, schools whose graduates outperform peers graduating from other institutions. But while the range is large, within each state a large proportion of schools have graduates who earn roughly the same after graduating. In Colorado, bachelor’s degree holders from 6 of the 15 four-year colleges and universities have median earnings clustered between $37,000 and $39,000. Similarly, bachelor’s graduates from 10 of the 22 four-year institutions reporting from Arkansas have overall first-year earnings that cluster between $30,000 and $34,000.
Graduates from flagships who go straight to work do not, on average, earn more than graduates from many regional campuses. The average first-year earnings of graduates from the University of Texas at Austin ($38,100), for example, are lower than the state median for bachelor’s graduates ($39,700) and lower than graduates from several University of Texas regional campuses (including UT Permian Basin, Pan American, Dallas, and Arlington, with campus medians all over $40,000). Similarly, in Colorado, graduates from the flagship university in Boulder have lower starting wages ($37,700) than bachelor’s graduates from Metropolitan State University ($38,500) and the University of Colorado Denver ($43,800).
It also is notable that in states where private not-for-profit colleges are in the database, including Virginia and Arkansas, graduates from these types of schools often have low first-year earnings. Yet the “net price” of attending these schools can be high. According to the National Center for Education Statistics, the average net price of attending Hendrix College in Arkansas is over $20,000 per year, but graduates on average made less than $26,000. Similarly, Hollins University in Virginia had an average net price of almost $21,000, just about equal to the first-year earnings of its graduates ($23,776). In contrast, Central Baptist college in Arkansas had a net price of less than $11,000, but its graduates had earnings of over $40,000. We have found in other states that the relationship between price and earnings is not straightforward.
Field of study is more important than place of study. The labor market rewards technical and occupational skills at all of the three degree levels—associate’s, bachelor’s, and master’s—that we have studied. Graduates with bachelor’s degrees in music, photography, philosophy, and other liberal arts fields almost always fall at the bottom of the list of majors organized by earnings. In the top slot in every state is an engineering field. In Arkansas, bachelor’s graduates with a degree in music performance overall earn less than $20,000, whereas engineering graduate earn almost three times that ($57,000). In Virginia, graduates with philosophy degrees average just over $20,000 whereas graduates with degrees in petroleum engineering average almost $62,000. Graduates with bachelor’s degrees in business administration usually have overall earnings above the overall wages of bachelor’s degree students statewide (for example, in Colorado, it is $43,000 for business versus $39,000 for all bachelor’s graduates; in Virginia, it is $36,000 versus $33,000 overall).
Until the data about student earnings across the nation are unearthed and put to full use, many students will make poor decisions about schools and programs—decisions that will leave them saddled with debt and clamoring for some kind of government bailout.
Many people who look at these early career data argue that the value of liberal arts degrees emerges in the longer run, because it might take liberal arts graduates longer to launch careers. But will the philosophy major who is now a barista at Starbucks really be a barrister in a large law firm 10 years from now? Although we do not yet have long-term wage data, the data from master’s graduates suggests that those in technical fields fare better that far up the educational ladder.
In Arkansas, for example, master’s graduates in creative writing have overall first-year earnings of less than $30,000. In Virginia, master’s graduates in creative writing earn less than $32,000. In both states, this was the lowest-paid major, whereas nurse anesthesiologist was the highest at about $130,000. In Tennessee, over $36,000 separated the master’s graduates in the lowest-paid fields (foreign languages, literature, and linguistics) from the highest-paid (health professions and related programs).
Overall, as with the associate’s and bachelor’s degrees, master’s degrees in technical fields yield far greater returns than do the liberal arts.
The S in STEM (science, technology, engineering, and mathematics) is oversold. Politicians and policymakers at the federal and state levels, among many others, have trumpeted the need for STEM education to feed the STEM workforce. But the labor market is far more discriminating in what kinds of degrees it rewards. Our data show that employers are paying more, often far more, for degrees in the technology, engineering, and math parts of STEM. And no evidence suggests that biology majors earn a wage premium. Chemistry majors earn somewhat more, but they do not command the wage premium of engineering, computer/information science, or math majors.
Three of our states—Texas, Colorado, and Virginia—have sufficient numbers of students in large STEM fields to allow an exploration of the link between STEM education and wages. The data show overall that although students in technology, engineering, and math experience greater labor market success than other students, the science fields do not generate any greater labor market returns than, for example, the decidedly not-STEM field of English language and literature. If we take wages as a signal of demand for workers, students with science majors are not in high demand.
We turn first to Texas. Given the number of students in Texas, we are able to report the first-year earnings of graduates with associate’s, bachelor’s, and master’s degrees in all of the major fields of studies we have chosen to investigate (see Figure 1).
At the associate’s degree level, there is a substantial wage increment for graduates with two-year degrees in computer and information sciences ($30,000) and in mechanical engineering ($32,000). However, graduates with associate’s degrees in the three other STEM fields studied fare less well. Their average first-year wages—$17,000 in biology, $18,000 in chemistry, and $18,000 in math—are considerably lower, and even lower than for graduates with associate’s degrees in the non-STEM field of sociology ($21,000).
Looking at the wages of STEM bachelor’s graduates, mechanical engineering graduates earn, on average, more than graduates of any other field—often by a factor of 2. Mechanical engineering graduates earn $74,000, whereas computer/information sciences bachelor’s graduates, the next closest group, earn $58,000. Math majors do well ($49,000), earning more than graduates in most other fields of study. Chemistry majors at $36,000 do better than biology majors ($26,000), who earn less than graduates with degrees in English ($32,000), sociology ($33,000) or psychology ($29,000).
In Virginia, there are fewer data available, but some observations are possible. We have found that graduates in engineering and computer/information sciences earn the most ($52,000 and $51,000, respectively), followed by math majors ($37,000). The average wage of chemistry graduates ($31,000) is only slightly higher than for sociologists ($30,000), psychologists ($29,000), or English majors ($29,000), whereas bachelor’s graduates in biology ($28,000) lag all of these other fields.
This is virtually identical to observations in Colorado, where graduates with degrees in engineering, computer science, and math earn the most. Graduates with chemistry degrees earn slightly more than graduates from other fields, and graduates with biology degrees earn about the same as graduates in sociology or English language arts.
At the master’s level, across the states, graduates with degrees in mechanical engineering, computer/information sciences, and mathematics are the highest paid, with chemistry graduates also earning more than graduates from the remaining fields. In Texas, where biology graduates with master’s degrees increased their earnings by about 50% as compared with biology graduates with a bachelor’s degree (from $26,000 to $40,000), their earnings are within $2,000 of sociology ($39,000), psychology ($38,000), and English ($38,000). In Virginia, master’s graduates in biology ($36,000) are paid virtually the same as master’s graduates in sociology and less than graduates in psychology ($44,000).
These findings show the power of linking student data to wage data. Students and policymakers who have been bombarded by the rhetoric invoking the critical importance of STEM education might assume that majoring in any STEM field will lead to better wages. Yet the objective wage data show that in each state and at each level of postsecondary credentials, graduates with biology degrees, the field that graduates the largest number of science majors, earn no more than sociology or psychology graduates. Chemistry graduates are fewer in number, and we often cannot report wage data for them. But when we can, chemistry graduates usually do slightly better than biology majors, but lag technology, engineering, and math graduates.
Knowing before going
As student debt hits $1 trillion nationwide, better decisions about where and what to study based on likely earnings after graduation could ease students’ financial woes and the nation’s growing debt problem. In a recent article on usnews.com, Mitchell Weiss, a cofounder of the University of Hartford’s Center for Personal Financial Responsibility, presented a valuable rule of thumb: “students should cap their debt based on future earnings . . . You don’t want to borrow more than what you can reasonably expect to earn.” Weiss further advised that students can make sure that their monthly loan payments do not exceed 10% of their income by keeping the total amount borrowed at or below the average first-year earnings for their degree field.
FIGURE 1
First-year earnings of Texas graduates, by degree level and major
In short, to make well-informed decisions, students need information about the potential earnings of graduates from each school and program under consideration. The states that have partnered with College Measures are working to make this information available to all. (We also are working with the states to improve current efforts in a number of ways; for example, by collecting wage data for students who graduated as many as 10 years ago to improve long-range projections of earnings potential.) A close reading of the data already on hand shows some key lessons about what graduates should take into account while deciding about what degree to pursue and where to get it.
First, the data show the folly of thinking about sub-baccalaureate credentials as “also-rans” in the education derby. True, graduates with four-year bachelor’s degrees usually earn more than those with associate’s degrees over their lifetimes, but graduates with associate’s degrees and many certificates can command a solid wage and, in the early post- college years, make as much as, or even more than, graduates with bachelor’s degrees.
Further, the higher education establishment’s emphasis on liberal arts bachelor’s degrees is out of sync with students’ legitimate concerns about debt and earnings and about the needs of local labor markets. Associate’s degrees, especially in technical fields, can be valuable. At the bachelor’s and master’s levels, students with technical/career- oriented degrees usually earn more, sometimes far more, than liberal arts graduates.
Finally, students with the same majors in the same state can achieve different incomes upon graduation depending on which college they attend. Students need to find out whether these comparative data exist across the schools they are considering. And if the data do not exist, they should ask their state legislators why not.
More generally, students, their parents, and their government representatives must insist that objective information about first-year earnings should be at every college-bound student’s fingertips. The White House’s proposed “college scorecard” might someday show earnings associated with different schools and programs, and the president has proposed sharing earnings and other data with students and their families. But even though taxpayers have paid hundreds of millions of federal dollars to build student-data systems that enable many states to report earnings data for each program in the state, most of this information gathers dust in data mausoleums, while the U.S. Department of Education has consistently failed to require states to use it.
Until the data about student earnings across the nation are unearthed and put to full use, many students will make poor decisions about schools and programs—decisions that will leave them saddled with debt and clamoring for some kind of government bailout. Students, lenders, taxpayers, and states should demand this information, and the federal government should make it easy to find and use. In the meantime, states that have taken the lead in releasing these data should be applauded and other states encouraged to follow their example.
While the wait continues for governments to make these data available, well over 6 million people have already fallen behind on their student loan repayments. Without the ability to make better-informed decisions, it can only be expected that more and more students will face drowning in a sea of red ink.
The Lessons of J. Robert Oppenheimer
“Whatever the enemy may be planning, American science will be equal to the challenge.”
—Franklin Delano Roosevelt, June 29, 1943
A commonplace of national security debates is that science, supported by the state, is the first and last line of defense against our enemies.
Science was not always understood in this light. Franklin Delano Roosevelt’s words to J. Robert Oppenheimer, quoted above, were meant to be motivational, not prophetic. Some 75 years before drones ruled the skies and the National Security Agency’s digital panopticon mapped the interactions between suspiciously menacing characters around the planet, U.S. science first began to thrive on the margins of military power. World War II altered irrevocably the status of science as a public good, and nothing revolutionized the scientific equation more than the race to build the first atomic bombs.
A race in name only, as the United States proved to be the sole serious contender. Under the skillful leadership of Oppenheimer, a brilliant young physicist plucked from obscurity by the Roosevelt administration during the most dangerous months of the war against Germany and Japan, the Manhattan Project provided a stunning example of the power of bringing together the world’s biggest brains in pursuit of a winning weapon. When in July 1945, in the deserts of New Mexico, the Manhattan leadership witnessed the first atomic explosion, the nature of power in human civilization, and the role of science in delivering that power, had changed forever.
For many scientists, especially physicists, the new terms of their existence proved intoxicating. Lionized as a saviors by the mass media, criticized as the “new priesthood” by renegades such as Ralph Lapp (himself a physicist), scientists were showered with money and wooed by the military and political establishments after World War II. And Oppenheimer emerged as a luminary of almost blinding power. Chair of the government’s secret committee on the future of nuclear weapons development, he lived and worked at the center of science’s new power.
By the late 1940s, however, the unanimity within the U.S. political elite, so crucial to defeating Germany and Japan in war, began cracking in the cold peace that ensued. President Roosevelt had maintained a stiff but effective alliance with “Uncle Joe” Stalin’s Soviet Union. Harry Truman, who inherited the presidency on FDR’s death, could not contain the rampant suspicions of the Soviet Union. Pivotal figures, including Oppenheimer, advised against automatically taking the arms race to the next level: from atomic to hydrogen bombs. This Oppenheimer wing wanted to test the capacity of the Soviet Union and the United States. to reach an accord on arms control, before dramatically escalating the power of nuclear weapons.
Oppenheimer wasn’t alone in advancing this position. Vannevar Bush, who as director of the wartime Office of Scientific Research and Development was Oppenheimer’s ultimate boss on the Manhattan Project, and James Conant, Bush’s chief assistant and president of Harvard from 1933 to 1953, also pressed the U.S. government to defer the testing of H bombs until a deal with Soviet Union to ban them was fully explored. Bush went so far as to join in a failed private campaign to delay, or cancel, the first test of an H bomb, scheduled by President Truman only days before a national election for his successor, won by Dwight Eisenhower. Bush complained that Truman, a lame duck, had robbed the incoming president of the chance to say yea or nay to the H bomb, describing the test as a “point of no return” in the escalating arms race with the Soviet Union.
Yet Oppenheimer alone suffered the humiliation of losing his security clearance in a tortured 1953 secret hearing of the Atomic Energy Commission that he could have avoided by simply resigning from a government post whose term was expiring anyway.
The question of why Oppenheimer suffered such grievous political penal- ties—and why his suffering mattered to so many important scientists—has been explored by some of the finest historians the United States has ever produced and by many of Oppenheimer’s contemporaries in physics, perhaps most notably I. I. Rabi. Within months of Oppenheimer’s death, Rabi led an extraordinary memorial gathering in which he described the enigmatic source of Oppenheimer’s powers both as a physicist and a leader. Not only did he seem capable of discovering, Rabi said, “everything worth discovering,” he had an effect on his fellow men that today is a trait present in every rock star and uber-celebrity and which Rabi, who knew Oppenheimer as well as anyone ever did, could only describe as “this spiritual quality, this refinement expressed in speech and manner, that was the basis of his charisma.”
Rabi added, “He always left a feeling that there were depths of sensibility and insight not yet revealed. These may be the qualities of the born leader who seems to have reserves of uncommitted strength.”
That the term charisma, an attribute that has come to be essential to the contemporary lingo of celebrity, could be applied to Oppenheimer wasn’t pulled out of thin air by Rabi. Not by any means. Max Weber, the German sociologist and an early analyst of the scientist as social actor, introduced the term to explain the “gift of grace” that some intellectuals appeared to possess. As Charles Thorpe, an Oppenheimer biographer and a lecturer in science and technology studies at University College, London, has explained, “Weber described charisma as a revolutionary force, fundamentally opposed to any form of institutional routine, and especially to bureaucratic organization.” Almost as if he had Oppenheimer in mind, although writing before World War II, Weber observed in his essay, “The Sociology of Charismatic Authority”: “The charismatic structure knows no regulated ‘career,’ ’advancement,’’ salary,’ or regulated or expert training.” A self-styled manager and an independent, often contradictory advocate, Oppenheimer seemingly embodied a Weberian vision of a new kind of existential intellectual.
The Oppie effect
Oppenheimer’s undeniable charisma anchored his outsized influence on his peers. He stood both inside the center of power and outside of its institutional constraints. He was a kind of Nietzschean Übermensch who in the face of the increasing bureaucratization of science and military affairs could on the one hand celebrate the creation of a new weapon of terrible power and at the same time tell a president (as he did Truman), “Mr. President, I have blood on my hands.” And which physicist besides Oppenheimer, in the wake of Hiroshima, could have told his glorified colleagues that “the physicists have known sin”?
Because of Oppenheimer’s charisma and his unusual ability to straddle worlds both artistic and scientific, what Herb York, in his classic memoir The Advisors, describes as the dispute between “hawks” and “superhawks” made Oppenheimer (whom York rightly calls a hawk) a high-value target for the superhawks. Edward Teller, the chief promoter of the H bomb in the early 1950s, and Lewis Strauss, chair of the Atomic Energy Commission and Teller’s political guardian, concluded that the shortest path to destroying the widespread opposition to unqualified development of the H bomb by the United States was to destroy Oppenheimer. They did. That Oppenheimer assisted his opponents by arrogantly dissembling about some of his minor, however dubious, actions to obscure his personal ties to members of the U.S. Communist Party made his defeat all the more frustrating to his friends, who also suffered political marginalization, if less publicly.
The whole saga is told expertly in the Pulitzer Prize-winning 2005 biography of Oppenheimer by Martin Sherwin and Kai Bird. The ambiguities of Oppenheimer’s personal morality were plumbed by S. S. Schweber, a theoretical physicist turned historian of science, in his In the Shadow of the Bomb, published in 2000. The entire mesmerizing transcript of Oppenheimer’s security hearing has long been available. And for those who want to learn more about scientists as tools of the state and the state as a tool of science, Thorpe’s Oppenheimer: the Tragic Intellect, published in 2006, offers rich rewards.
So what does Ray Monk’s new biographical tome—Robert Oppenheimer: A Life Inside the Center —add to the enormous literature on this talismanic subject? Not much, actually. Monk, a British philosopher and the author of a monumental biography of Ludwig Wittgenstein and another such study of Bertrand Russell, writes as if he’s learned recent U.S. history on the fly; his grasp of the role of science in U.S. society is no better. A professor of philosophy at the University of Southampton, Monk insists he wants to rescue from obscurity Oppenheimer’s formidable achievements in physics, chiefly arising from his pre-war work, even while conceding that Oppenheimer was no Einstein.
Neither was he a Heisenberg or a Niels Bohr. Undeniably, Oppenheimer endlessly fascinates people because of his terrible gift for managing the making of the atomic bomb, and for his peculiar political demise in the 1950s. Monk isn’t original on Oppenheimer’s fall from grace but neither is he wrong. Oppenheimer’s exile from power often is compared to Galileo’s brutal brush with Church authorities who insisted he recant his scientific judgments. Yet Oppenheimer never faced this sad choice, between choosing truth or acceptance by the powerful, because he always defended the decision to both build the atomic bomb and to use it. “We had great cause to do it,” Monk quotes Oppenheimer as telling CBS News in 1965, on the 20th anniversary of the bomb.
In this same interview, Oppenheimer said that building weapons of mass destruction was “not the natural business of the scientist.” But it was Oppenheimer’s business—and ever since 1945, the business of science or, more precisely, one in the portfolio of core activities.
When Oppenheimer’s boss Vannevar Bush published a collection of essays in 1967, the year of Oppenheimer’s death, he entitled the book, Science is Not Enough. Bush was explicitly referring to the limits of rational knowledge, to the importance of recognizing that science settles some matters of the human experience, but not others. He was also implying that scientists could not work effectively without partnerships with policymakers and politicians. Oppenheimer, ever enigmatic and aloof, might have always been the smartest guy in the room, but he mismanaged his relationships with the political and policy spheres. Usually presented as a tragedy, Oppenheimer’s story is more clearly viewed today as a cautionary tale about hubris and the role of the intellect in the world of the heart.
The New Normal in Funding University Science
Science policy analysts have focused recently on the federal budget sequester and the dramatic effects it could have on funding scientific R&D in U.S. universities, certainly a serious problem. But looking only at the sequester misses the larger picture. The sequester simply makes acute a chronic condition that has been getting worse for years. Even if Congress removed the sequester tomorrow and R&D funding returned to pre-sequester levels, university researchers would still face serious and growing problems in funding their research programs, systemic problems that arise from the R&D funding system and incentive structure that the federal government put in place after World War II. This reality dictates that policymakers, research administrators, and the scientific community must adjust to continuing low success rates if scientific research is to continue to flourish on university and college campuses.
Researchers across the country encounter increasingly fierce competition for money. Funding rates in many National Institutes of Health (NIH) and National Science Foundation (NSF) programs are now at historical lows, declining from more than 30% before 2001 to 20% or even less in 2011 (with an uptick in 2009 associated with stimulus funding). The funding rates in some programs are substantially worse, dipping into the single digits. At these success rates, even the most prominent scientists will find it difficult to maintain funding for their laboratories, and young scientists seeking their first grant may become so overwhelmed that individuals of great promise will be driven from the field. As the Chronicle of Higher Education reported in 2013, the anxiety and frustration among principal investigators were manifested in the form of a letter to NSF, signed by more than 550 ecologists and environmental scientists, criticizing the negative impact that new policies, designed to cope with the flood of proposals, would have on the progress of science, junior faculty members, and collaborative research.
Many scientists and outside observers blame these low funding rates on a decline in the federal commitment to funding scientific research. However, the evidence tells another story. The growth of the scientific enterprise on university campuses during the past 60 years is not sustainable and has now reached a tipping point at which old models no longer work and expectations on the part of universities and university-based scientists have to be brought into line with fiscal realities. At the same time, federal funding agencies must work with universities to ensure that new models of funding do not stymie the progress of science in the United States, but instead continue to fund the most deserving research, while recognizing the need to keep a broad portfolio of investigators active in order to hedge the nation’s R&D bet (it is not always easy to recognize the research programs that will bear the most fruit) and to make certain that students at a wide range of institutions can be trained by research-active scientists.
Origins of the crisis
So how did the nation get into this situation? In one sense, the answer is obvious: The demand for research money greatly exceeds the supply. And clearly the demand for research funding has gone up. More universities seek sponsored funding, and individual researchers submit more grant applications. At NIH, for example, the number of research grant applications doubled between fiscal years 1997 and 2011, from roughly 31,000 to 62,000. But that answer—demand exceeding supply—simply restates the question. Why has demand grown faster than supply? Many answers get thrown around, including the fecklessness of politicians who refuse to provide enough money for science, and a lack of understanding on the part of the general public about science and what it does for the country. But those responses clearly do not account for the increased demands that scientists have placed on the federal funding system. The deeper sources of the problem lie in the incentive structure of the modern research university, the aspirations of scientists trained by those universities, and the aspirations of less research-intensive universities and colleges across the nation. These incentives and aspirations date back decades and set up a dynamic that was bound to run into a funding crisis; it was only a matter of when. Perhaps the most surprising feature of the current crisis is that it took so long to arrive.
Since the founding of NSF in 1950, the research enterprise on university campuses in the United States has grown rapidly, especially as measured by the numbers of science and engineering doctorates awarded. The competitive grants system encouraged such growth. Principal investigators need a dedicated, inexpensive, and talented workforce of apprentices (graduate students) for research projects. Therefore, if a university wants to attract a significant amount of sponsored research money, it needs doctoral programs in the relevant fields and faculty members who are dedicated to both winning grants and training students. The production of science and engineering doctorates has grown apace. As NSF has detailed in a 2006 historical study of doctorates in the United States in the 20th century, for the five years of 1920-1924 the nation produced a total of 2,724 such degrees, an average of 545 per year. By period 1955-1959, straddling Sputnik, doctorate production had gone up by more than a factor of 10, averaging 5,662 per year. By 1995-1999, science and engineering doctorate production had gone up by another factor of 5, averaging 26,854 per year. There has been little increase since then, with the nation producing 27,134 such degrees in 2010. The growth in Ph.D. production in the latter half of the 20th century was fueled by the growth in size of science and engineering departments at major research universities, as well as by an increase in the number of universities offering such degrees.
Even though not all doctorate recipients become university faculty, the size of the science and engineering faculty at U.S. universities has grown substantially. This cadre numbered 271,550 in 2006, up from 221,682 as recently as 1993, according to NSF statistics. These scientists and engineers are spread among a much larger number of Ph.D.-granting departments than was the case 60 years ago, and these departments have adopted the norms that their faculty should be active in acquiring sponsored research money and in producing new knowledge and publications. Hence, proposal pressure goes up. These strategies make sense for any individual university, but will fail collectively unless federal funding for R&D grows robustly enough to keep up with demand.
Derek J. De Solla Price, in his prescient 1963 book Little Science, Big Science, saw that the rapid increase in resources going into scientific research could not continue indefinitely. Price put the dramatic events of his time into historical context and showed that they were part of a trend that had been developing for more than a century. At the very time that universities were enjoying rapidly growing budgets, and creating modes of operation that assumed such largess was the new normal, Price warned that it would all soon come to a halt. He pointed out that in the United States and Western Europe, the human and financial resources invested in science had been increasing much faster than the populations and economies of those regions, and that such growth could continue only as long as the absolute number of scientists remained a very small proportion of the total population and R&D budgets a small part of the total economy. Once the number of scientists reached a few percent of the population, the growth would have to slow down; otherwise, he said, “we should have two scientists for every man, woman, child, and dog in the population, and we should spend on them twice as much money as we had.” Since that result is not possible, growth in the scientific enterprise would have to slow down at some point, growing no more than the population or the economy. Science policy built on the assumption of indefinite rapid growth was bound to come to grief.
Dead-end solutions
Many other analysts have perceived a crisis in the federal funding of university science. In 2007, the National Academies published the ominously titled Rising Above the Gathering Storm: Energizing and Employing America for a Brighter Economic Future. In 2013, the Academies followed up with Research Universities and the Future of America: Ten Breakthrough Actions Vital To Our Nation’s Prosperity and Security. Both of these studies sounded an alarm about the potential decline in U.S. global leadership in science and technology and the grave implications of that decline for economic growth and national security. Both also contained numerous analyses and recommendations; at their core, however, was a proposal for the federal government to spend significantly more money on research, especially on basic research. As expressed in Gathering Storm: “Increase the federal investment in long-term basic research by 10% each year over the next 7 years through reallocation of existing funds or, if necessary, through the investment of new funds.” This would mean roughly doubling that budget in seven years. In a footnote, the report recommended that the “reallocation” of money for this doubling could come from any federal agency, not just the research agencies. In addition to this doubling, the study called for an additional $100 million for special early-career investigators and yet another $500 million per year for facilities and instruments. The follow-up report on research universities echoed the call for a doubling of basic research funding.
Although we are not opposed to increasing federal funding for research, we are not optimistic that it will happen at anywhere near the rate the Academies seek, nor do we think it will have a large impact on funding rates. Universities and colleges have demonstrated a remarkable capacity for absorbing increases in federal funding by increasing research infrastructure, as was seen when Congress doubled the NIH budget over the course of five years beginning in the late 1990s. More good projects were funded as a result of the infusion of funds, but success rates for grants remained flat during the doubling and dropped immediately afterward. A more serious problem with the recommendation to double the basic research budget over the course of seven years is that it is devoid of context. It does not acknowledge the current pressure on the federal budget or the historical relationship that R&D funding has had to that budget.
The pressure on the federal budget is obvious. Where R&D fits in that budget is more complex. R&D funds do not come out of the budget as a whole, but rather out of the discretionary budgets, whether defense or nondefense, which are little more than one-third of the total budget. As Daniel Sarewitz pointed out in 2007 in this journal, when examining R&D spending as a percentage of the discretionary budget, a measure the American Association for the Advancement of Science has been tracking for decades, what jumps out is the remarkable consistency of nondefense R&D spending. After a steep rise and fall in the 1960s, mostly due to the Apollo program, nondefense R&D settled down by the middle of the 1970s to make up roughly 10% of the domestic discretionary budget, and there it has stayed for almost 40 years. This has held true during both Republican and Democratic administrations and Congresses and when the White House and Congress have been held by the same or different parties. The defense portion of the R&D budget has been more volatile over the same period, fluctuating from 10 to 15% of the discretionary budget.
What this means for the future of federally funded R&D is that universities should not expect any radical increases in domestic R&D budgets, and most likely not in defense R&D budgets either, unless the discretionary budgets themselves grow rapidly. Those budgets are under pressure from political groups that want to shrink government spending and from the growth of spending in mandatory programs. There is no reason to assume that R&D will be able to make claims on a larger portion of the discretionary budget, because other existing programs can be expected to defend their budgets. Of course, if the total discretionary budget increases due to economic growth, R&D will share in that increase. It is also numerically possible, although it seems politically unlikely, that defense R&D could pick up more of the task of funding basic research, the sort most often undertaken at universities. The basic point is that the growth of the economy will drive increases in federal R&D spending, and any attempt to provide rapid or sustained increases beyond that growth will require taking money from other programs. The solution to the problem of funding university science and engineering research will not come from ever more massive infusions of new money from the federal government. The demand for research money cannot grow faster than the economy forever and the growth curve for research money flattened out long ago.
Path out of crisis
To chart a realistic path out of this crisis, it is necessary to start by reframing the goal. The goal cannot be to convince the government to invest a higher proportion of its discretionary spending in research. For 40 years, R&D funding has competed with a host of other national needs—from road and bridge building to social welfare to public health to education—and for 40 years has come away with 10% of the discretionary civilian budget. Getting more is not in the cards, and some observers think the scientific community will be lucky to keep what it has. Instead, the goal must be to sustain the most vigorous scientific research programs possible on university campuses, given the reality that levels of federal funding are going to grow slowly in concert with the growth of the U.S. economy, at best.
The potential to take advantage of the infrastructure and talent on university campuses may be a win-win situation for businesses and institutions of higher education.
Why should universities and colleges continue to support scientific research, knowing that the financial benefits are diminishing? First, attracting federal research dollars has never been just a financial benefit. A lively research culture makes it possible for universities to attract good students and faculty as well as raise their prestige within the academic community. Second, universities take it as their mission to expand the boundaries of human knowledge, including scientific knowledge. Third, faculty members are committed to their scholarship and will press on with their research programs even when external dollars are scarce. Fourth, the training of scientists, even at the undergraduate level, does not take place in teaching laboratories, but rather in research laboratories. If the United States is to train the next generation of scientists and reap the economic benefits associated with scientific research, it is critical to have active research laboratories, not only in elite public and private research institutions, but in non-flagship public universities, a diverse set of private universities, and four-year colleges. Talented students from a variety of backgrounds are found in all of these institutions, and the nation cannot afford to lose some of that talent by limiting cutting-edge scientific training to a small number of universities.
Universities and colleges have long accepted the reality that the federal government would not underwrite all of the scientific research efforts under way on their campuses. Indeed, institutional funds for R&D are the second-largest source of funding for academic R&D, rising from 12% in 1972 to about 20% in 1991 and remaining at that level through 2009. Increasing, or even sustaining, that level of investment will be difficult, particularly for public institutions as state support for higher education continues its inexorable decline. How then do increasingly beleaguered institutions of higher education support the research efforts of the faculty, given the reality that federal grants are going to be few and far between for the majority of faculty members? What are the practical steps institutions can take?
First, they must change the current model of providing large startup packages when a faculty member is hired and then leaving it up to the faculty member to obtain funding for the remainder of his or her career. The premise for this model is a reasonably high funding rate for grant proposals. The thinking goes as follows: Provide a faculty member with a laboratory and the means to generate preliminary data and anyone worth his or her salt will win a grant and then go on to sustained funding over a career. The new reality of low funding rates calls for a new model, one in which universities and colleges recognize that even the most distinguished researchers will experience gaps in funding and require in-house assistance to maintain a research program. The need for assistance throughout a career can be met only if universities invest less in new faculty members and spread their internal research dollars across faculty members at all stages of their careers, from early to late.
Moving toward smaller startup packages will not be easy. Faculty members in the sciences and engineering see the size of a startup package as a signal of an institution’s commitment to research, and a university that unilaterally reduces its startup packages will find it difficult to attract highly accomplished job candidates. Negative repercussions may be ameliorated by a national conversation about changes in startup packages and by careful consultations with prospective faculty hires about long-term support of their research efforts. Many prospective hires may find smaller startup packages palatable, if they can be convinced that the smaller packages are coupled with an institutional commitment to ongoing research support and more reasonable expectations about winning grants.
Smaller startup packages mean that in many situations, new faculty members will not be able to establish a functioning stand-alone laboratory. Thus, space and equipment will need to be shared to a greater extent than has been true in the past. This will place increased emphasis on the construction of open laboratory spaces and the strategic development of well-equipped research centers capable of efficiently servicing the needs of an array of researchers. The phaseout of the individual laboratory, which is already under way at many universities and medical centers, brings with it enhanced opportunities for communication and networking among faculty members and their students. Collaborative proposals and the assembly of research teams that focus on more complex problems can arise relatively naturally as interactions among researchers are facilitated by proximity and the absence of walls between laboratories. Universities can compete for top faculty members based in part on the collaborative opportunities rather than simply the size of the startup package.
An increased emphasis on team research will place greater demands on research administrators (deans, vice presidents for research, provosts) to be fully engaged with their research faculty members, so that investments in the research enterprise (such as new hires and new equipment) can be directed at projects that have good buy-in from the faculty, have the greatest chance of receiving external funding, and have the potential to lead to important results. Faculty members who are at the beginning of their research careers will require careful mentoring to ensure that they learn how to work both as part of a team and independently. Involvement in multiple projects should be encouraged, and it will be incumbent on senior faculty members to provide junior faculty members with thorough mentoring and with prudent leadership opportunities.
Even with careful mentoring and thoughtful grooming of junior faculty for leadership opportunities, it is the rare assistant professor who will be in a position to lead a research team. The more likely trajectory of a junior faculty member will evolve from contributing team member to increasing leadership responsibilities to team leader. Because contributions to a team and the development of leadership qualities are unlikely to be apparent to outside evaluators, internal evaluations of contributions and potential will become more important in tenure and promotion decisions. Successful leadership of a research team is likely to become an important criterion for promotion to full professor at many research universities.
Low success rates for grant proposals at the major federal funding agencies will not deter faculty members with active research programs from requesting support from those agencies, but relationships with foundations, donors, state agencies, and private business will become increasingly important in the funding game. The opportunities to form partnerships with business are especially intriguing. Many businesses have cut back their R&D infrastructure, so the potential to take advantage of the infrastructure and talent on university campuses may be a win-win situation for businesses and institutions of higher education. Businesses can tap into the expertise of highly skilled scientists and their students on an as-needed basis, while scientists gain insight into the questions important to businesses and the means by which to translate research results into marketable products.
Our suggestion is hardly new, and some universities have already developed extensive relationships with businesses. In order for such collaborations to expand, leaders in both sectors need to rethink how and why they can take advantage of joint work and the diversity of forms that such collaboration can take. If universities wish to replace a significant portion of their federal funding with money from the private sector, businesses will need to greatly expand their university work. Industry has funded only a modest portion of university R&D, falling to about 5% in 2011 from 7 to 8% in the early 1950s, according to NSF’s National Patterns of R&D Resources. How much industry might be able or willing to increase that funding is difficult to predict, but even a large percentage increase in such funding will represent only a small increase in university R&D funds, considering the system as a whole. Obviously, for a few specific universities, industry funding could provide a considerably larger fraction.
Further complicating university collaborations with business is that past examples of such partnerships have not always been easy or free of controversy. The biotechnology revolution created many deep relationships between firms and universities. This led to considerable controversy, as some faculty members worried about firms dictating the research priorities of the university, pulling graduate students into proprietary research (which could limit what they could publish), and generally tugging the relevant faculty in multiple directions. To whom did faculty members owe their loyalty, and what were appropriate constraints on faculty members whose work attracted the biotech firms? The large research universities had to grapple with these problems and developed rules and guidelines to control them. The results of that work should be widely disseminated to help head off some of these problems.
University faculty and businesspeople often do not understand each other’s cultures, needs, and constraints, and such gaps can lead to more mundane problems in university/industry relations, not least of which are organizational demands and institutional cultures. University researchers need to be sensitive to the intense deadlines firms may face, and firms need to realize that they cannot approach a university during the last two weeks of spring term and ask that six faculty members drop everything and spend the next month working full-time on a new project. That said, both sides have good reasons to work out those differences. In addition to funding for research, universities can receive indirect benefits from such relationships. High-profile partnerships with businesses will underline the important role that universities can play in the economic development of a region. Perhaps the biggest barrier to genuine collaboration will be adjusting the expectations of both sides. Universities have to see firms as more than just deep pockets, and firms need to see universities as more than sources of cheap skilled labor.
These extramural relationships can also extend beyond the private sector. University researchers and their students can take on problems relevant to local and state governments or nonprofit organizations that operate in their area, possibly with assistance from foundations or other philanthropy. An article in the June 21, 2013 issue of Science pointed out how important private philanthropy is to university research programs, although some people quoted in the article doubt that it can replace large sums of federal or state money. According to NSF’s National Patterns data, nonprofit entities provided almost 10% of university and college R&D funds in the early 1950s but they provide only 7 to 8% today. Universities can encourage new outreach efforts on the part of their faculties by honoring all successful efforts to generate research dollars, not only those that result in NSF and NIH grants. Greater local involvement would provide other benefits to universities and colleges. Institutions of higher education that become scientific and engineering resources for the localities and regions in which they are located can make a stronger argument for financial support from state and local governments.
We do not believe that research proposed and supervised by individual principal investigators will disappear anytime soon. It is a research model that has proven to be remarkably successful and enduring, and one that appeals to talented junior and senior faculty members. In addition, initiatives such as NSF’s Experimental Program to Stimulate Competitive Research have succeeded in making serious research opportunities available to a geographically diverse set of institutions, encouraging the development of scientific talent throughout the country. However, we believe that the most vibrant scientific communities on university and college campuses, and the ones most likely to thrive in the new reality of funding for the sciences, will be those that encourage the formation of research teams and are nimble with regard to funding sources, even as they leave room for traditional avenues of funding and research.
The new reality of low funding rates for most proposals that university scientists submit to NSF and NIH results not from a lack of support for science on the part of legislators or the public, but from a buildup of the scientific infrastructure in universities and colleges that has now outstripped the funding capacity of the federal government. This budgetary landscape is unlikely to change in the foreseeable future, and universities need new models of supporting scientific research on campus if they are to remain centers of training, research, and economic development. The new normal need not be bleak, but it requires science policymakers, university leaders, and the scientific community itself to rethink models of the scientific enterprise on university campuses.
Trade Policy Is Science Policy
By the time this article goes to press, the United States and Europe will be preparing for their second round of negotiations on a comprehensive free trade agreement, scheduled to commence on October 7 in Brussels. The ground for this widely noted Transatlantic Trade and Investment Partnership (TTIP) was prepared earlier this year by a joint announcement by U.S. and European leaders during the G8 summit in Northern Ireland in June, followed by a first round of negotiations in Washington in July. The political stakes are high. President Obama has declared TTIP a priority of his administration in the second term, and attention to the subject has been raised further by the parallel efforts of a U.S.-Japan free trade agreement. Recent allegations about U.S. espionage activities in Europe that captured media attention as a result of the Snowden leaks nearly prompted EU politicians to cease trade negotiations before they really began.
The idea of aligning the United States and the EU in a free trade zone is not new. Many attempts have been made in the past to better integrate the world’s two leading economic regions, which are jointly responsible for 40% of global economic output and $ 2 billion in daily trade of goods and services. However, given the abundance of dire economic news in recent years, this time analysts and commentators were quick to tout the renewed push by government leaders on both sides of the Atlantic. Following the initial announcement during Obama’s State of the Union Address on February 12, 2013, the New York Times wrote of a “transatlantic grand bargain [..] that would cover nearly half of the world’s economy [and] give a significant boost to the global economy and renew America’s most important alliance.” The Economist titled its story “A good idea [..] that business should rush to support.” The Times (London), commented that “transatlantic trade [is] set for historic breakthrough” and cautioned against the prospect that “Britain would be excluded if it decided to pull out of the Union.” The German weekly Die Zeit heralded “The dream of a Wirtschafts [economic]-NATO,” indicating that TTIP might not only address the weary problem of a sluggish economic recovery, but also provide a much-needed new vision for the North Atlantic Treaty Organization and transatlanticism at large after the end of the cold war.
Yet, upon closer inspection, the acclamations are premature and arguably misleading. Trade tariffs and taxes—the traditional targets of free trade agreements—are already virtually nonexistent between the United States and Europe for most goods and services, averaging only 4%. The main leverage of TTIP would lie in reducing non-tariff barriers, such as the costs imposed by national regulations and red tape. As captured succinctly by Vice President Joe Biden at the Munich Security Conference: “The reason we don’t have [TTIP] already is not because no one ever thought of it; it’s because there have always been difficult issues, such as regulations and standards, which continue to divide us.” In other words, TTIP is primarily a proposition about harmonization or mutual recognition of regulatory frameworks, most notably those that deal with the high-tech, high value- added goods and services that the EU and the United States care about most. It is, in short, about of technological, health, safety, and environmental standards.
TTIP thus falls squarely within the domain of science and technology policy, a domain where agreement on common goals and mechanisms for implementation has proven contentious between Europe and the United States. The decade-long stand-off on genetically modified (GM) organisms, irreconcilable positions on international agreements such as the Kyoto Protocol on climate change and the Basel Convention on hazardous waste management, or the adherence to different safety standards in the automobile industry are cases in point that highlight how entrenched the European and U.S. positions tend to be. Admittedly, all these issues relate to trade and national economic interests; yet, framing them as trade problems misses the point of why these differences exist in the first place. Rather than being matters of economic necessity, they are expressions of national preferences on issues such as health, safety, and the environment, and as such deeply enmeshed in the value system, experiences, and political culture of a society. Likewise, treating TTIP as an economic proposition is in part misleading because it suggests ostensible consensus about economic necessity on issues that can be deeply divisive for non-economic reasons.
How discordant free trade and national science and technology policy can be may be best illustrated by two cases from TTIP’s most prominent predecessor – the North American Free Trade Agreement NAFTA. In 1997, the US-based Ethyl Corp. sued Canada under NAFTA for banning Methylcyclopentadienyl manganese tricarbonyl (MMT) as a gasoline additive. Canada had moved to ban the use of MMT in gasoline in light of new evidence of MMT’s neurotoxicity and potential public health risks, which exacerbated MMT’s already bad image as a chemical that interferes with emission control in cars. Yet, the existence of contradictory scientific evidence prevented the Canadian government from issuing an outright ban of MMT under the Canadian Environmental Protection Act. To act swiftly and prevent potential harm, the government chose to ban MMT indirectly by prohibiting its transport and import, though not its production. Ethyl Corp., the only producer of MMT, subsequently sued Canada on the basis of NAFTA Chapter 11 for unfair treatment of foreign companies vis-à-vis domestic competitors and de-facto expropriation of investments. The case was settled outside the court: Canada withdrew its ban and compensated Ethyl Corp.
In another NAFTA case, the U.S. company S.D. Myers sued the Canadian government for its 1997 ban of the shipping of polychlorinated biphenyl (PCB) wastes from Canada to be processed in the United States. Canadian regulators were not convinced that the US would transport and dispose of PCB, a highly toxic and persistent carcinogen, in accordance with international standards as defined by the 1989 Basel Convention, to which the US was not a signatory. Canada lost the case in 2000, but filed for review in 2001 with the Federal Court of Canada on the grounds that the decision exceeded the NAFTA tribunal’s jurisdiction and was in conflict with both Canada’s obligations to the Basel Treaty and its sovereign public policy in public risk matters. The court dismissed Canada’s appeal.
These two cases attracted significant attention not because of their (relatively modest) economic impact. Rather, they blatantly revealed that what is at stake in free trade agreements is not only trade barriers, but also the sovereignty of a country to interpret scientific data and handle technological risk in the ways it chooses, as well as the supremacy of democratically legitimized politics over international investments. The history of world trade suggests that the overturning of national science and technology policy by foreign company interests is neither uncommon nor unpredictable; indeed, there has been a pattern of sweeping interventions in a decisively antiregulatory manner. “With only two exceptions,” Lori Wallach and Patrick Woodall find in their book Whose Trade Organization?, “every health, food safety, or environmental law challenged at the WTO has been declared a barrier to trade.”
If TTIP is to aim for a more fruitful interaction between trade and science policy, it is paramount to better understand the sources of their frequent incompatibility. Here, at least three points are worth making from a science policy perspective. First, science and technology do not straddle nations and cultures as easily as the circulation of commercial goods might suggest. Science and technology are deeply embedded in—and constitutive of—the ways in which we choose to live as societies. For example, the arrival of agricultural products of genetic engineering in the 90s played out very differently across countries. In the United States, GM crops were seen as an extension of existing biotechnologies, not fundamentally different or more risky, and were hence understood to be well-covered under existent regulatory frameworks. Britain, traditionally in line with liberal U.S. regulation on GM organisms, was hit by the bovine spongiform encephalopathy (BSE) crisis, prior to which government authorities and experts had wrongly assured the public that “mad cow disease” could not be transferred to humans. The crisis thoroughly undermined public trust in the government’s capacity to manage risk in agricultural bio- hazards and lead to an unusually deliberative and scrupulous approach in Britain. Germany, against the backdrop of decades of strong environmental movements, took a forward-looking but extremely cautious strategy, using detailed regulation and publicly monitored experimental procedures to introduce GM crops into the environment to safeguard against any risk. Despite seemingly identical technologies, then, countries develop unique ways how to cope with compounds of scientific, technological, ethical, and social uncertainties. Instead of speaking of neatly packaged “technologies,” policy scholars thus often prefer to speak of hybrid sociotechnical systems that cannot be easily disentangled for economic or regulatory purposes. This complicates the common assumptions of ready tradability.
Second, much of science and technology regulation deals with impacts that are not easily captured by markets, and hence are not easily tradable through commercial interactions. For example, environmental externalities (e.g. air pollution from car emissions, or forest and river degradation through chemicals), health externalities (e.g. the spreading of health hazards such as BSE beef, different food processing standards such as the chlorine-washing of chicken, or different safety standards embodied by different national drug approval processes), security externalities (e.g. the proliferation of “dual-use” technologies), or privacy issues (e.g. the storage of user data from social media platforms or patient data for health services) all beget broader societal effects that are “external” to market interactions. As economics Nobel laureate Joseph Stiglitz puts it, “trade agreements typically put commercial interests ahead of other values – the right to a healthy life and protection of the environment, to name just two.” Moreover, market mechanisms may fail us because of imperfect information (e.g. lax food labeling standards), incomplete markets (e.g. absence of clear property rights for shared natural resources such as clean air or water), monopolies (e.g. IP rights granted on software, pharmaceuticals, or genes), or high transaction costs (e.g. agreeing on common technical standards for electric vehicles), all of which are considered essential to the functioning of markets. The US and the EU differ markedly on how and how much they rely on markets with regard to all of the above examples, and all of them are bound to reappear in TTIP disputes in one way or another.
Third, progress in science and technology frequently challenges the very terms and categories we use in our canons of law, including trade agreements. GM crops, stem cell research and the rise of gene patents are challenging our traditional notions of “natural” and “life,” pointing to blatant gaps in existing regulatory frameworks. Consumer genetic testing with its statistical propensity statements puts into questions our understanding of “sick” and “healthy,” and with them whole health care industries, public welfare system, and the role of medical profession. The storage of personal data on servers around the world and the ubiquity of the internet are challenging our notions of “privacy” and “freedom of speech.” These examples illustrate that laws do not refer to fixed entities, but that science, technology, and the law are in permanent mutual interaction and flux. Countries have developed complex mechanisms at the intersection of science and the law to carefully re-evaluate the legal implications as science progresses, making sense of old terminology and customs in light of recent breakthroughs. However, these mechanisms differ markedly between countries. They hinge on different bodies of law, different national precedence cases, and different legal traditions at large. Moreover, they strike different balances between scientific expertise, civic rights, and democratic participation for the acquisition and use of scientific information. The language of trade, in contrast, tends to take legal categories as given and de facto identical across nations, while treating de jure differences as mere historical relics and barriers. They are blind to the fact that to harmonize regulation across high-tech nations is to also question what is meant by such terms as “life,” “health,” “private” and “safe” in these societies, and with it the very ways in which citizens relate to science and technology. As a result of this ignorance, the deeper causes of regulatory differences and the limited success of previous free-trade attempts remain unexplained. The protracted struggle to turn the EU alone into a uniform regulatory space in science and technology matters stands witness to the inadequacy of any broad-brush approach.
What is to be learned from these three “complications?” Science, technology, and the economics of trade are intertwined in many important ways. Yet, science and technology policy follows—and should follow—different rules and rationales than trade, and it is important to maintain this normative distinction. Differences in science and technology policy are not simply barriers to trade, but the result of decades-long and often painstaking deliberation of societies about how much risk they are willing to take, to whom they turn for scientific advice, and what priority they assign to various societal goals. Heralding TTIP as a purely economic proposition, then, is thus a deeply reductionist move that should provoke an outcry among scientific and science policy communities. To claim that different safety regulations in the United States and the EU are simply different expressions of “comparable levels of safety”, as suggested by the European Commission in a recent public outreach document on TTIP, is an almost cynical depiction of the complexity, heterogeneity, origin, and purpose of health, safety, and environmental regulation around the globe, tantamount to begging the question of why regulations exist in the first place.
Instead of black-boxing and side-stepping complicated science and technology issues under the pretext of trade, then, politicians on both sides of the Atlantic should work toward a much-needed global science and technology policy agenda for the 21st century and use this as a stepping- stone for future free trade agreements. Just as with foreign policy, science and technology policy would undoubtedly benefit from a strong transatlantic axis. But just like foreign policy, too, a science and technology policy that only cares about trade will not do.
Advancing Evidence-Based Policymaking to Solve Social Problems
Despite spending billions and billions of dollars each year, the United States is simply not making rapid enough progress in addressing a range of social problems. Many children are poorly prepared to start or advance in school. Many prisoners end up back in jail after being released. Many new and displaced workers lack skills to succeed in the workplace. Many people suffer from chronic illnesses such as diabetes and asthma. In the face of these and other social problems, the nation has either failed to develop effective solutions, failed to prove that the solutions work, or failed to scale up the solutions that do work.
These failures have adverse consequences for the affected individuals and their communities; they also damage the nation’s economic health. At the most basic level, the nation’s prosperity depends on the productivity of its workforce and the share of residents who are employed. But when there are 7 million youth who are neither in school nor working, when half of low-income fourth-graders are not reading at even a basic level, when 1 in 15 African American men is incarcerated, and when the nation ranks no better than average in college graduation rates among developed countries, the United States is clearly not maximizing the potential of its workforce. The results are felt in a lower standard living for individuals and in reduced economic growth for the nation.
Solving such social problems, difficult under any circumstances, is complicated by the nation’s continuing fiscal woes. At every level of government, policymakers are facing the same challenge: How do we continue to innovate and make additional progress in addressing the nation’s problems when budget cuts are making it difficult, if not impossible, to hold onto the gains we have already made? The only way to keep making progress in this fiscal environment is to produce more value with each dollar that government spends. Doing so will require better use of evidence in policymaking.
The good news is that over the past decade, new evidence- based practices have emerged, at the federal, state, and local levels that simultaneously offer the potential to speed up progress in addressing social problems and to make better use of taxpayer dollars. Further, there are a number of clear steps that the federal government can take to promote the use of these practices throughout all levels of government.
If these evidence-based approaches to policymaking spread widely, we will achieve better outcomes with government expenditures by replacing less-effective government programs with programs that work better, and we will develop new, more-effective approaches. But if our goal is to make significant progress in addressing our most serious social problems, simply expanding the use of these strategies is unlikely to be enough to produce the results we require. We need to supplement the wide diffusion of these practices with a more-focused approach that aims to supply solutions for specific high-priority populations. To this end, I propose that the government launch two initiatives—that will span a decade and target entire populations of at-risk individuals in specific communities.
The various evidence-based practices that have emerged in recent years fall into five general categories, based on the challenges they are intended to address. These challenges are:
Subsidizing learning and experimentation to develop new solutions. After 40 years of applying rigorous evaluation methods to social policy, researchers and the government have learned a lot about what works and what does not. But for many of the most important social problems, there are no proven, cost-effective, scalable strategies. The challenge is how to finance needed program development and experimentation. If the government or a philanthropy funds 10 promising early childhood interventions and only one succeeds, and that one can be scaled nationwide, then the social benefits of the overall initiative will be immense. Therefore, there is a need for funding mechanisms that pay for the learning—and the failure—that are necessary to ultimately come up with successful solutions.
The simplest way to increase social innovation is to fund it directly through government or philanthropic grant competitions and innovation funds. Alternatively, governments can guarantee to “buy” the results of social innovations. In producing private consumer goods, innovators know that if they produce a terrific product, there is a market waiting for it. But “customers” do not necessarily exist who will scale up successful social innovations, and this may inhibit philanthropies and social entrepreneurs from investing in developing them. Alternatively, governments can offer large prizes for the development of solutions to important public problems, an approach that has worked in a number of more technical areas.
Increasing the amount of evidence on what works. Faster and less expensive ways are needed to find out which innovative solutions work. Today, the outcomes of most programs are never measured, much less evaluated by comparison to a rigorous counterfactual scenario. Occasionally, a program will be subjected to a large program evaluation that, by the time the results are available, may indicate whether or not the program worked in the past but not whether it is still working, given that conditions may have changed.
One approach to finding answers is prioritizing evaluation funding. Spending a few hundred million dollars more a year on evaluations could save tens of billions of dollars by identifying which programs work and generating lessons to improve programs that do not work. Federal agencies should be given the authority to set aside a portion of their program funding for evaluation, and individual grants can carry a requirement to include evaluations.
Also, granting agencies can structure grant competitions to simultaneously reward interventions that have developed rigorous evidence of effectiveness and to generate new evidence on promising practices that have not yet been evaluated. For example, the i3 program run by the Department of Education (DOE) provides competitive grants to local education agencies to expand innovative practices to improve student achievement, increase high-school graduation rates, or increase college enrollment and completion. The program uses three tiers of grants: scale-up grants to fund practices for which there is already strong evidence, validation grants to fund promising strategies for which there is currently only moderate evidence, and development grants to fund “high- potential and relatively untested” practices. Most of the scale- up grants have provided approximately $3 million each, most of the validation grants approximately $15 million each, and most of the development grants approximately $50 million each. If more agencies used this tiered approach, then groups that depend on grants to support the development of social interventions would probably work to obtain the added evidence that would bring larger grants.
In the past, a major obstacle to building up evaluation evidence has been the cost associated with data collection (an in-person survey can easily cost $1,000 or more per sample member). The information technology revolution offers the means to improve evaluations considerably. Government administrative data systems can be used to provide important outcome measures on a monthly or quarterly basis and to compare the performance of different providers. Evaluations have also been limited by the delay (often 5 to 10 years) between when an evaluation is proposed and when evidence becomes available. Although some delay is necessary to measure the long-run impacts, with information technology and the availability of large administrative data sets measuring key outcomes such as earnings histories, college enrollment, and criminal trajectories, there is the opportunity to do evaluations more rapidly to provide useful assessments of current program effectiveness. It is time to bring the private-sector practices of rapid-cycle innovation and use of data for continuous improvement to the public sector.
Making greater use of evidence in budget and management decisions. There are several challenges to making budget decisions based on evidence of program effectiveness. For many programs conclusive evidence does not exist. Even when evidence of program effects does exist, it can be analytically challenging to extrapolate from that evidence to broader policy effects or to systematically compare the relative effectiveness of different policy options. When funding is distributed to lower levels of government or is used to finance provision by numerous private-sector service providers, effectiveness can vary widely in different locations. In some cases, underfunding is what causes programs to be ineffective. Thus, the best policy response to poor performance can be to increase funding. On the management side, the main challenge is to produce evidence on a high enough frequency to allow a feedback loop between management practices and outcomes.
In addition to technical issues, there are often political obstacles. Legislatures sometimes earmark funding for particular providers, thwarting efforts to award grants through merit-based competitions. An evidence-based initiative that threatens to reduce the market share of an incumbent provider who has friends in the legislature may not endure, whereas an ineffective program that is politically connected may be immortal.
Several strategies have been developed to tackle such issues. The tiered evidence approach used by the DOE’s i3 grant competitions to direct funds to programs with the best track records has been adopted by several other federal agencies, including the Department of Labor (DOL) and the Department of Health and Human Services (HHS). Even without tiered standards, grant competitions can make evidence of success a selection criterion. Grants made through noncompetitive means, such as formula grants, can also make the adoption of best practices a requirement for some or all of their funding.
Agencies also are doing more—and could do yet more— to compare the performance of different providers. For example, the federal Head Start program has historically renewed existing providers automatically. But under new regulations designed to respond to concerns about uneven quality at Head Start sites, providers are awarded five years of funding and then evaluated, with the bottom 10% of performers required to compete with other potential providers for funding. This approach of re-competing the worst performers is a good model for types of social services where it is not easy to scale the size of operations up or down.
In a related step, the government can publicize the performance of all providers and then give the individuals who are eligible to be served a voucher to choose among them. This approach is used in the Australian employment program, Jobs Services Australia, where the government compiles results on reemployment rates and other quality metrics for each service provider and publishes a rating (one to four stars) for each.
Another approach addresses the fact that in policy areas where dozens of different interventions have been evaluated in separate research studies, often using different outcome measures and different evaluation methodologies, it can be difficult for policymakers to make sense of all of the evidence, especially when the cost of the interventions varies widely. A review of the evidence by a policy-focused team of experts can help determine the relative cost-effectiveness of different approaches. The Washington State legislature created the Washington State Institute for Public Policy to produce studies of this sort. The institute uses a benefit/cost model to review the impact of various criminal justice policies, and state policymakers nationwide are using the findings to determine which policies are the most cost-effective for reducing recidivism.
Targeting efforts around spreading proven practices has also proved useful. New York City’s Center for Economic Opportunity provides an example. The center, established in 2006 and supported by a $100 million annual fund, focuses on developing and evaluating innovative approaches to reducing poverty. Initiatives that are successful then become eligible for permanent funding through the city budget. The center has produced more than 50 initiatives, many of which have been evaluated with randomized controlled trials. The federal Charter Schools Program, which funds successful, high-quality charter schools to expand enrollment or set up additional schools, is another example. Since 2010, the DOE has awarded competitive grants to support the expansion of 34 existing high-performing charter schools and the creation of 251 new high-quality charter schools. In both situations, the same teams that set up the original models are involved in the replications. Although narrow-purpose programs can sometimes be excessively rigid and stifle innovation, when they support proven innovations they can be another way to spread successful practices.
Rather than managing programs based on the quantity of services provided, government agencies need to track outcomes for specific target populations and manage their programs to achieve outcome goals.
Simply cataloging successful practices can help them to spread. The DOE’s What Works Clearinghouse, the Department of Justice’s CrimeSolutions.gov, the Substance Abuse and Mental Health Services Administration’s National Registry of Evidenced-Based Programs and Practices, and the Department of Labor’s Clearinghouse of Labor Evaluation and Research are helpful steps toward making evidence on what works more available. Private-sector efforts such as the Coalition for Evidence-Based Policy’s Social Programs that Work list are similarly useful.
One of the most direct ways to use evidence in allocating resources is to stop funding things that are found not to work. An example of this occurred early in the Obama administration when federal funding for the Even Start program, which provides literacy training to parents and children in homes where English is not the first language, was eliminated after a randomized control trial found that outcomes were no better for those served by the program than for those in the control group. This decision was controversial. Supporters of the program argued that it had improved after the period covered by the evaluation, but the cancelation remained in force.
A leadership strategy called PerformanceStat also has proven valuable. In this approach, the chief executive or a top deputy of an agency holds regular meetings with key staff to review up-to-date data on progress toward achieving performance goals. The PerformanceStat movement began at the local level with New York City’s Compstat and NYCStat, Baltimore’s CitiStat, and Maryland’s StateStat. The method has since spread to other locations, and uses of the techniques have corresponded with falling crime in New York City, the demolition of blighted properties in New Orleans, improved Medicaid claims processing in Los Angeles County, and reduced homelessness in Washington, DC. In the past two years, this approach has blossomed within the federal government as well, with nearly two dozen agencies using the strategy.
Making purposeful efforts to target improved outcomes for particular populations. Most government social service funding is dedicated to purchasing slots in programs. Programs are managed to deliver a defined set of services to a fixed number of people rather than to achieve any particular outcome. Multiple government programs often provide “stove-piped” assistance or services to a given individual, with none of them accountable for getting the individual to achieve success. Rather than managing programs based on the quantity of services provided, government agencies need to track outcomes for specific target populations and manage their programs to achieve outcome goals. Successful population-focused efforts will generally require extensive collaboration with many nongovernmental community partners, including businesses, nonprofit service providers, and philanthropies.
A number of approaches can help address these issues. The Greater Cincinnati Strive Partnership is perhaps the best example of an effort to define a target population and coordinate services in a strategic way to make sure everyone in the population receives the services they need to succeed. Strive is an initiative in Cincinnati, Ohio, and two neighboring cities in Kentucky—Covington and Newport—that aims to improve student achievement “from cradle to career.” The partnership has brought together a range of community members to focus in a data-driven way on achieving eight outcomes: kindergarten readiness; fourth-grade reading proficiency; eighth-grade math proficiency; high school graduation rates and ACT scores; and postsecondary enrollment, retention, and completion.
The partnership takes an “every child” approach and regularly tracks the number of students who are not achieving target outcomes to form strategies to deliver the services necessary to raise the number of successful outcomes. Different community organizations are taking the lead on various components of the initiative. Kindergarten readiness has risen in all three communities, and the Cincinnati Public Schools became the first urban school district in Ohio to be rated “effective.”
An important component of population-focused efforts is matching the right services to the right individuals. Some services work better for particular population subgroups than for others, and some are cost-effective only for certain population subsets. New York State, as part of its Work for Success employment initiative for the formerly incarcerated, is developing a client matching system to connect prisoners with the appropriate set of services upon release from prison.
Another approach is setting outcome-focused goals and managing them. The Department of the Interior’s initiative to reduce violent crimes in Indian communities illustrates the power of goal setting, frequent and population-focused performance measurement, replication demonstrations, and scaling. Over three years, violent crime has fallen by 55% at four reservations. The agency is now working to expand the initiative to two additional reservations.
Spurring innovation and aligning incentives through cross-sector and community-based collaboration. Outside of education, most social-service provision is done by private providers, with most of the financing coming from government. This means that government’s task is to create an environment with its grant competitions and procurements so that providers and their philanthropic partners can be successful in innovating, producing evidence on what works, and scaling up effective services.
The federal government has recently taken a number of steps toward that goal. The Social Innovation Fund, administered by the Corporation for National and Community Service, makes grants to grant-making intermediaries that match the federal awards dollar for dollar with funds raised from other sources. Each intermediary then runs a competitive process to make grants to expand community-based nonprofits with evidence of strong results, and the grantees are required to match the grants they receive. To date, the fund has awarded a total of $138 million to 20 intermediaries, which have selected 197 nonprofit subgrantees, resulting in $350 million in nonfederal cash match commitments. Each grant is expected to be rigorously evaluated, though given the relatively small size of the grants and the early stage of development of some of the organizations receiving grants, it is unclear how many impact evaluations will actually emerge from the initiative.
The federal government has also used waivers and performance partnerships to encourage community-level innovation. Disadvantaged communities and individuals are often the recipients of services from multiple federal programs spanning several federal agencies. In many cases, this funding is not well coordinated, and no one is responsible for whether or not the combination of funding produces successful outcomes. In his 2013 budget, President Obama proposed to allocate $200 million in existing funding to Performance Partnerships in which states and localities would be given the flexibility to propose better ways to combine federal resources in exchange for greater accountability for results. The initial proposals were targeted at the areas of disconnected youth and neighborhood revitalization. Several states gave examples of the projects they would like the flexibility to undertake. For example, Iowa was interested in developing a coordinated approach to providing services to high-risk youth—those involved in the child welfare, juvenile justice, mental health, and vocational rehabilitation systems.
More broadly, federal waiver authority is an important tool for developing innovative approaches. By letting state and local governments test and evaluate new strategies, they can demonstrate solutions that can then be spread through legislative changes. Nine states are currently testing new strategies for serving children and families involved in the child-welfare system. To be successful, a waiver program must not only give states the flexibility to try new solutions, but it must also incorporate rigorous evaluation so that informed decisions can be made about whether to spread the new strategies to additional jurisdictions.
An important category of initiatives in which state and local governments are being given the flexibility to combine federal funding streams in creative ways is that of place-based initiatives. These include the Department of Housing and Urban Development’s Choice Neighborhood Program, which invests in improvements in housing, schools, transportation, access to employment, and the Sustainable Communities Initiative, a joint effort of several federal agencies that supports regional planning and development efforts.
The availability of a federal grant competition can serve as an action-forcing event that enables government, philanthropic, and private partners at local levels to come together and produce an innovative plan to improve outcomes. Perhaps the most successful example of this has been the DOE’s Race to the Top Fund, which offered grants to states for educational reform efforts and required all of the necessary stakeholders to be partners in the state proposals. Notably, many of the states that did not receive federal funding nonetheless decided to implement their proposed reform plans. As with waiver authority, the key to producing learning from initiatives such as this is not simply to promote innovation but also to rigorously assess the results of the different strategies, so that these state initiatives can truly function as “laboratories of democracy.”
Federal-state partnership funds represent another approach. Many federally funded social programs are administered by state and local governments, and efforts to improve the administration of these programs require cooperative efforts across levels of government. In 2010, Congress authorized the Partnership Fund for Program Integrity Innovation, managed by the Office of Management and Budget (OMB), which received $32.5 million to be spent over a multiyear period. The OMB set up a Collaborative Forum with representatives from state and local governments, nonprofits, federal agencies, and participation by the public to come up with ideas for pilot projects that could demonstrate best practices and inform policy decisions. The OMB approves pilot concepts and then transfers funds for the pilot to a lead federal agency, which implements the pilots in collaboration with state and local partners. As one example, the Department of Justice is working with three state and local juvenile justice agencies to develop a cost-effectiveness scorecard. By showing the cost-effectiveness of different evidence-based juvenile justice interventions, the score- card will help program leaders make better service contracting decisions and also help frontline service providers make better decisions about particular interventions for youth.
Pay for Success initiatives using social impact bonds (SIBs) represent a particularly novel approach to financing social programs. Under the most common model, the government contracts with a private-sector intermediary to obtain social services and then pays the intermediary entirely or almost entirely based on the achievement of performance targets. If the intermediary fails to achieve the minimum target, the government does not pay. Payments typically rise for performance that exceeds the minimum target, up to an agreed-upon maximum. The intermediary obtains operating funds by raising capital from commercial or philanthropic investors who provide upfront capital in exchange for a share of the government payments. The intermediary uses these operating funds to contract with one or more service providers to deliver the interventions necessary to meet the performance targets.
New York City launched the nation’s first SIB initiative. The city is using this approach to finance services for 16- to 18-year-olds who are jailed at Rikers Island, with the aim of reducing recidivism and related budgetary and social costs. Services are being delivered to approximately 3,000 adolescent males per year, from September 2013 to August 2015. MDRC, a nonprofit, nonpartisan education and social policy research organization, is serving as the intermediary, overseeing day-to-day implementation of the project and managing the two nonprofit service providers that are delivering the intervention. Goldman Sachs is funding the project’s operations through a $9.6 million loan to MDRC. The city will make payments that range from $4.8 million if recidivism is reduced by 8.5% to $11.7 million if recidivism is reduced by 20%. Bloomberg Philanthropies is guaranteeing the first $7.2 million of loan repayment.
Although SIBs are still a highly experimental approach to financing social programs, they are also highly promising because they directly address all five of the challenges involved in disseminating evidence-based practices. Because SIBs shift the risk of failure from taxpayers to the private sector, they enable governments to try innovative solutions. Because rigorous real-time impact assessment is an essential component, SIBs generate additional evidence on program impacts. Because an intervention that results in a successful SIB will likely be scaled up whereas an unsuccessful one will not receive further funding, the evidence from a project is highly likely to be influential in budget decisions. Because SIBs assign specific populations to service providers and hold them accountable for outcomes, they avoid the traditional fragmented and slot-based approach to service provision. Because SIBs are multiparty contracts that combine government, service providers, and private investors in a multiyear effort to achieve performance goals, they promote cross-sector collaboration.
Spreading the new practices
Despite the encouraging progress, it remains the case that most government spending is not allocated based on evidence or with a focus on innovation or performance. Even in federal agencies that have been the most creative in developing new ways to allocate grant funds, such as the DOE and HHS, the bulk of spending is distributed through conventional grants and other traditional mechanisms. Therefore, it is an important priority to spread these new strategies widely: to additional programs within the federal agencies that are already using them, to additional federal agencies, and to more state and local jurisdictions.
Dissemination will occur faster and be more likely to survive changes in administrations if Congress and the president take action to support the adoption of effective approaches. There are a variety of legislative and administrative actions that would help spread these practices. These include:
Providing funding authority for evaluations. All agencies that administer social programs should receive authority, similar to that currently provided to the DOL, to reserve a portion of program spending to fund program evaluations. The DOL’s authority is better crafted than similar authority that has been provided to other agencies because it gives the agency the flexibility to use the evaluation funds to evaluate the highest-priority initiatives rather than tying the funds to evaluation of specific programs. The agency authority should be provided only to agencies that establish a chief evaluation officer position or have a similar office that is dedicated to producing independent and rigorous evaluation evidence about the agency’s programs.
In addition, a small evaluation fund should be provided to OMB for cross-agency evaluation initiatives. The administrative structure could be similar to that of the Partnership Fund described above and would enable coordinated, cross-agency evaluation planning for related programs. OMB would be encouraged to consult with Appropriations Committee leadership in deciding which programs to evaluate and to demonstrate the potential benefits of planned studies.
Expanding the use of tiered evidence standards in grant competitions. In high-priority policy areas where sufficient evaluation evidence is available, agencies should be encouraged to use tiered evidence standards in grant competitions. Structuring a grant competition in this way ensures that the largest share of federal funding goes to practices that have been shown to be effective, while also investing smaller amounts of funds in developing evidence about promising but not yet proven approaches. Grant competitions that use tiered evidence standards are expensive to administer because they generally require agencies to recruit outside evaluation consultants to review the evidence base of each proposal received. Thus, they are worth using only for large, high-priority grant competitions.
Reserving a portion of formula funding for proven practices. The majority of federal social spending is administered through formula funding to state and local governments, rather than through grant competitions. As there currently is a limited evidence base for most activities funded via formula funding, it would not make sense to restrict the use of these funds only to evidence-based practices. Instead, a portion of these funds should be used to build the evidence base. Then, over time, as the evidence base becomes strong enough, formula funding provided to state and local governments should begin to require that a portion of such funds be spent on programs that have been proven effective. Depending on the policy area and the amount of evidence that exists, this requirement could start by stipulating that 1% of such funds be allocated to proven practices, then have the requirement rise over time to 5%.
Directing the OMB to submit an annual report on evidence-based techniques and practices. The 2010 Government Performance and Results Modernization Act was important because it codified the new agency performance reporting framework in a way that makes the framework more likely to endure. Similarly, Congress could take steps to show that it supports the recent executive branch evidenced-based initiatives. At a minimum, a congressional committee could have an annual hearing at which it invites the OMB director and some agency representatives to describe their progress in using evidence-based techniques. Congress could also require the OMB to produce an annual report listing evidence-based practices by agency and reporting the percentage of each agency’s grants that were made using evidence-based techniques. Many such reporting requirements quickly devolve into time-wasting compliance exercises. Therefore, if such a report is requested, the requirement for producing it should be sunsetted after five years and apply only if Congress also rescinds several existing OMB reporting requirements.
Directing a specific government agency to take charge of producing cost-effectiveness reports. The congressional budget and appropriation committees should jointly identify five priority policy areas each year and ask either the Congressional Budget Office or the Government Accountability Office to produce a report in each area identifying what evidence currently exists about the outcomes being produced by federal spending in that area; what is known about the relative cost-effectiveness of different strategies in the area; what promising strategies exist that have not been rigorously evaluated; and where promising strategies are lacking and what funding strategies and incentives could be used to spur the development of new solutions. Potential areas for such reports include job training, early childhood education, and school dropout prevention, among many others. This added requirement would probably require an increase in the agency budget of at least $3 million per year, but this modest investment would enable Congress to target resources more effectively. Once the agency has gone through the effort of producing an initial report in each area, it should be updated every two or three years.
Compiling federal program evaluations into a comprehensive Web site. In 2010, the OMB issued guidance requiring agencies to make information readily available online about all federal program-impact evaluations that are planned or already under way. This effort was intended to be analogous to the HHS clinical trial and results data bank (ClinicalTrials.gov) that aims to prevent drug companies from hiding negative trial results. Although some agencies complied by posting their evaluations on their agency Web sites, the OMB never moved forward to compile all of the agency information into a comprehensive federal evaluation Web site. In addition to preventing the suppression of results, a comprehensive federal evaluation Web site would help Congress and the public understand which programs have been evaluated, which ones haven’t, and what the results showed. A challenge with government transparency efforts is that they often provide a large quantity of information without the interpretive context necessary for consumers of the information to use it. Thus, any federal effort of this sort will likely need to be accompanied by a parallel effort by organizations like the Coalition for Evidence-Based Policy to interpret the information.
Making administrative data more accessible for measuring outcomes. Evaluation studies that wish to use government administrative data to measure program outcomes now typically need to go through extensive one-off negotiations to arrange access. Establishing a standardized way for evaluators to access common federal data sources would increase the number of evaluations that can occur.
The 10-year challenge
If the various evidence-based approaches to policymaking spread widely, the government will achieve better outcomes, will stop spending money on programs that do not work, and, most important, will spur the development of new, more-effective intervention strategies. But if the goal is to make significant progress in addressing the nation’s most serious social problems, simply expanding the use of these approaches is unlikely to be enough. It will be necessary to supplement the wide diffusion of these practices with a more-focused approach that aims to find solutions for specific populations.
Consider the challenges of reducing recidivism among ex-offenders, raising fourth-grade reading and math skills among children living in high-poverty neighborhoods, preventing youth from dropping out of high school, helping chronically unemployed individuals obtain and keep jobs, raising community college completion rates, eliminating chronic homelessness and homelessness among families, and helping developmentally disabled youth make successful transitions into the adult workforce, among many others. Although dozens of programs spend billions of dollars serving these populations, services are delivered in a highly fragmented manner. One program provides mental health services, another provides housing services, and still another provides job-readiness training. But in most cases, no one is responsible for ensuring that a specific cohort of individuals in a particular community achieves successful outcomes. Moreover, it is not just federal government programs that determine whether success is achieved. Results depend on the joint actions of multiple levels of government, diverse not-for-profit and for-profit service providers, private businesses, and philanthropic and other community partners.
With a goal of overcoming this fragmentation and producing the community-level collaboration and innovation necessary to make real progress on the nation’s most persistent social problems, I propose the 10-Year Challenge. Congress and the president should work together to identify 10 social problems where it is a national priority to find solutions. All of the problems would be ones where the specific individuals in the population to be served can be identified and baseline outcomes can be established; these two factors will provide an observable baseline against which improvement can be measured.
Through a grant competition, 10 communities would be selected for each problem—100 communities overall—in an effort to transform outcomes for the specific population within 5 to 10 years. A single agency would be the granting agency for each initiative, though many of them will require cross-agency collaboration. The granting agency would first issue planning grants of $250,000 each to several dozen communities that demonstrate a commitment to cross-sector partnerships and organizational capacity to develop competitive proposals. Final awards would be made to those communities that successfully propose a data-driven, collaborative approach to transform delivery of services to achieve measurable improvements in outcomes for specific cohorts of individuals.
In selecting winning proposals, the agency should look at such criteria as the project’s design, the level of commitment of community partners, and the likelihood based on existing evidence, that the project will make significant progress in addressing the target social problem;; the potential for the project to produce rigorous evidence that would add to what is currently known about the effectiveness of particular strategies; the extent to which the proposed strategies represent significant advances over current practices; and the potential for scaling the project within the given state and to other states or other similar populations.
In the projects, a target population could be statewide (for example, all youth in a state who are aging out of the juvenile justice or foster-care system in a given year) or much more geographically targeted (for example, all preschool-age youth in a particular neighborhood). In most cases, interventions will involve 1,000 to 2,000 individuals per year. With fewer individuals, it will be hard to have enough statistical precision to know what the results are; whereas budgetary resources are unlikely to permit significantly larger groups to be served, except in cases in which the cost per person served of the intervention is very low.
The projects would spend, on average, $10 million a year on services (with flexibility depending on the nature of the intervention and the size of the community and the target population). The grants would cover one-third of the cost of service provision, with state and local governments providing one-third and private community partners covering one- third. The federal government would also provide up to $1 million per year per project for evaluation expenses. In total, the federal share of the initiative would cost approximately $400 million per year. Funding for the initiative could come from repurposing existing grant and formula funding, or from a congressional appropriation. In addition, the federal government would waive program rules as necessary so that communities could take existing funding streams and use them in more flexible ways to fundamentally redesign systems.
Pay for Success
In the second initiative that I propose, the government would become a strategic partner with state and local governments in expanding current Pay for Success/SIB projects into areas where state and local activity has the potential to achieve important federal policy objectives or produce significant federal budget savings. The highest priority would be to create an initiative around early childhood interventions including home visiting, early learning, and preschool, or initiatives spanning birth to second grade. Evidence of success in early childhood programs is strong, but state and local governments are having trouble establishing Pay for Success projects in this area because much of the financial benefit of these interventions accrues to the federal government in the form of lower Medicaid and transfer program spending and higher federal tax revenue. Federal involvement could enable the economics of these projects to work.
As another example, if a state government can set up a Pay for Success project that helps disabled individuals return to work rather than apply for federal disability insurance benefits, the federal government should offer to reimburse the state government for any success payments it makes in the project.
The federal government should also consider a broader role as a strategic partner with state and local governments in establishing SIB projects. The rationale for a broader federal role is that if one state or local government discovers a solution to a social problem, it will have tremendous value to the nation as it gets scaled nationwide. As mentioned above, a process through which the federal government subsidizes learning at the state level can help overcome the underinvestment in learning that is likely to occur when individual jurisdictions cannot capture the full value of their discoveries. The federal subsidy could come in the form of an extra prize-like payment to investors in successful SIB projects. Alternatively, the federal government could “backstop” a portion of the losses in unsuccessful projects.
To support this effort, Congress should give the DOE and HHS the authority to repurpose a total of up to $125 million of existing funds to support five state or local Pay for Success initiatives. The funds would be used to match, on a dollar-for-dollar basis, state or local success-based payments. A typical-sized project would provide $10 million of services per year for four years and serve approximately 1,000 families per year. With a state/local commitment of $25 million and a federal commitment of $25 million, success-based payments of up to $50 million would be possible. Funds repurposed in this way would remain available until expended, rather than expiring at the end of the fiscal year.
During the past decade, governments have shown tremendous creativity in coming up with new approaches to foster experimentation and learning and to allocate spending to social programs with the best evidence bases. The results of the programs funded through the new mechanisms will greatly add to the knowledge base regarding which policies and programs work in addressing serious social problems and which do not. If the new evidence-based practices continue to spread, the amount of learning will accelerate and the country will reap fiscal and economic benefits.
But without a strategic effort to develop approaches that target entire populations of at-risk individuals in specific communities, it is unlikely that the nation will move the dial on its most pressing social problems. What is needed is a decade in which we make enough serious attempts at developing scalable solutions that, even if the majority of them fail, we still emerge with a set of proven solutions that work.
Defining Energy Access for the World’s Poor
The poorest three-quarters of the global population still use only about 10% of global energy—a clear indicator of deep and persistent global inequity. Modern energy supply is foundational for economic development, yet discussions about energy and poverty commonly assume that the roughly 2 to 3 billion people who presently lack modern energy services will demand or consume them only in small amounts over the next several decades. This assumption leads to projections of future energy consumption that are not only potentially far too low, but that also imply, even if unintentionally, that those billions will remain deeply impoverished. As we argued in our article in the Summer 2013 Issues, such limited ambition risks becoming self-fulfilling. Here we provide some supporting data.
Not all “energy access” is the same
What counts as energy access? Answering the question is not simple. World Bank data show the wide range of what can be meant by “energy access” and how per capita consumption differs among countries at “full electrification” and among those with much lower access rates. Countries that are classified by the Bank as having 100% household access to electricity services vary in their electricity consumption by more than seven-fold. Yet for a household of five, annual electricity consumption of less than 2,000 kilowatt hours (kWh) per year would be far less than the typical household energy services would imply in even the least energy-consumptive wealthy countries, such as Bulgaria or Greece. Thus, “full” energy access does not necessarily mean access to a full array of modern energy services.
Average annual household energy consumption across several countries with various degrees of “energy access”
Source: Global Tracking Framework. World Bank Sustainability for All Program, Washington, DC, 2013.
Better to be Bulgarian
This figure provides some insight into how modern levels of energy access compare to proposed development benchmarks The numbers for the United States, Germany, and Bulgaria provide a sense of the range of electricity consumption levels enjoyed by nations with “modern” economies. In contrast, the International Energy Agency’s (IEA) World Energy Outlook defines an “initial threshold” for energy access to be 250 kWh per year for rural households and 500 kWh per year for urban households, assuming 5 people per household. This equates to 50-100 kWh/year per person, or about 0.5% of the electricity consumed by the average American or Swede, and 1.7% of the average Bulgarian.
For a sense of scale, the use of a single 60 Watt light bulb for four hours per day requires about 90 kWh per year. The graph shows the stark contrast between how energy access is defined and what it really means. The grey bar shows average global per capita electricity consumption for 2010 and the one above that shows projected per capita consumption for 2035. The small difference between the 2010 and 2035 numbers shows that the billions of people currently in energy poverty are not expected to exhibit modern levels of electricity consumption over the next quarter-century, meaning that the IEA assumes that billions will remain in poverty.
Levels of global per capita electricity consumption compared to the IEA definition of “energy access”
Source: International Energy Agency and World Bank.
Assuming away emissions
The consequences of assuming continued energy poverty for the next 25 years are further reflected in IEA’s projections of future carbon dioxide emissions. The minimal consequences to emissions and consumption resulting from this scenario essentially reflect a “poverty maintenance” level of energy service provision. Emissions increase by such a small amount because new energy consumption increases by a very small amount. But poor countries are unlikely to settle for such a future. Conflicts between energy and climate priorities deserve a deeper and more open airing in order to help better frame policy options, including the difficult question of tradeoffs among competing valued outcomes.
Change in energy demand and CO2 emissions under the IEA’s universal energy access scenario
Source: International Energy Agency, World Energy Outlook, 2011.
Prescription for Productivity
Everyone thinks the United States needs more innovation—to shore up economic growth, to generate more jobs, to improve schools, to improve health care—and so we have a profusion of academics, think-tank experts, and federal officials proposing innovation agendas. But this book is more than a 10-point list of actions. The authors frame the argument for why the United States should adopt an explicit innovation policy and then suggest how such a policy should be crafted in light of both U.S. political and economic history and the policy stance of other countries.
Along the way, the authors take a hard swipe at economists in prominent policy positions who in their opinion have failed to provide leadership on innovation policy and a foreign policy establishment that focuses on political objectives without considering consequences for U.S. economic competitiveness.
The book begins by making the scariest possible case that the United States is in decline. “Look at Britain” is their main argument. Britain ignored growing trade deficits and declining manufacturing capacity, and the United States is on the same trajectory. The story is not that simple.
First, the U.S. trade deficit is largely a product of a low national savings rate. It is said: “America spends, Europe balances, and Asia saves,” and that seems all too true. The standard macroeconomic solution to that problem might include some aspects of what the authors call innovation policy, such as tax credits for productivity-enhancing investments, but it would most likely not include actions that aimed to shore up the domestic base of an industry or sector (as these authors would do for the U.S. tech sector).
Second, the persistence of trade deficits does of course play out in the demise of certain domestic industries, but that is not all that happens in an economy running trade deficits. In a country such as the United States with strong laws and institutions, capital willingly flows into the country as foreign direct investment, purchases of U.S.-issued securities, real estate investment, etc. And although the financial crisis and Great Recession make the reading of recent trends difficult, foreign direct investment in the United States remained relatively strong through 2007, which seems prima facie evidence that Atkinson and Ezell are off base in their contention that the negative U.S. trade balance discouraged business fixed investment in the United States.
Now, it is also too true that economists often fail to acknowledge the importance to the public interest of maintaining a domestic base in certain industries, such as aeronautics and electronics for national defense. But this political reality does not negate the fact that the root cause of persistent trade deficits is low national savings. Rather, it suggests that policymakers in countries running trade deficits need to closely monitor the composition of national investment, and perhaps even tinker with it. It is much easier to shift the composition of investment than it is to engineer a turnaround in private (much less public) spending/saving propensities.
Third, advanced countries, not just the United States, lost their edge in terms of productivity growth more than 15 years ago. Nevertheless, the United States is still the world productivity leader. Estimates of 2010 average labor productivity corrected for price differences across countries indicate that the level of U.S. average labor productivity exceeds Europe’s by 25%, Japan’s by 30%, China’s by 85%, and India’s by 90%. These differences, especially the latter two, are likely to shrink in coming decades, but a convergence in average productivity levels is not a decline in U.S. productivity except in a relative sense.
Science’s role
Because innovation involves the introduction and spread of new and improved products and processes broadly in the economy, innovation is said to encompass, but to be more than, scientific invention. An economy may be more productive because marketing research led to the creation of new services or better product design, new human resource practices led to more effective workers, etc. Such innovations, and their diffusion, may have little or nothing to do with knowledge gained through scientific R&D, although they may be, in some cases, complements to investments in R&D and information technology.
A broad view of innovation does not, however, contradict or undermine the importance of science policy, whose core mission is public support of basic research. The economists Richard Nelson and Kenneth Arrow made the case for public research funding using a market failure argument more than 50 years ago. They argued that private-sector investment in basic research is less than optimal, because a full return on investment is not realized by the knowledge creator. Because private agents, acting alone, will fail to undertake a socially desirable amount of scientific experiments to generate new knowledge, public funding of basic research is desirable to generate social and economic benefits.
A link between public R&D spending and productivity growth is not necessary to justify the government investment. This is not to say that such a link is not there. It surely is, but the benefits are far from immediate. Thus, although the consequences of public research support are potentially far-reaching in terms of long-term economic growth, increasing public spending on basic research is not a means for shoring up economic growth and fostering innovation in the near or medium term.
Getting it right
Atkinson and Ezell’s innovation policy is consistent with the reality that technological advances and scientific discoveries must somehow be sold or commercialized in private markets to be economically beneficial to society. They argue that if national policies governing business regulation and taxation are not just right (i.e., neither too laissez-faire nor too mercantilist), a nation will lose in the global economic race. On the one hand, for example, they suggest that national and local policies are needed to support small specialist businesses (such as small parts suppliers), whose participation in large global value chains creates risks for them beyond their control. On the other hand, they acknowledge that a nation must accept that innovation entails business closures and job losses and that new technologies bring with them uncertain social and environmental impacts.
Atkinson and Ezell sound, at times, schizophrenic about just what is needed to promote rapid productivity growth, but there is a reason for this. Everything we know about U.S. productivity and job growth, including the determinants of business location, suggests that regulations and institutions that promote effective competition in labor, capital, and product markets are associated with innovation and economic growth via Schumpeterian “creative destruction.” What must be tolerated at the individual business level cannot be tolerated at the aggregate national level, according to Atkinson and Ezell. Hence the inherent schizophrenia (i.e., the United States cannot fail even though some of its businesses must!)
Atkinson and Ezell provide numerous examples from across the globe of what they consider good and bad innovation policies. They suggest, for example, that Europe’s strategy is inhibited by an internal contradiction. Although Europe has developed ambitious policies to promote innovation, many European countries are unwilling to accept the constant economic transformation that goes along with the lightly regulated labor and product markets the continent needs to achieve more innovation. Likewise, Japan’s stated commitment to innovation is undermined by its unwillingness to restructure its inefficient service industries.
In the final analysis, Atkinson and Ezell offer as innovation policies what are essentially aggressive versions of existing science and fiscal policies: first, an innovation investment tax credit (covering R&D, worker training, and traditional capital investments); second, about $30 billion more per year of public R&D spending; and third, the establishment of a National Innovation Foundation that helps businesses to become more innovative and competitive through technological and organizational change. Germany has successfully implemented this formula, and the United States has previously implemented some of these strategies (although not on a national scale).
They also want technology road-maps and a coordinated attempt across disparate departments of government to promote strategic sectors of the U.S. economy. In the national defense and energy areas, such initiatives are already in place. And we have the America Competes Act (2007 and 2010), the Jumpstart Our Business Startups Act (2012), and a host of recent initiatives such as a National Export Initiative, a National Network for Manufacturing Innovation, and the recently announced (but underfunded) BRAIN Initiative. But it doesn’t hurt to advocate beefing up and better coordinating these programs.
Finally, Atkinson and Ezell conclude their book with a novel call for a global innovation system, a new Bretton Woods, they say. They propose a framework that recognizes that the post- World War II commodity-based manufacturing economies are now specialized innovation economies and that the free flow of finance and trade is no longer sufficient as a tool for the promotion of global economic growth. They argue, for example, that today’s World Bank policies that encourage export-led growth are actually a beggarthy-neighbor form of innovation mercantilism and need to give way to the win-win strategies built on global collaboration. This discussion is insightful, especially when thinking about manufacturing and science-based innovation.
Gaps
Although this book offers a very thorough discussion of most aspects of innovation, some gaps exist. For example, the notion that innovation involves feedback from customers is completely missing. Investments in market research and customer relations are as important as investments in the techheavy R&D, training, and traditional capital investment favored by Atkinson and Ezell. A second missing factor is that tradable business, professional, and financial services could also be a source of U.S. global competitive advantage. Service industries are largely dismissed in this book, even though many U.S. business service firms are world leaders.
Finally, the authors do not consider the communications and public understanding dimension of innovation policy. The macroeconomist in me suspects that much as monetary policy works through communications and “anchoring” of inflation expectations, an effective innovation policy needs to operate through anchored expectations of robust long-run economic growth, if you will. We are unsure just how much business and consumer optimism can be boosted via a concerted policy to communicate how national innovation policies can accelerate the economy’s rate of growth, but we do believe that economic optimism leads to new hires and new investments in innovative capacity in the short and medium run.
Innovation policy is an imperative according to these authors. The imperative is based, in my opinion, on an exaggerated case for “America in decline,” but this is not to deny the serious fiscal challenges that face this and other advanced countries, challenges that robust business productivity growth can help solve. The authors’ argument for including a global dimension in national economic policies is an important contribution.
Their analysis of the political economy of global innovation reveals that fostering robust productivity growth is not simple. It requires many conditions and path dependencies to be in place. And because there are many ways of building and sustaining innovative capacity, a strategic approach to national policymaking, one in which current capabilities are routinely assessed and evaluated as suggested by these authors (and attempted in Europe and elsewhere), would seem to be warranted.
In the final analysis, however, the conduct of innovation policy is complex because the determinants of entrepreneurship, innovation, and productivity growth are themselves complex and not all that well understood. I am reminded of an insightful analysis of productivity growth conducted by Zvi Griliches many years ago, in which he inquired whether a decline in public R&D that began in the mid-1960s contributed to the decline in business-sector productivity growth in the early 1970s. Griliches found no connection, but he likewise found no compelling evidence to support any other explanation, despite the many culprits examined in his inquiry. Rather like Murder on the Orient Express, Griliches concluded, they all did it!
The many-faceted nature of actions needed to stimulate the growth potential of a country such as the United States is most assuredly not a reason for ambivalence toward innovation policy. But it is a reason to have a national policy that can be clearly communicated to business and consumers. These authors have made a start at doing that, and although many economists will not agree with the reasoning behind their arguments, what is clear from this study of the political economy of global innovation is that there are many pathways to building and sustaining greater innovative capacity. We just need to be sure to get on one.
Carol Corrado ([email protected]) is a senior advisor and research director in economics at The Conference Board and senior policy scholar at Georgetown University’s Center for Business and Public Policy.
Our better selves?
Medical science gives us many ways to improve ourselves and our offspring, and in How to Build a Better Human: An Ethical Blueprint, Gregory Pence highlights a number of them, including folic acid to prevent birth defects, in vitro fertilization, modafinil and other stimulant drugs, cosmetic surgery, performance-enhancing drugs in sports, antidepressants, personalized genomic medicine, preimplantation genetic diagnosis, “eugenic” abortion, vaccinations, and cloning. In clear language accessible to nonexperts, Pence details the development of these technologies and the ways in which they work. He supplements his technical discussions with ethical analyses in which he probes the value of these interventions and how society should react to them. Should women obtain cosmetic surgery, he asks, in order to feel better about themselves? Should students use drugs to do better on exams? Is it wrong to live longer? To use stem cells? A philosopher intent on stepping outside of the ivory tower, Pence ends by presenting six practical proposals to move us forward.
When we explore these ethically treacherous waters, Pence prudently counsels us to reject the rigid worldviews of both “alarmists” and “enthusiasts.” The former, comprising bioconservatives such as Leon Kass, Jeremy Rifkin, and Bill McKibben, hold simplistic beliefs about the virtue of what is “natural” that rest on what Pence calls “pessimistic religion,” which, he claims, “always opposes medical innovation,” as demonstrated by religious resistance to the use of anesthesia in childbirth. The enthusiasts, on the other hand, are exemplified by the transhumanists, whom Pence criticizes as ethical libertarians with overly optimistic views about everything from robotic surgery to genetic engineering. Pence does not sit squarely astride the fence, however; since the alarmists for decades have received more publicity and skewed public policy in their favor, Pence argues that it is “time for a little enthusiasm,” so long as it is combined with a healthy dose of ethics. Pence also cautions us against perpetuating “a depressing mistake that has infected bioethics for a half-century: lumping too many different kinds of cases together.” One apt example that he gives is conflating genetic modifications that affect only somatic tissues with alterations to the germ line that can be passed on directly to one’s children. These pose different risks, observes Pence, and therefore “should carry different orders of concern.”
Unfortunately, Pence makes the very mistake that he warns us against by constantly shifting from enhancements to therapeutic interventions within the same ethical analysis. How can we object to cosmetic surgeries such as breast implants and liposuction, he asks, when surgeons also replace hips? What’s wrong with using alertness drugs to improve performance on bar exams when the same drugs combat the mental infirmities of aging? Why oppose genetic engineering to enhance children when there might be a gene-based vaccine to protect them against cancer? Certainly it is not always easy to distinguish enhancements from therapeutic interventions. The difference often turns on notions of what is “normal” versus “beyond normal,” and normality is a muddy, shifting, and often arbitrary concept. Grey areas abound. For example, is a drug that prevents athletes from sustaining muscle tears during training an acceptable way of preventing injuries or an objectionable means to enhance performance? (This happens to be the effect of taking anabolic steroids.) Yet keeping enhancements and therapies separate to the extent possible is essential for ethical discourse; otherwise we would find it just as compelling to spend tax dollars on improving cognition in people with an IQ of 170 as on improving the executive function of people with mental disabilities.
Pence also sometimes ducks difficult issues by imagining them away. For example, he asserts that we need not be concerned that parents will use prenatal genetic testing to select embryos for implantation because so few parents are doing so, thereby ignoring the likelihood that the practice will expand as tests for more conditions and traits are developed and as prices come down over time. People will not mate to maximize enhancement, he declares, but for “sex, love, marriage, and status,” notwithstanding a burgeoning industry in which people buy eggs and sperm for reproduction based on factors such as the donors’ IQ and whether they graduated from an Ivy League college. Pence also doesn’t think that we need to worry that genetic engineering will change human nature, stating that “genetic experiments on babies will not be allowed because they’re dangerous, will be extraordinarily complex to evaluate, and never gain ethical traction.” But it is impossible to know what will happen in the future—for instance, whether a country with a different ethical tradition than ours will seek to improve the genetic stock of its population and trigger an international gene race. Moreover, genetic experiments on babies are already being carried out, for example, in France in an effort to repair nonfunctioning immune systems. Sure, these experiments are aimed at curing disease rather altering non-disease characteristics, but Pence hardly can rely on this distinction here when he doesn’t do so elsewhere in his book.
The highpoint of Pence’s book is the chapter on living longer. He begins by taking philosopher Bernard Williams to task for objecting to immortality because it would make people’s lives not worth living; if this were so, replies Pence, then people simply would end them. He then engages more substantive arguments: that extending life would waste resources (then why, he asks, have we spent so much on improving sanitation and other living conditions); that longevity is not natural (why is the lifespan of say, fortyseven years in the United States in 1900 more or less natural than living into one’s eighties?); that living longer would be foolish and boring (not if it was a life worth living); that the pursuit of longevity would lead us to spend too much during the last few months of life (which only seems apparent if we ignore the people who survive substantially longer as a result of what is spent on them); that people who want to live longer are selfish (not if they use the extra time to create wealth and welfare for others); and that family relationships would suffer (not if new arrangements could be negotiated). The final objection that he considers is that we can’t afford longer living because it would bankrupt entitlement programs such as Social Security and Medicare. Pence offers two responses. The first is the obvious one that people must pay more up front and/or receive reduced benefits. Pence’s second suggestion is to make illegal immigrants pay double in order to become legalized. This would not be unfair, he maintains, since they would be better off being legal or being here than remaining (or returning to) where they originated. Putting aside the fact that illegal immigrants on average earn far less than native-born workers, so that requiring them pay twice the amount of FICA and Medicare taxes would be especially onerous, it seems off for an ethicist to suggest that we can treat immigrants however we wish so long as it is better than they would be treated where they came from.
If the chapter on living longer, notwithstanding the immigration peccadillo, is the best, the most disappointing discussion in Pence’s book concerns doping in sports. He accepts uncritically the National Institute on Drug Abuse’s claims about the health risks of anabolic steroids, for example, despite the lack of scientific support. He cites the suicide of wrestler Chris Benoit as evidence of the risk of steroids without mentioning the autopsy that showed that he had chronic traumatic enceph-alopathy, a degenerative condition produced by repeated concussions that is usually seen in boxers and that causes depression and erratic behavior. He asserts that “anything not legally open to all competitors should be banned. So the controversy among users and nonusers about the long-term safety of using steroids is moot. Steroids are used to gain an unfair advantage.” In other words, steroids are against the rules, so they should be against the rules, and therefore there is no need to consider how safe or unsafe they are. Pence also calls the fact that a doctor provided steroids to a large number of police officers and firefighters “bizarre”; perhaps it is bizarre that the same doctor provided the drug to so many individuals, but insofar as steroids increase strength, why is it so bizarre that police and firefighters want to use them? Finally, Pence joins other misguided anti-doping opponents in objecting to the use of performance enhancement in sports because they are not “natural.” The blood that is withdrawn from athletes and then re-infused right before a competition in the most classic form of sports enhancement is as natural a substance as it gets, and for that matter, when did Pence last see a Gatorade tree?
Several of the proposals at the end of Pence’s book are calls to study the safety, efficacy, and comparative effectiveness of enhancements, including paying for the studies with public funds. Safety studies certainly make sense, since without them there will be a lack of good data on just how dangerous certain popular enhancements might be, but Pence’s call for effectiveness studies, such as a comparison of caffeine, modafinil, and amphetamines in “mental competition,” is interesting in view of his opposition earlier in the book to the use of public funds to “subsidize” enhancements. He also recommends creating a database to collect anonymous reports of adverse experiences submitted by people who attempted to enhance themselves; if enough people filed reports despite the social stigma associated with enhancement use, the database could join the National Survey on Drug Use and Health and the emergency room Drug Abuse Warning Network operated by the Substance Abuse and Mental Health Services Administration within the Department of Health and Human Services as part of an early-warning system to identify enhancements that merited the formal evaluations that he advocates. Another of Pence’s proposals is for the Food and Drug Administration and insurance companies to “reject the old distinction between therapy and enhancement, and let people get reimbursed for developing enhancing drugs.” Since neither the FDA nor insurers sponsor drug development, Pence presumably means that the FDA approval process should be more hospitable to enhancements and that health insurers should reverse their policy of refusing to cover them. But he does not explain how insurers are to set premiums in light of the moral hazard associated with elective interventions such as enhancements. Pence’s final proposal is to reaffirm the need for different cases to be analyzed separately rather than lumped together. Once again, however, he fails to follow his own advice, regarding surgery that “normalizes” the facial appearance of a child with Down’s syndrome as “cosmetic and enhancing,” when many instead consider it to be reconstructive.
Maxwell J Mehlman ([email protected]) is Arthur E. Petersilge Professor of Law and director of the Law-Medicine Center at Case Western Reserve University School of Law and professor of biomedical ethics at Case Western Reserve University School of Medicine.
What’s Art Got to Do with It?
For the past eight years Issues has been including art in addition to its written articles. There’s nothing unusual about including illustrations and other types of visual material to accompany articles in magazines. It’s an effective way of presenting data, attracting attention, or emphasizing a point. The graphic materials are developed after an article is written with the purpose of enhancing the impact and appeal of the text. That’s not what we do in Issues.
The visual material that appears is reproduction of art, which is very different from graphic illustration. All the art we feature was created for its own purpose, not to serve the interests of a specific article. In fact, in almost all cases the artist does not know anything about the articles that will be adjacent to the art. In some cases, the art is placed with an article or group of articles to which it has a thematic connection, but in no case is the art intended to be simply a reflection or extension of the text. This is the same approach we take with the articles. They are grouped together because they have a thematic connection, but they often offer very different perspectives and propose very different policy agendas.
Sometimes, as in this edition, there is not even a thematic connection. The art in the Forum section has always been independent of the text for the obvious reason that the letters always address a wide diversity of topics. There is no theme. And although we often choose art on themes included in the articles, just as we sometimes choose to publish several articles on one theme, we also include art that has no obvious connection to anything else in the magazine. To be honest, it’s hard to imagine a visual corollary to many of the subjects addressed in Issues articles. Take a look at the table of contents. How much art makes reference to the importance of evidence-based policymaking or the regulatory framework for geoengineering research?
Some aspects of policy are simply best treated in text. But as many participants in policy understand, decisions are not made solely, or even primarily, on the basis of empirical data and scientific analysis. It is not just the obvious need to incorporate the perspectives of social science disciplines such as economics and sociology but also the power of ideology, religion, ethics, and other cultural dimensions. Although all of these aspects can be addressed in writing, some of them are not easily approached with words. As we learning from the work of neuroscientists, psychologists, behavioral economists, and others, humans—even humans with PhDs— reach decisions by various routes. Daniel Kahneman won his Nobel prize for what might be described as the science of nonscientific thinking.
Art is one of the ways humans express and try to understand the real and unreal, the beautiful and the ugly, the uplifting and the degrading, the good and the evil, the obvious and the unknowable, the human and the inhuman.. The art we choose reflects the multifaceted relationship of humans to science and technology. It celebrates, criticizes, mocks, warns, ponders, uses, and distorts, and in so doing enriches our understanding of where science and technology fit in the cultural landscape. Without that understanding, we cannot expect to find effective ways to weave S&T into the policymaking fabric
Like most of you who read this magazine, I live primarily in the world of words, evidence, and logic, so I depend on others to guide me in the search for appropriate art. I am fortunate to have JD Talasek and Alana Quinn, the staff of the Cultural Programs of the National Academy of Sciences (CPNAS), to find the art and provide the text to accompany it and to Pam Reznick to present it effectively in print. Indeed, the remarkable exhibits and programs organized by CPNAS are the inspiration for many creative collaborations and interactions between artists and scientists. (Roger Molina, director of the arts and technology program at the University of Texas at Dallas, performs a similar function at UTD and though his role as executive editor of Leonardo, a journal of art and science.)
We are particularly grateful to the numerous artists who have allowed us to reproduce their work for free and to the gallery owners, agents, and museum curators who have helped us acquire high-resolution images that we need to do justice to the work. The look of Issues is feasible only because of the generosity of the art world and the belief of many individuals that what we are trying to accomplish in Issues has real social and aesthetic value.
Finally, we are indebted to the Issues readers who have supported this expansion of the magazine’s content. There have been no angry letters and no cancelled subscriptions. Perhaps the science policy community is not dominated by an unimaginative, hyper-rational, academic mindset. Readers and authors alike have been outspoken in their appreciation for what we are trying to do. Is this a sign that wonkdom has wisdom as well as knowledge?
From the Hill – Summer 2013
Sequester in review
In spite of substantial debate and controversy over the effects of indiscriminate across-the-board cuts in the days leading up to the deadline, sequestration went into effect on March 1 as required by law. Cuts to defense and nondefense R&D will total an estimated $9.0 billion from the fiscal year (FY) 2013 federal R&D budget. These cuts will place a particularly acute burden on government agencies, as they must be implemented nearly five months into the fiscal year.
As widely expected, Congress failed to pass a balanced alternative deficit reduction plan to replace the sequester. The House of Representatives, however, did pass an appropriations bill (H.R. 933) that would fund the federal government for the remainder of the 2013 FY. The legislation, which passed 267 to 151, would fund both defense and nondefense R&D at FY 2012 levels, although all R&D would remain subject to sequestration—a roughly 7.8% decrease for defense R&D and a 5.0% decrease for nondefense agency R&D. The House bill was written as an appropriations bill for the Department of Defense (DOD) and Veterans’ Affairs, and as a continuing resolution (CR) for the remaining agencies. This allowed the House to provide some flexibility to DOD and Veterans’ on how each could allocate the sequester cuts.
On March 11, the Senate Appropriations Committee released its revised version of the House bill. Both Appropriations Chairwoman Barbara Mikulski (D-MD) and Ranking Member Richard Shelby (R-AL) agreed to the legislation that would continue to fund the government for the remainder of the FY. The revised “hybrid” bill does not eliminate the sequestration but does expand the House version by including additional flexibility for the Departments of Justice, Homeland Security, Agriculture, and Commerce, as well as NASA and NSF. The bill also includes a small increase (a $71 million, pre-sequestration cut) for the National Institutes of Health. On March 20, the Senate voted 73 to 26 to pass its version of the Continuing Appropriations Act. The act includes an amendment submitted by Sen. Tom Coburn (R-OK) that limits funding for political science research at NSF; specifically, the agency will be able to fund political science research only if it is certified by the NSF director as “promoting national security or the economic interests of the United States.” The next day, the House of Representatives voted 318 to 109 to approve the Senate’s changes.
The White House released its FY 2014 budget request on April 10. The president proposes a $3.8 trillion budget in FY 2014, projecting a $744 billion deficit. In R&D funding, the budget calls for $144.1 billion, including $69.7 billion for basic and applied research. In general terms, the budget shows a marked shift from defense to nondefense R&D, and from development to research. Perhaps most notable for R&D funding, however, is the president’s proposal to roll back sequestration. Provisions in the Budget Control Act currently cap discretionary spending at $966 billion in FY 2014, a level that House Republicans have embraced. However, the president’s budget and Senate Democrats propose returning the discretionary spending limit to the pre-sequester level of $1.057 trillion. Resolving this $91 billion difference is key for R&D funding, as the president’s budget is predicated on the higher spending level.
R&D in the FY 2014 Budget by Agency (budget authority in millions of dollars)
Failing to raise the cap would likely leave FY 2014 looking much like FY 2013, when R&D funding fell by more than $9 billion, or 6.7%, below the prior year, according to American Association for the Advancement of Science estimates. This decline comes on the heels of cuts in prior years, resulting in a three-year R&D decline of roughly 17%, which would be the largest relative decline in federal R&D funding in 40 years. Although some of the reduction in FY 2013 was due to funding cuts in final appropriations, the majority of it was the result of sequestration. Some agencies did appear to fare better than others in the final summation. For instance, NSF, the Department of Homeland Security (DHS), the National Nuclear Security Administration, and the National Institute of Standards and Technology (NIST) all received funding boosts that partially or fully offset sequestration.
Because FY 2013 appropriations came a full six months late, the administration delayed its own FY 2014 request until April. Compared with postsequester FY 2013 estimates, the budget proposes substantial increases across virtually every major agency. Compared with FY 2012 (the last year before sequestration), the budget would boost nondefense R&D spending by 5.2% after inflation and cut defense R&D by 9.5%. The defense cuts are all in the development stage, and research spending would actually increase.
In inflation-adjusted dollars, the administration proposes a combined 4.9% increase above FY 2012 for R&D at the America COMPETES agencies (NSF, NIST, and the Department of Energy’s Office of Science); a 4.2% increase for the Department of Agriculture, including a nearly 50% increase for extramural research; and a neardoubling of the DHS R&D budget for construction of the National Bio- and Agrodefense Facility in Manhattan, Kansas. However, the budget also cuts 2.4% from NIH, 1.4% from NASA, and 5.4% from the Environmental Protection Agency. Many of the key increases are reserved for targeted programs intended to drive technological innovation, including smart systems, materials, and cyberinfrastructure research at NSF; the Space Technology mission at NASA; the Clean Energy Manufacturing Initiative at the Department of Energy; and the National Center for Advancing Translational Science within NIH. DOD’s R&D budget would decline substantially, although basic research funding would increase.
Although the budget continues to make investments in the administration’s priority research areas, the overriding question is whether Congress can agree to a deal that raises the discretionary spending ceiling to make the president’s budget work. Barring an agreement, FY 2014 would end up looking similar to FY 2013, with billions of dollars in lost R&D falling victim to the nation’s fiscal challenges.
The Obama administration has proposed a reorganization of science, technology, engineering, and math (STEM) education programs in what it says is an effort to more efficiently manage the $3 million that the federal government spends each year on science education, public outreach, and training programs for new scientists and engineers.
The president’s FY 2014 budget outlines a plan for reducing the number of active STEM programs from 226 to 112; 78 programs would be eliminated altogether, and 49 would be consolidated. The consolidated programs would be run under the auspices of one of three agencies: the Department of Education would manage precollege science and math education programs, NSF would manage undergraduate and graduate STEM training, and the Smithsonian Institution would manage any extracurricular STEM activities.
Although there would be budget cuts for specific agencies that would lose their STEM programs—most notably NASA, NIH, and the National Oceanic and Atmospheric Administration— the budget calls for a $3.1 billion investment in STEM education programs, a 6.7% increase from FY 2012 levels. The Department of Education alone would receive a 4.6% increase from FY 2012 levels to fund, among other things, a new Master STEM Teacher Corps Initiative and the STEM Teacher Pathways program, which was designed to prepare 100,000 new STEM teachers for the workforce in the next 10 years.
This proposal comes in the wake of a 2012 General Accounting Office (GAO) report that found that 83% of federally managed STEM programs overlapped to some extent, but less than half of these programs were coordinated with other agencies. The GAO also reported that agencies were not evaluating the success of their programs adequately.
“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.
On April 2, the White House announced that $100 million in its FY 2014 budget proposals would be designated for a new research initiative focused on the human brain. The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative would include research investments from NIH, the Defense Advanced Research Projects Agency, and NSF, as well as public/private partnerships.
Congressional activity has recently cast a gloom over the future of social, behavioral, and economics (SBE) research. In late April, Lamar Smith (R-TX), the chairman of the House Science, Space and Technology Committee, submitted a letter to NSF requesting “access to scientific/ technical reviews and the Program Officers Review Analysis” for five SBE-related research grants. The letter elicited a sharp retort from the committee’s ranking member, Eddie Bernice Johnson (D-TX), expressing concern that it would “destroy the merit-based evaluation system at NSF.” Meanwhile, ScienceInsider reported on a discussion draft bill (not formally introduced) that would require NSF to certify that each grant met three specific criteria including: “is of the finest quality, is groundbreaking and answers questions or solves problems that are of utmost importance to society at large” and is in the “interests of the United States to advance the national health, prosperity, or welfare, and to secure the national defense by promoting the progress of science.”
On April 26, the House approved the Responsible Helium Administration and Stewardship Act (H.R. 527). The bill authorizes the Secretary of the Interior to resume sales of “crude helium for federal, medical, scientific, and commercial use.” The legislation aims to stall a potential shortage of helium by creating a phased approach for access to and pricing of the helium reserve. The Senate has initiated hearings to consider the House bill.
On April 16, the House passed two bills related to interagency cybersecurity research. The first bill, the Cybersecurity Enhancement Act (H.R. 756), would reauthorize cybersecurity research and education programs at NSF and NIST. In addition, it would require the administration to submit an assessment of cybersecurity risks across all federal agencies as well as a strategic plan to guide R&D. The second bill, the Advancing America’s Networking and Information Technology Research and Development Act of 2013 (H.R. 967), would reauthorize the interagency Networking and Information Technology Research and Development program created in 1991 to fund R&D in computing, networking, and software.
A bipartisan group of eight senators formally unveiled their major immigration reform bill on April 17. The bill features a new class of visas for entrepreneurship and would significantly boost the number of H1-B visas available to immigrants with advanced degrees, particularly in math and science. The Senate Judiciary Committee quickly held hearings on the bill.
The STEM Education Opportunity Act (H.R. 1353), introduced by Rep. Richard Hanna (R-NY), would amend the Internal Revenue Code of 1986 to allow a tax deduction for students enrolled in STEM programs at institutions of higher education. The bill was introduced in the House on March 21 and has been referred to the Ways and Means Committee for consideration.
On March 21, Science, Space and Technology Committee ranking member Eddie Bernice Johnson (DTX) introduced the STEM Opportunities Act of 2013 (H.R. 1358) to promote the participation of women and minorities in STEM fields. First, it would require NSF to collect comprehensive demographic data on the recipients of federal research awards and on STEM faculty at U.S. universities in order to better understand national patterns. It would also require the Office of Science and Technology Policy to address best practices across federal agencies to minimize the effects of implicit bias in the review of federal research grants.
The Space Leadership Preservation Act (H.R. 823) has been reintroduced by Rep. John Culberson (RTX) and four cosponsors. The bill would extend the term of the NASA administrator to six years, create a board of directors to oversee the agency, and restructure the budget. The House Science, Space, and Technology Committee held a hearing on the legislation in late February.
Reps. Peter DeFazio (D-OR) and Jason Chaffetz (R-UT) introduced a new bill, Saving High-tech Innovators from Egregious Legal Disputes (SHIELDS) (H.R. 845), that would protect U.S. innovators from “patent trolls” who buy very broad patents for products they did not create and then sue companies for infringement.
Proposed: A Competition to Improve Workforce Training
In the United States, education and training programs have long been key in helping people get better jobs and achieve higher living standards. With the earnings divide between skilled and unskilled workers at a historic high, the imperative for increasing skill levels is great. Training programs offer opportunities for low-income individuals to qualify for jobs that enable them to enter the middle class and for displaced workers to regain a significant portion of their lost earnings. Improving workforce skills also enhances the nation’s competitiveness and fosters economic growth.
Evidence shows that many career and technical training programs lead to high-paying jobs and stable careers. In fact, the earnings of young adults with two-year degrees in technical and industrial fields or with certificates requiring at least a year’s worth of credits in similar fields often are comparable to those of workers with more traditional four-year degrees. Moreover, there is sound evidence that these benefits can accrue to workers young and old and to those with strong or weak academic backgrounds. For example, 65% of individuals who received training certificates in high return fields had grade point averages (GPAs) of C or lower in high school, compared to only 15% of individuals who earned four-year degrees in high-return fields. This difference suggests that poor academic preparation need not be a barrier to obtaining a high-return credential.
Even with the best of intentions, however, many people seeking career advancement ultimately choose training programs that do not suit their needs or the needs of local employers, and many do not complete the training programs. Some, uncertain of the outcomes, hesitate to invest time and money in training at all. These poor choices represent a troubling loss of economic gains for workers and for taxpayers.
A main reason for such poor results is that many people interested in pursuing new or upgraded skills cannot obtain reliable information about what training programs are available, how completing programs affects earnings, and whether they have the attributes needed to complete the high-return programs. The good news is that these information deficits can be resolved.
Toward this goal, we offer a plan that is built on providing prospective trainees with the information they need in ways that make it easy to use and understand. The plan, which will be organized on a state-by-state basis, will feature a mix of online information systems coupled with assistance from career counselors. The online systems could be accessed at workers’ homes, public libraries, campus career centers, and public One-Stop Career Centers supported by the Workforce Investment Act. The help from career counselors could be integrated into support programs at training institutions and at One-Stop Centers.
To drive the plan forward, we propose a competition among states for grants to enhance information collection and dissemination and expand the availability of staff-provided career guidance. Statistical analyses and educated opinion suggest that our plan will work. The competition will definitively assess its overall success, identify which of its components are most effective in terms of performance and cost, and provide a blueprint for maximizing returns for workers and the nation alike.
Our hope is that the competition will be jointly run by the U.S. Departments of Education and Labor. To be effective, $15 million will be needed over five years to fund at least two state proposals.
Big payoff, but poor choices
Evidence shows that many career and technical training programs lead to high-paying jobs and stable careers. In fact, young adults with a two-year degree in a technical or industrial field or a certificate requiring at least a year’s worth of credits in similar high-return fields often increase their earnings by 33% or more, to levels comparable to those of workers with more traditional four-year degrees. In contrast, students with two-year degrees in low-return fields seldom enhance their earnings at all.
Unfortunately, a recent study in Florida showed that three out of four young community college students either completed low-return programs or did not complete enough high-return courses for them to have much of an effect on their earnings. Similar results have been observed in studies in the state of Washington and in Pittsburgh, covering unemployment insurance claimants of all ages.
To better understand why students often make poor choices, we interviewed staff who advise students and other participants at community college and workforce training programs. The close-to-unanimous conclusion from our discussions is that the prospective trainees face systematic information deficits that hinder decision-making. For example:
They are not aware of the wide range of programs available at local community colleges and for-profit training institutions. In particular, although they are familiar with academic programs leading to two- and four-year degrees, they often are unfamiliar with the wide range of available highreturn certificate and career-oriented two-year programs.
They have limited information about how returns vary among programs. They overestimate the returns from academic programs and underestimate the returns from career-oriented programs, especially those in building trades and protective services. They fail to recognize that some high-return programs can be completed quickly, whereas others take years to complete. They also fail to recognize that demand for some skills is widely distributed across the country, whereas other skills are in high demand only in some locations.
They have difficulty assessing whether their schooling and experience are adequate for them to complete programs. On the one hand, they underestimate the importance of academic preparation in certain high-return fields—such as those related to science, technology, engineering, and mathematics (STEM)—and they fail to recognize when their STEM skills are not strong enough to complete certain highreturn programs. On the other hand, they fail to recognize that they have skills needed to obtain high-return certificates in areas such as health care, protective services, auto mechanics, plumbing, and heating and air conditioning repair and installation.
They have great difficulty obtaining effective career counseling. They may have few friends or relatives to turn to who are knowledgeable about training options. This is often true for low-income workers, blue-collar displaced workers, and children of immigrants who may be the first in their families to pursue further career training.
They are not able to adequately compare the net returns across similar programs at different institutions. By not factoring in differences in costs, they sometimes select highreturn, high-cost, for-profit programs from which, after repaying loans, the net benefits are no higher than from lowerreturn but much less expensive community college programs. Although many for-profit programs offer high-return training that more than offsets their high costs, some advertise misleading statistics about benefits and costs. In addition, for-profits spend far more on advertising than community colleges do. The advisers we surveyed said that potential trainees too readily accept advertising claims without assessing their accuracy or carefully weighing the benefits and costs of alternatives.
Constructing simple measures of who participates in the programs and how they fare in the job market can yield valuable information.
One factor contributing to such awareness gaps is that community colleges spend billions of dollars on instruction but only tiny amounts on support services. The counseling that takes place is aimed toward helping students select the courses they need to complete a program—after they have already selected a program of study. There are few organized efforts to help prospective trainees make sound choices of programs that further their goals and complement their skills. At most community colleges, the ratio of students to career counselors is greater than a 1000 to 1.
There is some evidence that counseling students does help and can be a key element of successful dropout prevention programs. Community colleges counselors reported that their services frequently prevented prospective trainees from enrolling in programs that they were unlikely to complete, were unlikely to improve their career prospects, or were inconsistent with their interests and constraints.
There is also evidence that counseling can be done at low cost. One-Stop Career Centers provide these services to all applicants for training vouchers to help them select an appropriate program. The services, which include individual and group counseling with well-trained staff, cost less than $400 per person. At the conclusion, individuals have filled out a form similar to a college application that is based on their own research and the information obtained from their counseling that describes the likely outcomes from the best available training options, the requirements to complete those options, the extent to which the individual meets those requirements, the direct and indirect costs of the training, and how those costs will be met.
Although there is unambiguous evidence that many career-oriented training programs are capable of increasing the earnings of workers with diverse backgrounds, the evidence is less strong for how better information and improved assessment and counseling would affect students’ selection and completion of high-return programs. This is precisely the knowledge gap that our proposed competition is intended to fill.
Shape of the competition
Most states, aided by substantial data development funding by federal and state governments, already have a wealth of basic data on various aspects of workforce training. Several states are using the data to produce relevant performance measures, and a few states even make that information available online. But overall, the systems have not produced much improvement in the completion of career and technical training programs that offer high payoffs for participants.
In part, this is because users are unaware of or lack the means to access the systems. A more central problem is that the information is often not presented in ways that make it useful. Potential trainees who currently make the poorest training choices often have the least experience and preparation in using data to make complex decisions. This is especially true for individuals who did not do well academically in high school and have had little, if any, postsecondary education.
The competition we propose will offer grants to states to use their own existing longitudinal data systems to fill major information gaps and then deliver the information to prospective trainees in a meaningful way. The grants would support efforts in four areas. These are: (1) assembling the data needed to make sound decisions; (2) organizing the data to produce relevant measures, including those that accurately reflect the payoffs from training programs and are needed to identify high-return fields and programs; (3) disseminating the information using systems that combine use of computers and staff in a way that improves training choices; and (4) sustaining systems that prove to be costeffective. Although the primary focus would be on helping prospective trainees make the best possible choices, the competition would also create incentives for administrators and policymakers to respond to changes in those choices by moving resources from low-return programs where few workers end up with better jobs to high-return programs where many workers end up with better jobs.
The following section examines each of the program components in turn.
Assembling data. States would assemble longitudinal data that link completion of specific education and training courses to labor-market outcomes. Included would be data on completion rates and post-program earnings of participants in specific programs; on program attributes such as field of study, duration, and cost; and on participants’ backgrounds, including age, gender, years of education, highschool grades, number of years of high-school math and science courses, and pre-program earnings.
Much of this information is already available. Although some of the data were collected in response to the No Child Left Behind Act, the major impetus came from the Department of Education when it made more than $600 million available through its Statewide Longitudinal Data Systems (SLDS) program, and from the Department of Labor when it made about $30 million available to add workforce data to the education data. Today, at least one-third of the states have a full system in place that includes secondary, postsecondary, and earnings data, and most of the remaining states lack only the inclusion of wage record data, which are not especially difficult or costly to include. Some states have data going back 10 or 20 years, which are very useful for assessing the long-term effects of training and how the effects vary under different economic conditions.
For this component of the competition, states would be required to identify the sources of data they intend to use and how they would be matched at the individual level, including safeguards to protect personal privacy.
Organizing data. States would use the data to demonstrate how post-program earnings and completion rates vary depending on the characteristics of the programs, characteristics of the participants, and characteristics of the local labor markets. Whereas nearly all states have the data required to estimate expected completion rates and earnings, or could assemble these data relatively easily, only a few states have organized the data to provide the information required to help actual and potential trainees improve their choices. These states have used the data mostly to produce basic tabulations of the number of students in a training program, number completing the program, basic characteristics of the average student, number employed, and earnings over different periods.
A key goal of the competition is to encourage states to produce statistics that potential trainees can use to assess their probability of completing different programs, estimate the boost in earnings they could achieve after completing the programs, and develop realistic estimates of direct and indirect program costs. Without having all three types of information, potential trainees might enter high-return programs that they would be unlikely to complete or that would cost more than students’ expected increases in earnings.
Constructing simple measures of who participates in the programs and how they fare in the job market can yield valuable information on program completion rates and subsequent earnings by field of study. Analysis can also show the importance of program length and intensity, trainee characteristics such as academic preparation that affect outcomes, and labor- market characteristics relating to local demand for workers in different fields.
More advanced measures can tailor the information to applicant and program characteristics. For example, prospective trainees can be advised that information technology (IT) specialists earn about $45,000 three years after completing training. However, 90% of those completing IT programs had high-school GPAs of 3.0 or better and completed at least three years of high-school math courses. Trainees also could be informed that IT graduates living in cities with substantial high-tech employment earned about $15,000 more than IT graduates living in small cities and rural areas far from high-tech centers. Further, prospective trainees who lack the academic preparation that makes completion of IT programs likely could be given comparative information about health care, protective services, and other training programs that offer high wages and high probabilities of completion to trainees with lower levels of academic preparation.
Growing recognition of the importance of providing reliable information about the returns and costs of training is demonstrated by the Department of Education’s Gainful Employment programs, which require certain education institutions, including for-profit groups that offer courses that do not lead to a degree, to disclose a range of information to prospective students. The disclosure requirements, however, assume that the information would be understood sufficiently to reduce unreasonable risk-taking by prospective trainees, especially those who might incur large debts to obtain high-cost training from for-profit institutions. Our proposed competition would complement Gainful Employment by providing information about which statistics are misleading and what set of well-rounded statistics and assistance in interpreting them would lead to attainment of the programs’ underlying goals.
In the end, these calculations should provide easy-to-understand metrics to help stakeholders navigate the world of workforce development programs. For this component of the competition, states would be required to describe what statistics would be produced, how the data collected would be used to create those statistics, and what group or body would be charged with the task.
Disseminating information. States would develop ways to display the information and provide staff assistance when necessary, so that stakeholders with different levels of experience in using data to make complex decisions end up making sound decisions. States would be free to propose creating and testing a range of systems to display and disseminate information as well as provide staff assistance. Whatever systems the states implement, they will need to develop rigorous methods to measure their overall effectiveness and how different elements affect users with different characteristics. Particular attention should be given to devising systems that combine online and staff assistance, so that individuals who often fail to make sound decisions get the help they need. This group includes individuals with the poorest academic preparation and least experience in using data to make decisions.
One option that states might choose for displaying information could be posting at-a-glance report cards on the Web that describe training programs and their performance. Report cards might be developed and tested with three (or more) different levels of complexity.
States might start by developing a basic report card that draws from the SLDS program. The report card could have a menu-based system similar to the Web-based systems commonly used to find, for example, the lowest airfare. At the most basic level, a potential trainee could specify program characteristics, and the Web-based system would display a menu on completion rates and earnings of appropriate programs. For example, potential trainees could enter items such as the field of interest, the location of interest, cost, duration of the program, whether full-time attendance is required, high-school GPAs of completers, expected earnings gains of completers, and percentage typically completing.
The search engine would select the specific programs that meet the user’s criteria in an order specified by the user, such as from highest to lowest expected returns. The user would review the information and alter the search criteria to narrow the search to the most relevant options. As the search is narrowed, the user could request that the system present a screen that directly compares one program with other programs.
Florida and other states have systems that use the SLDS to place this type of information on the Web, along with information about the cost of the programs, entrance requirements, and duration. For example, a prospective trainee could inquire about registered nursing programs and certified nursing assistant programs in Miami and then compare differences in earnings, completion rates, cost, and duration across these two types of programs and within each type.
To build on the basic report cards, states could create an intermediate-level system where trainees would enter personal characteristics to obtain more tailored choices. The list of programs to be considered could be narrowed by putting in personal characteristics such as highest level of education, GPA, number of math courses completed, grades in those courses, and characteristics of programs of interest, such as cost, duration, flexibility of when and where courses are offered, and fields of study. By providing much more accurate information about the individual’s probability of program completion, the intermediate system would quickly narrow consideration to programs that have a high potential for completion and for generating high returns for the individual user. Thus, the intermediate system would reduce the burden placed on users of determining the extent to which general statistics provided by the basic system would apply to them.
An advanced system using report cards would include all the features of the intermediate system, along with a Webbased assessment of the potential trainee’s attributes that affect the probability of completion and interests. For example, there are Web-based versions of both the Armed Service Vocational Aptitude Battery and tests offered by ACT that potential trainees could take to assess their level of academic and work-related skills as well as the careers the testtaker would be best qualified for and find most interesting. When entering such test results into the state system, prospective trainees could widen the range of programs to be considered or narrow choices to programs with the best salaries and highest levels of personal satisfaction.
Prospective trainees also could use community college entrance exams and other tests to determine whether they qualify for specific programs. An important adjunct to these tests would be an online tutorial system that would help potential trainees brush up on skills they once mastered or even develop new skills needed to gain entrance to programs. Pueblo Colorado Community College, in association with the local One-Stop Center, has developed this type of system. It has helped many trainees enter high-return training credit programs without having to first complete time-consuming and costly remedial courses. Such a system would be especially beneficial to workers who are unaware that community colleges require passing entrance exams to enter many programs, have rusty skills because they have been out of school for many years, or cannot afford the time or expense of completing remedial courses.
In addition, the same systems that collect data and create the report cards for use by prospective trainees can produce metrics that are useful to decisionmakers who want to understand how to better serve program participants. In particular, administrators could use information on labor-market returns to adjust course offerings—dedicating more resources to programs that meet trainees’ needs and cutting back on programs that are mismatched to local employer demand. Greater transparency regarding performance will also exert competitive pressures on programs to improve outcomes.
As the primary determinant of an award, we recommend using a combination of the expected benefits of the proposed system relative to its cost and the feasibility of creating the system.
Sustaining systems. States would need to identify information systems that are unambiguously cost-effective and propose ways to permanently fund effective systems after grant startup funds are exhausted. Sustainability is a relevant component of this competition because it will give precedence in awarding funds to states that have realistic plans to implement cost-effective systems. It also will give states opportunities to think about ways to create incentives for trainees to use the systems to achieve their own goals and for program administrators to use the systems to increase the returns from taxpayers’ investments.
For example, states could require recipients of student financial aid to use the systems to develop a realistic plan to achieve their goals, with the expectation that simply reviewing their options will improve their choices without any compulsion to alter decisions. Similarly, states could require community colleges to put in place performance-management systems to assess labor-market effects of career-oriented programs and make resource allocation decisions that increase the number of high-return slots at the expense of low-return ones.
In explaining their proposals, states could demonstrate that their legislatures would approve the funds needed for continued operation. Or they could describe ways to secure funding that would not require new appropriations. For example, they could propose making small reductions spread across many students in state-funded scholarships to cover ongoing costs, or they might propose reducing community college career and technical education programs with low enrollment and using those savings to fund the Web-based systems and provide more career counselors. Such mechanisms might also induce state education agencies and legislative bodies to reallocate resources from low-return to high-return programs based on evidence of their cost-effectiveness.
Close-up view of proposals
As with the Department of Education’s Race to the Top competition, a key to obtaining high-quality proposals is to clearly define the goals of the competition (including the theory of action underlying those goals) and to provide a clear understanding of what is required to win an award. We want the proposed competition to focus attention on the need to create an integrated system where the whole is greater than the sum of its parts: assembling relevant data, creating useful measures from those data, testing alternative ways to disseminate the information so that it improves trainee choices, assessing the cost-effectiveness of alternatives, and putting in place permanent systems once they are proven to be cost-effective.
A second key element of the competition is creating an effective scoring system that ensures that the funded proposals are those with the greatest potential to provide clear evidence of the effectiveness of systems for helping a range of users. As the primary determinant of an award, we recommend using a combination of the expected benefits of the proposed system relative to its cost and the feasibility of creating the system. The goal is to fund innovative proposals that go beyond systems already in place but are still feasible to construct with available technologies.
The first part of each proposal would describe the system, provide a convincing explanation of how it would increase earnings and returns on investment, and explain how those benefits relate to costs. The centerpiece of the description would be an analysis of how the system would alter the choices made by prospective trainees and how those changes would affect earnings and investment returns.
The second part of the proposal would detail how the system would be created within the proposed time and budget constraints. It would include a thorough description of what data would be used, how the data would be organized to estimate completion and earnings, how the estimates of completion and earnings would be developed, how those estimates and other information would be accessible on a Web site, and how end users would extract information from the system. A key component of this discussion would be describing prior experience in performing each task and the qualifications of the team members on the project.
The third part of the proposal would describe how the proposed system would be tested, the types of training programs and users that would be included in the test, and how the benefits of the system would be measured. The more inclusive the test and the greater the rigor of the test, the more points would be awarded.
Although the estimate of the expected value of the proposed system would be the primary basis for making awards, no award would be made unless the proposed tests were sufficient to determine whether the system was cost-effective for at least some users and some types of programs. However, the review panel could work with a state with a promising proposal to refine the tests to reach a point where a reasonable accuracy would be achieved.
The fourth part of the proposal would describe the funding mechanisms that would be used to sustain systems once they are demonstrated to be unambiguously cost-effective. This section also could describe how states would ensure that trainees and program managers use the systems effectively and thereby generate the savings that could be used to sustain the systems.
For example, trainees receiving state grants could be required to produce coherent plans that examine local demand for the skills being pursued, the probability of program completion, direct and indirect costs, and how the out-of-pocket expenses would be covered before registering for programs. Community colleges could be required to conduct orientations for first-time students before they register for classes or after registering but before the start of classes. That orientation would include group sessions providing an overview of how to use the information systems to identify and select effective career training plans, as well as group and individual sessions to review plans with career counselors. Similarly, program managers could be required to oversee the development of information on workplace outcomes by program and student characteristics, and then use the information to provide feedback to various departments or to make decisions on resource allocations.
Our view is that awards should go to states whose proposals describe systems with the best chances of being highly cost-effective, as long as they provide the means to determine their effectiveness. However, if there are proposals that are roughly equivalent in terms of expected value and clarity of evaluation, preference should go to proposals that offer the system with the greatest promise of being sustained.
Returns on investments
We expect that new systems developed under the competition grants will lead to at least a 10% shift in outcomes among students who currently fail to make sound choices when seeking career-enhancing education and training. This shift would substantially reduce the percentage of students who leave college after a year or so with no career-enhancing credential, or leave with a low-return two-year degree. If 10% of students end up making better choices by obtaining a high-return certificate or two-year degree, the social return on the investments in training programs also would increase significantly. And perhaps an even larger positive effect could come from improved information and counseling that induces workers to seek training, particularly those who do not enter training programs because they are uncertain or even skeptical of their benefits and costs.
We are optimistic that the demonstrations will capture the best available information and make it available in practical and innovative ways that will yield many rewards. We are also optimistic that determining precisely how much difference it would make if the information available to prospective trainees were improved and they were offered more help in making decisions that further their goals in a few states will lead to widespread adoption of effective systems.
Given the problems of current education and training efforts, as well as the tightening budgets of the many people still out of work, we think the time is right to set the wheels of competition—a historic driver of the nation’s progress— in motion.
A Public-Private Approach to Public Safety Communications
After the tragic bombing at the Boston marathon, Boston’s cellular networks instantly filled with calls. One company spokeswoman had to publicly plead with its customers “to use text or email to free up voice capacity for public safety officials at the scene.” In other words, this nation allocates resources that are critical for emergency response through the use of plaintive press releases. U.S. public safety agencies do have the alternative of using their own communications systems, although most of today’s public safety systems are based on pre-Internet, pre-cellular technology that does not meet the needs or expectations of today’s emergency responders.
As I argued in a 2007 article in Issues, part of the problem with traditional public safety communications systems is that many thousands of individual police and fire departments run their own systems, perhaps with a different technology than their neighbors, when what is really needed is a nationwide solution. There has since been movement in this direction, culminating in 2012 when the U.S. Congress funded the creation of a new nationwide network called FirstNet. However, FirstNet’s success is still uncertain. A shift in priorities could put FirstNet on a better path. In particular, whereas much of current discussion of FirstNet revolves around building new infrastructure specifically for public safety—and new infrastructure should certainly be built—time and funding constraints should shift the immediate focus from building new infrastructure to leveraging existing infrastructure and commercial technology in new ways, including new forms of public/private partnerships.
By almost any measure, the thousands of public safety communications networks in the United States today are inadequate. The most discussed problem is the lack of interoperability, which means that in many places emergency workers such as police and firefighters have incompatible communications systems that prevent them from interacting with one another. However, interoperability is just one of the problems. Current public safety infrastructure is unnecessarily expensive, because all these independent and overlapping networks require an order of magnitude more towers than would otherwise be needed. Indeed, if one wants to predict the amount of costly infrastructure that will be built in a region, the number of municipal governments in the region is a far better predictor than either the population or the area of the region. The unnecessarily large number of towers combined with pre-cellular technologies also make public safety an extremely inefficient user of spectrum, and preventing a shortage of available spectrum from hampering economic growth has become a high priority for the U.S. government. Moreover, because so much equipment is designed specifically for the fairly small public safety market, mobile handsets for public safety typically cost an order of magnitude more than handsets that are mass-produced for a consumer market. Finally, traditional public safety systems support only voice communications at a time when consumers carry phones that offer data capabilities and countless applications that would be very useful for emergency responders. In short, U.S. taxpayers expend billions of dollars more than necessary every year to perpetuate a system that fails to meet modern needs or exploit new technologies. The solution to all these problems is to build out a public safety network infrastructure that serves the thousands of municipal public safety organizations and is based on a single technical architecture that uses spectrum efficiently. At this time, such an architecture would be based on the fourth-generation cellular standard (LTE) and Internet standards (IP).
Such a system could save many lives. Imagine a city that has just been battered by a hurricane. Emergency responders from adjacent states rush to the city for search and rescue missions. Today they would come with incompatible communications equipment, so coordination would be a problem. Moreover, as we saw after Hurricane Katrina, even local responders may not be able to communicate if the hurricane destroys the towers they depend on, even if there are commercial systems still working. Those responders who are lucky enough to have access to a working system will have voice communications and nothing more. In contrast, with FirstNet, responders from all agencies will be able to communicate using whatever infrastructure has survived. In addition to voice communications, medics will send video of critical patients back to hospitals, police will distribute pictures of missing children over the airwaves, and firefighters will download the blueprints of damaged buildings to see how to enter safely.
The 2009 transition from analog to digital television created a once-in-a-generation opportunity to reinvent public safety communications by suddenly making bands of prime spectrum available nationwide. Under the right federal policy, it would be possible to adopt a single technical approach nationwide and to choose an approach that uses the latest and most cost-effective cellular and Internet technologies to bring a wide range of broadband services to public safety. This new approach for public safety was endorsed by the government in the 2010 U.S. National Broadband Plan, and later by the White House. The idea became real in 2012 when Congress authorized funding and reserved 20 megahertz (MHz) of spectrum that was previously used for TV for the creation of FirstNet, a network for first responders. This raised expectations, which is both an opportunity and a danger. Now the biggest threat to success for FirstNet may be the risk of not meeting these expectations quickly enough with the resources available. FirstNet’s funding will fall somewhere between $2 billion and $7 billion, depending on how much money is raised in the future auction of spectrum that becomes available after some TV broadcasters voluntarily choose to relinquish their spectrum. If the maximum of $7 billion is raised for FirstNet, it would be a great start, but still not enough money to build out infrastructure everywhere in the country. For example, the Federal Communications Commission (FCC) estimated the cost of building an LTE network in the most-populous areas that would provide indoor coverage to 99% of the population and outdoor coverage to 99.5%. This plan, which would leave roughly 45% of the U.S. land area without coverage inside buildings and 37% with no coverage at all, would cost between $12 billion and $16 billion over 10 years, of which $7 billion would be capital cost. This estimate assumes that costs would be decreased through a high level of cooperation with commercial carriers, which may or may not occur. Lack of cooperation could double or triple capital costs. Moreover, some responded to this analysis by saying that the network should support even greater data rates than the FCC had assumed, because public safety would benefit from higherquality video. Increasing upstream edge-of-cell rates from 256 kilobytes per second to 1.2 megabytes per second was also found to increase capital cost almost threefold. Clearly, infrastructure cannot be built everywhere with this budget, even under best-case assumptions.
Some money may come from state and local sources, but the federal government will need to be the primary funder. Of course, Congress could appropriate more federal money. After all, this kind of infrastructure-building could save lives by strengthening public safety and homeland security, while creating jobs in the short term and saving taxpayer money in the long term. Such opportunities are rare. Nevertheless, additional funding from Congress seems unlikely, given the current state of budget discussions. Thus, if FirstNet is to deliver useful services to the entire nation, rural as well as urban, it cannot rely only on building infrastructure to achieve this. Luckily, there are other options.
Meanwhile, if FirstNet cannot deliver valuable capabilities quickly, it may never get the chance. Congress gave states the ability to opt out of FirstNet entirely and use that 20 MHz of spectrum in other ways. There are also a number of cities that have expressed a preference for running their own infrastructure. If many cities and states go their separate way, the result will recreate the public safety tower of Babel characterized by interoperability failures, costly custombuilt equipment, and inefficient use of expensive infrastructure and valuable spectrum. At the same time, some of these states and cities are understandably anxious to move forward quickly on infrastructure that can save lives. FirstNet can keep them interested in being part of a nationwide system by making clear that concrete benefits are coming soon to every state that backs the FirstNet plan. FirstNet must move quickly, and this urgency should affect the approach to deployment.
Use what we have
The best way to provide useful services nationwide quickly and with limited funding is to leverage commercial infrastructure and technology as much as possible. However, there are strong forces pulling in different directions. Some public safety advocates envision a nationwide public safety infrastructure that is built specifically for public safety and does not make use of existing commercial systems, much as today’s LMR (land mobile radio) public safety systems do not make use of commercial systems. This vision is based in part on the traditional view of public safety agencies that they should be in complete control of their resources, without the need to negotiate with commercial providers, and it is based in part on misconceptions about how far the budget can go. Under the 2012 law, this is simply not feasible, as it would take significant time to roll out all-new infrastructure nationwide and cost far more than $7 billion. Moreover, much of the money and time would be spent building infrastructure in densely populated areas that are already well served by multiple commercial providers. Even with infinite budget and time to deploy, this is not the ideal solution for public safety. When this stand-alone network is not functioning, perhaps because a tornado hit a public safety tower, emergency responders would have no communications at all.
On the other side, there are those who envision emergency responders relying entirely on the products and services emerging from the commercial market. This might be profitable for the carriers, but it would also fail to meet public safety needs, as many public safety representatives have pointed out. It is obvious that there are parts of rural America that will not get LTE coverage any time soon, so emergency responders there cannot rely on the commercial market. Less obvious is the fact that even big cities include areas where signal reliability is inadequate for emergency response, and the cost of extending infrastructure to serve these areas better is not justified based on the number of paying subscribers who live there. Like coverage, infrastructure dependability is also a concern. Profit-seeking commercial carriers do not always have the incentive to provide sufficient power backup or physical hardening to meet public safety standards. Similar issues exist in the handsets. Although public safety agencies can reduce costs by using components mass-produced for the consumer market wherever possible, emergency responders need features that may not emerge from a commercial market without a certain degree of coaxing. Of particular importance is the ability for user devices to communicate directly with each other, rather than requiring that all communications pass through a cellular tower. (Engineers in the Internet world refer to this as “ad hoc networking,” and public safety users refer to it as “talk-around.”)
Considering these limitations, the best path is a hybrid strategy that leverages commercial infrastructure where possible, supplements it where necessary, and allows significant progress in a short time. A number of actions could be taken that would shift FirstNet’s emphasis in its early years to taking advantage of existing commercial capabilities without compromising the overall approach of the FirstNet plan.
Priority roaming agreements. Although deploying infrastructure that operates in the mostly idle 20 MHz of spectrum that has been allocated to public safety is certainly worth doing, the best way to make high-quality LTE services available through much of the nation quickly and at little initial cost is by establishing priority roaming agreements with commercial carriers. With a priority roaming agreement, an emergency responder can tap into a commercial network and have priority access, thereby guaranteeing good quality of service even when the network is congested with traffic from non-emergency responders. LTE offers a wide range of sophisticated features that support priority access, although negotiating the specific details with each carrier will require care. Indeed, in any region where this is possible, priority roaming agreements should be established with multiple carriers.
The best way to provide useful services nationwide quickly and with limited funding is to leverage commercial infrastructure and technology as much as possible.
This has several enormous advantages. One is capacity. There are roughly 3 million U.S. police, fire, and emergency medical services workers, but the commercial cellular infrastructure was designed to support over 320 million subscribers. Even in severe emergencies such as a terrorist dirty bomb attack in Manhattan, commercial networks can offer more capacity than prominent public safety groups have estimated they would need, and still have a lot of capacity left for civilian users. Moreover, being able to roam onto two networks increases capacity available to public safety by far more than the obvious factor of two, because devices such as mobile video cameras that require high data rates can connect to the closest cell tower, regardless of provider. For a given amount of spectrum, the transmission rate achievable near the center of a cell is more than an order of magnitude greater than what is achievable near the edge of the cell. As long as cell towers of different carriers are not collocated, a device can often choose its carrier so that it operates near the center of a cell, and therefore requires far less spectrum. Another advantage is fault tolerance. If just one network, government or commercial, is working, emergency responders can communicate. Coverage is similarly improved, because a location is covered as long as a device there can connect to any one of the networks operating in its region.
Most important given the immediate constraints on First-Net, priority roaming agreements can be established quickly. Although some public safety representatives have expressed concerns about roaming costs, the cost should be less than many people expect, assuming that the prices paid by public safety agencies are no higher than those paid by the general public. Roaming charges are probably proportional to public safety traffic, whereas infrastructure costs are fixed independent of utilization. One cost study showed that roaming is less expensive than building new infrastructure in the long run if and only if the average utilization of the dedicated infrastructure built for public safety is under 10% for the multiyear life of the equipment. By its nature, public safety traffic comes in bursts; utilization can be quite high during large emergencies but is very low most of the time. Utilization of a public safety network may exceed 10% in many areas, making build-out beneficial in the long run. However, utilization probably won’t exceed 10% by much, meaning that priority roaming is a reasonably cost-effective alternative. In the most severe localized emergencies, which might take place over a few square miles, typical roaming charges have been shown to be small as compared to other costs, such as the overtime of emergency responders. The same cannot always be said for emergencies that affect very large areas, such as hurricanes, but there are other ways to protect the budgets of state and local agencies in these extreme cases.
Targeted infrastructure build-out. Because the FirstNet budget will not support nationwide deployment of infrastructure that operates in the public safety band, there will be a strong temptation to spend limited resources in a way that covers as many people as possible. In the short term, when funding is limited and the sense of urgency is great, this is precisely the wrong approach; it does not take full advantage of priority roaming. Initially, priority should be given to areas that meet one of two criteria. The first is that coverage in an area is not sufficient using only priority roaming onto commercial carriers. This may mean bringing coverage to rural areas that have none, but it also means filling in gaps that are important for public safety in urban and suburban areas, such as Rock Creek Park in Washington, DC.
The other criterion for selecting an area for early buildout is if that area will not require government funding. In some parts of the country, commercial providers will be happy to subsidize the build-out as long as they can provide commercial services over any capacity not needed for emergency responders. This creates an opportunity for a public/private partnership. As discussed above, public safety utilization is likely to be low much of the time, and this idle capacity can be quite valuable, at least in big cities where demand is greatest. Indeed, commercial carriers may pay for the privilege of serving public safety in return for access to public safety spectrum. Unfortunately, judging from earlier studies, these arrangements are probably only profitable for carriers in big cities. (There are those who hope to use this strategy to fund a truly nationwide build-out, and they are likely to be disappointed.)
Sharing infrastructure. In areas where commercial carriers already operate in their own spectrum, it is possible to deploy equipment that will “light” the public safety band as well by sharing many components, and this can greatly reduce costs. This may also involve some form of public/private partnership. When doing its cost estimates, the FCC looked at a variety of these cost-saving sharing arrangements. For example, under the sharing agreement, public safety may be able to make use of some or all of the following: existing cell towers, antennae, cabling, radio processing equipment, backup power facilities, and the communications links between cell towers and the nearest communications hub. According to FCC estimates, capital costs would be 2.5 times greater without this form of sharing. Savings are even greater with a synchronous roll-out; i.e., if the radio area networks operating in the public safety band are deployed at the same time as commercial systems are upgraded to LTE. Despite the tremendous cost savings, the approach has its detractors, because as long as funding is viewed as unlimited, it is easier for a government agency to build infrastructure if it does not have to cooperate with commercial companies.
There is a risk when public safety begins to rely on infrastructure owned by commercial operators for its basic operation. Unlike priority roaming arrangements, public safety will generally rely on a single provider in any given location. Initially, carriers may compete with each other to obtain this business, but once one is chosen, FirstNet must avoid becoming locked into that operator, as this would allow the operator to demand unreasonably high rents when the contract is renewed. Risk of capture can be reduced by signing long-term contracts and soliciting bids for followon contracts several years before an existing contract expires. Moreover, carriers are much less likely to use their incumbent position to charge higher rents in big cities where carriers derive significant benefits from access to public safety spectrum. Thus, it might be helpful when negotiating sharing arrangements to pair these cities with rural areas and require carriers to share infrastructure throughout the combined areas.
Note that if this kind of infrastructure sharing with commercial carriers can be used to bring wireless services to emergency responders in a given area, then priority roaming can also be used to provide those same services. If the only goal were to serve these areas as soon as possible, priority roaming would probably be the better choice, but infrastructure sharing is cost-effective where average utilization is high. Thus, both arrangements are desirable in the long run.
Multiband mobile devices. Infrastructure is worthless without mobile devices to use it. Negotiating with device manufacturers and standards bodies to create devices that meet public safety needs should be a high priority for First-Net. To obtain the benefits of priority roaming discussed above, devices must operate in the 20-MHz public safety band as well as bands operated by multiple commercial carriers. Some devices must be more rugged than is typical for the consumer market. Eventually, devices will be needed that support applications of importance to public safety, such as push-to-talk voice communications. This latter capability requires changes in the infrastructure as well as the handset and should be addressed in the standard-setting bodies.
FirstNet can gain the attention of manufacturers and standards bodies as long as it has the support of public safety agencies nationwide. If all of these agencies say they will purchase devices for local police and firefighters as long as those devices meet technical specifications set by FirstNet, then manufacturers will listen. The more states and cities opt out, the less effective this approach will be.
Mobile ad hoc networks. As proposed in the National Broadband Plan, fixed infrastructure should be supplemented with mobile devices that can form ad hoc networks, which means that the mobile devices in a region can communicate among themselves, even if there is no fixed infrastructure such as a working cell tower nearby. FirstNet can also make this happen. A good place to start would be to encourage agencies to equip police cars and fire trucks with such devices. This is a relatively inexpensive way to extend the reach of public safety infrastructure. In a location where the public safety network is reachable outdoors but not indoors, the mobile device on a fire truck may extend coverage into a burning building. Moreover, mobile devices that can form ad hoc networks are invaluable in areas where there is no functioning infrastructure, perhaps after a hurricane or earthquake. At least users in the disaster area could communicate with each other, even if they need some other means to communicate with people far away. FirstNet can make this happen in part by making sure that there is a common standard for public safety agencies nationwide and authentication services for those devices, so that even devices from different agencies can work together and can do so without serious risk of a security breach. Because it serves the nation, FirstNet is also better positioned than any state or municipality to ensure that there are stores of mobile devices that can be moved to a major disaster wherever it occurs.
FirstNet is now positioned to provide emergency responders with high-speed mobile data services, at lower cost, higher spectral efficiency, and greater dependability than we have seen with previous public safety systems. To reach this potential, they must move quickly. The key to making rapid progress at low cost is leveraging commercial infrastructure and commercial technology. This begins by establishing priority roaming agreements with multiple commercial carriers and aggregating the demand of public safety agencies nationwide to convince device manufactures and standards bodies to meet public safety needs. Without rapid progress, there is a danger that states and municipalities will go their own separate ways, and this historic opportunity will be lost.
Forum – Summer 2013
Smarter health care
Robert Saunders and Mark D. Smith (“The Path to Continuously Learning Health Care,” Issues, Spring 2013) describe a path for building a smart health care system that provides care at a lower cost. Their vision is akin to the “learning health care system,” defined by the Institute of Medicine (IOM) as a place where “each patient care experience naturally reflects the best available evidence and, in turn, adds seamlessly to learning what works best in different circumstances.”
This goal requires close relationships between research and care delivery, creating bidirectional learning where (1) research drives practice— including the organization of care; and (2) practice, steeped in the challenges of achieving the triple aim, drives research. The implication? Research must increasingly occur within real-world delivery systems. We at Group Health are among several health plans, research organizations, and funders working nationally to build such systems.
One key lesson to date is that learning systems require true partnerships among researchers, providers, and the communities they serve. As such, activities must focus on issues that are relevant and valuable to all. The Patient Centered Outcomes Research Institute, a new federally funded nonprofit aimed at finding evidence for health care decisionmaking, wisely exemplifies this value by requiring patient and provider involvement in defining and designing projects. Such engagement encourages research that results in evidence meaningful to patients and their care. One approach we have used successfully for the past five years is our Partnership for Innovation Program, which solicits ideas from clinicians who are then paired with investigators to collaborate on pilot studies. Ideas are selected based on their potential to improve quality, reduce cost, and be spread. To date, we have funded 31 individual projects based on innovations proposed by front-line providers, including planned concurrent evaluations to judge value and potential for spread.
Another key lesson is that learning systems must be nimble. Especially with advances in information technology, including the production of continuously generated and increasingly granular data, research must adapt its stride. The traditional pace of developing ideas, writing and executing grants, writing papers, and moving on to the next project, with too little attention to dissemination, will no longer do. A new model develops evidence synchronous with delivery systems, often working in the virtuous cycle of design, implement, evaluate, and adjust. This approach can be applied to system innovation and the adoption of new technology and treatments, and operate in real time. Rapid deployment with concurrent evaluation also helps learning systems abandon hoped-for innovations that do not pan out, a problem endemic in U.S. health care.
As Saunders and Smith point out, advances in information technology may raise increased privacy concerns. An ethical approach requires that we balance regulatory requirements for obtaining individual consent for the use of de-identified, continuously generated data with the benefits that the public will reap from generalizable knowledge that results from research based on reasonable access to such information sources. Resolving uncertainty in this domain is urgent.
Working together in authentic partnerships, we can create the important changes needed to advance learning health care systems aimed at discovering ways to provide the best care at lower cost.
ERIC B. LARSON
Executive Director
Group Health Research Institute
Seattle, Washington
Disturbing health data
Tom Plewes’ Real Numbers feature (“Shorter Lives, Poorer Health,” Issues, Spring 2013) offers a snapshot of the data compiled by a prestigious National Research Council panel. The data are so much more than statistics and numbers. They represent real human suffering, loss, and trauma. Whether from the gun violence that dominates the lives of too many communities today, or a result of the outrageous monthly costs of paying for medications to manage diabetes or hypertension for decades, or from the pain of grieving after the loss of a limb or a loved one; these data should trigger emotions that mobilize us to action. Unfortunately, emotions can paralyze more often than they mobilize. When I face our nation’s health disadvantage, I feel anger and extreme disappointment in our refusal to face the fact that this degree of suffering is needless. As a nation, we could shift from an overmedicalized culture to one that promotes health and well-being in our communities by deciding to create the “social conditions or determinants of health.” Becoming a nation that experiences better health outcomes would require ensuring access to quality, nutritious, affordable food for all, as well as more affordable housing, transportation, and education. Health would be supported by more equitable employment opportunities that pay a living wage. Reducing inequality would reduce associated stress and allostatic loads, thereby lowering the risk of many stress-related diseases.
The data alone should serve as a wake-up call for policymakers and for the public about the future health and viability of our nation. The fact that we spend more on medical care than our peer nations and still have worse health outcomes should prompt a re-examination of U.S. health-related policies and government expenditures. We spend less on social policies that support overall well-being than our peer nations who have significantly better health outcomes. The irony is that most Americans still believe that we have the best health care in the world. The idea of a “U.S. health disadvantage” is not widely known.
“Shorter Lives, Poorer Health” makes it clear that the U.S. health disadvantage is not limited to low-income or to minority communities alone. This nation, as a whole, is facing a major crisis in the premature loss of life and the disability of too many of our citizens under age 50. What does losing so many productive days and years of life mean to our future economy, to our national security, and to the U.S. capacity to compete on a global scale?
The full report calls for a comprehensive national communications campaign to raise the public’s awareness about our nation’s health disadvantage. Tom Plewes’ article is an important step toward broader communication of the report’s findings. If we fail to move toward creating healthier communities and providing the social infrastructures needed to promote and sustain health, the demands for health care will far outpace our care delivery systems’ capacity to respond. That is a frightening inevitability, indeed.
GAIL C. CHRISTOPHER
Vice President for Program Strategy
W. K. Kellogg Foundation
Battle Creek, Michigan
DISCOVERY-RESEARCH IS ABOUT CREATING NEW KNOWLEDGE ABOUT THE NATURAL WORLD. INVENTION-RESEARCH IS ABOUT CONSTRUCTING NEW ARTIFACTS. OUR MODEL PLACES BOTH TYPES OF ACTIVITY ON AN EQUAL FOOTING.
Fuel cell future
As pointed out by Noriko Behling in “Making Fuel Cells Work” (Issues, Spring 2013), “fuel cells are singularly remarkable in their potential” for efficiently converting chemical energy to electricity. Moreover, they are also unique in their ability to address all six of the key energy strategies of the recent U.S. Department of Energy (DOE) Quadrennial Technology Review. As such, they fully warrant the proposed National Fuel Cell Development Project to spur transformational innovation in this critical high-efficiency technology. However, if begun, the program must focus on driving the technology to higher system efficiency and lower capital cost with the currently available fueling infrastructure.
Unfortunately, fuel cells have been linked programmatically to a hydrogen economy, through the DOE’s EERE Hydrogen and Fuel Cells Program, creating three grand challenges: (1) develop reliable, low-cost, protonexchange—membrane fuel cells (PEMFCs); (2) develop portable H2 storage; and (3) develop and deploy an H2 production and distribution infrastructure. The tremendous infrastructural cost of creating the latter has perceptually relegated fuel cells to a “future technology” and resulted in a drastic reduction in funding by the DOE in favor of vehicle electrification.
In contrast, the lesser-known solid oxide fuel cells (SOFCs) are fuel-flexible, capable of operating on both conventional fuels (such as natural gas and gasoline) and future alternative fuels (such as H2 and biofuels) and thus only have one grand challenge: Reduce the operating temperature and cost. Unfortunately, as pointed out in the article, SOFCs have been programmatically relegated by the DOE Fossil Energy SECA Program to use in large-scale electric power production from coal, when in fact smaller-scale distributed generation with natural gas is a more attractive market for SOFC manufacturers.
This stovepiping within the DOE by fuel type and application has impeded technological progress and commercial success. The vast majority of funding has gone to address the three grand challenges of a hydrogen economy rather than focusing exclusively on advancing fuel cell technology itself. Moreover, although SOFCs are a technology that doesn’t require a hydrogen economy, the primary program that supports their development (SECA) had its budget for them zeroed out in the administration budget request for three years in a row.
Finally, the growing abundance of domestic natural gas provides tremendous potential for the U.S. economy, and it is incumbent on us to use this resource as efficiently as possible. Fuel cells are unique in this regard, and a National Fuel Cell Development Project should focus on advancing the technology that is most capable of operation on this game-changing fuel.
ERIC D. WACHSMAN
Director, University of Maryland Energy Research Center
William L. Crentz Centennial Chair in Energy Research
University of Maryland
College Park, Maryland
Climate engineering research
Jane C. S. Long and Dane Scott (“Vested Interests and Geoengineering Research,” Issues, Spring 2013) argue rightly that work must start now on the governance of research on climate engineering (CE), an issue that is likely to pose severe environmental and geopolitical challenges as the slow-motion debacle of climate change unfolds. After cataloging individual motives that may obstruct rational and impartial policymaking (and veering a little close to exhortations not to act on them), they advance several proposals for the governance of CE research. A few of these, such as transparency about research aims and results, public research funding, independent advisory bodies, and public consultation, are sensible and widely supported, albeit a little underspecified, when the devil is in the details. I focus on two proposals that hold more interest and more potential difficulty.
First, they propose that publicly funded research should generate no private intellectual property(IP) but do not propose prohibiting privately funded research, nor barring private IP arising from it. It is clear why they do not try to prohibit private funding: This would pose grave problems in defining and enforcing the boundary of what is prohibited. But their proposal could face serious difficulties if investors foresee large commercial opportunities in CE. Research might then split into two streams, with activities thought to promise valuable innovations funded privately and the rest funded publicly. Such a two-track research program, with strong selection pressure, may not advance the authors’ aims of keeping legitimate public control over key information about capabilities and risks and generating attendant public trust in decisions about whether, when, and how to develop or deploy CE capabilities.
Second, the authors struggle at a few points with the serious problem of how to organize research and craft incentives to attract the best minds but not tilt the playing field either to any particular approach or to a favorable bias toward CE overall. They worry, appropriately, that incentives will favor technical successes and positive assessments, when the societal need is for clear understanding of both efficacy and risks, in the context of the total response to climate change—including diligent efforts to root out every problem, limitation, and risk of any proposed CE approach.
They sketch two responses: adversarial assessment via some adaptation of the red team/blue team approach used for military technologies that could not be discussed in the open literature; and a shift in program structure, away from purely investigatordriven research toward a “collaborative, mission-driven” model. They advance this last point quite tentatively, expressing concern based on the legacy of environmental harms of past mission-driven research programs, particularly military ones.
Adversarial CE assessment appears to be a highly promising idea, but unlike its military antecedents is fully compatible with evaluating CE approaches and risks in the open literature. Once sufficiently well-posed questions or technical proposals can be teed up for such an exercise (a nontrivial matter), it only needs someone to frame the questions and fund and manage the exercise. Far from requiring secrecy, the combination of intensive debate within the exercise and wide expert and public review outside it is likely to both improve the results and help build public trust.
The question of investigator- versus mission-driven research is more difficult, as the authors’ evocative but imprecise term “collaborative, missiondriven” suggests they recognize. Criticizing past mission-driven programs for environmental damage does not quite capture the problems, because those programs’ missions were defined exclusively in terms of technical performance and national security. Their environmental harms do not mean that they failed, but that their mission failed to capture all that was at stake in what they were doing; showing the importance, and difficulty, of properly defining the mission.
What would be the mission be for a CE research program, and how should it be defined? It clearly would include advancing understanding of the effectiveness and risks of identified CE approaches, but should it also include improving CE methods to make them more effective and less risky? This is not as obvious as it sounds. It is clearly the case under some conditions: for example, if climate-change risks were so severe and imminent that the need to deploy effective CE was widely agreed on. But under other conditions, “improving” CE capabilities could be destructive; for example, if it were clear that an advance in capability would sharply undermine prospects for reaching an effective global mitigation agreement (but how would we know that?), or if advances in CE capability were to allow precise regional tuning of effects, risking increased international tensions or suspicions.
One clear implication is that the “mission” of a CE research program cannot be defined without high-level political and democratic input (and hopefully some wisdom), and that any such definition would have to iterate, perhaps repeatedly, between political and scientific inputs. In the absence of some political convergence on goals for climate policy overall, attempts to define a mission for CE research may be not just premature, but risky.
EDWARD A. PARSON
Dan and Rae Emmett Professor of Environmental Law
Faculty Co-Director, Emmett Center on Climate Change and the Environment
University of California Los Angeles School of Law
In his reaction to our paper “RIP: The Basic/Applied Research Dichotomy” (Issues, Winter 2013), Neal Lane (Forum, Spring 2013) raised a few important issues to which we are pleased to respond. Lane’s thoughtful reading of our paper resulted in his agreement with our critique of the linear model and the discontinuity it represents with the actual practice of research. At the same time, he is rightly cautious about possible misinterpretations of our arguments for the restructuring of long-standing federal policy. We agree with Lane about the need for caution and provide two suggestions on how the discovery-invention model might be properly used in improving current federal policy.
We are in agreement with Lane about the necessity of funding fundamental studies in the natural and social sciences. The funding of such work is fully compatible with our understanding of the public interest, and such research exemplifies the best of the long-term viewpoint we advocate. It is for this reason that “discovery” is placed on an equal footing with “invention” in our model. Indeed, our empirical example of the 1998 Nobel Prize in Physics given for the fractional quantum Hall effect exemplifies this broader understanding of the public interest. It is our hope that a fuller consideration of discovery and invention will actually lead to increased funding, in both the natural sciences and engineering, than is currently the case.
Lane’s characterization of the discovery-invention model as an outcomesoriented model does not fully reflect our arguments. In our view, one of the primary failings of the basic/applied model is its assumed linearity that creates a false hierarchy between so-called basic and applied research. The discovery-invention cycle provides a much needed correction. As presented in our examples, discovery-research is about creating new knowledge about the natural world. Invention-research is about constructing new artifacts. Our model places both types of activity on an equal footing, thereby incorporating the inherent bidirectionality in the flow and development of knowledge. When it comes to setting priorities in federal science and technology (S&T) policy, use of the discovery-invention model should broaden the relevant decision matrix to incorporate possible future technologies and the development of novel processes and engineered materials, in addition to the importance of increasing knowledge about nature. It is our hope that the use of the discovery-invention cycle will lead to more integrative decisionmaking in which motivational goals are but one of many considerations.
We hope that consideration of our model will lead to the kind of initial experimentation that Lane calls for and that the uptake of some of these ideas will lead to a rethink of many of the dysfunctional elements of the current national S&T infrastructure, while preserving the very best aspects of publically funded science and engineering.
VENKATESH “VENKY” NARAYANAMURTI
Benjamin Peirce Professor of Technology
and Public Policy
Here in New Mexico in the 1970s, before the expansion of government programs and subsidies for renewable energy, there was great interest in the Sun and in the adobe brick used in construction for passive heating and cooling.
Unfortunately, we govern ourselves with great concern for financial elites but little for the public. The elites show less and less interest in the many now almost extinct nonelectric uses of the Sun. We have few clotheslines and need electric lights on all day in our shopping centers despite our usually sunny weather.
While ignoring traditional nonelectric uses of the Sun, we continue subsidizing solar power plants and wind generators. I wonder if Michael Levi (“The Hidden Risks of Energy Innovation,” Issues, Winter 2013) doesn’t find this same thing where he lives.
STEVE BAER
Zomeworks Corporation
Albuquerque, New Mexico
Time for a Government Advisory Committee on Geoengineering Research
Nobody likes geoengineering. But whether your basic response is revulsion or resignation, the idea is getting increasing attention, and we need to develop a better way of talking about it. The most prominent scheme, known as solar radiation management (SRM), would aim to reduce global warming by spraying aerosols into the stratosphere or whitening clouds, thereby reflecting more sunlight back into space. Even strong advocates of geoengineering research acknowledge the many risks involved. The physical risks include possible shifts in global precipitation patterns and increased droughts and floods in the world’s most vulnerable regions. The political risks include the possibility that geoengineering technologies will provide a welcome excuse to avoid difficult measures to reduce greenhouse gas emissions. And many see geoengineering as yet another expression of the same technocratic mindset that underlies modern industrialism and global warming itself. Moreover, the mere prospect of geoengineering is a profound indictment of decades of failed efforts to reduce greenhouse gases. No wonder that discussing it has long been taboo.
And yet reasonable people disagree about what to do about it. With regard to geoengineering research, some say it shouldn’t be conducted at all. Others argue that research should be limited to computer modeling and laboratory studies. Some insist that small-scale deployment is necessary to develop technologies that could be used in a climate emergency, such as melting Arctic permafrost. With regard to policy, some advocate self-regulation by scientists, others favor oversight by national governments, and others call for international treaties.
Reasonable people also disagree about the relevance of competing ethical frameworks. Should we embrace utilitarian cost/benefit analysis? Some analysts suggest that geoengineering would be far cheaper and more effective than reducing carbon-based energy production. Or should we emphasize basic moral principles? Some argue for cultivating a more humble relationship with nature or taking responsibility for past greenhouse gas emissions. Others say our first responsibility is to prevent catastrophic climate change by any means necessary. Or should we let “the people” decide, and if so, which people and through what mechanisms?
This vexing jumble of technical uncertainties and political disagreements is not going away any time soon. As climate change impacts become more pronounced, public pressure to adopt quick and easy remedies will grow. Indeed, government agencies in the United States and abroad have already funded geoengineering research, including modeling projects, climate strategy projects, and some climate research with applicability to geoengineering. Privately funded research is in full swing, and entrepreneurs have filed patent claims on prospective geoengineering technologies. In the coming years, poor countries with rising sea levels and growing demand for carbon-based energy may deem geoengineering an attractive option. Rich countries with powerful fossil fuel lobbies may well agree.
This situation raises a series of pressing questions for scientific governance. What kinds of geoengineering research should governments fund, if any? Who should oversee such research? What criteria should they apply? And how can we encourage international cooperation and understanding?
Many commentators focus on the immediate need for substantive standards, but this is only half the challenge: Such standards must emerge from trusted institutions and a transparent process. We believe that in the United States a standing government advisory body would provide a critical focal point for policy formation around geoengineering research. Such a body has been proposed by a task force of the Bipartisan Policy Center and others. What such a body should look like and how it should be established remain open questions. This article proposes design characteristics, membership, and key functions of a geoengineering advisory body for promoting societal discussion and governance of geoengineering research.
Nongovernmental initiatives and the UK SPICE experiment
The oversight of geoengineering research has been addressed by several recent nongovernmental initiatives. In March 2010, the Climate Response Fund organized a meeting with over 150 experts from diverse fields in Asilomar, California, to develop norms and guidelines for geoengineering research. In the same month, the Royal Society, the Environmental Defense Fund, and The World Academy of Sciences founded the Solar Radiation Management Governance Initiative (SRMGI), which has organized deliberative meetings in the United Kingdom, India, Pakistan, Senegal, Ethiopia, China, and South Africa. Nongovernmental organizations have also produced thoughtful reports on the topic (see the recommended reading). These efforts have brought analytical clarity and public attention to key issues, but they have not been integrated into governmental policymaking.
The most ambitious effort by a national government to confront the challenges of funding and governing geoengineering research has been in the United Kingdom, and the results are instructive. In 2010, three UK research councils funded the Stratospheric Particle Injection for Climate Engineering (SPICE) project, which included a small outdoor geoengineering study. The plan was to model a SRM deployment by spraying 150 liters of water from a balloon into the atmosphere through a 1-kilometer hose.
Although the SPICE project sailed through university research oversight procedures, UK funding bodies required a “stage gate”: an extra review by an independent panel of scientists, social scientists, and a member of a civil society organization. As part of this process, the panel worked with SPICE scientists to bring the work into accordance with norms for “responsible innovation.” Social scientific research on public dialogue and engagement attempted to assess societal views on the experiment and geoengineering more generally. The experiment carried no significant physical risks, and yet it provoked a flood of criticism by civil society actors and significant debate in the United Kingdom and abroad.
Political controversy over SPICE hinged on a number of issues. First, a coalition of international environmental groups and other nongovernmental organizations (NGOs) claimed that the experiment circumvented international policy discussions that were ongoing. Second, the choice to investigate a deployment gadget, and not the physics of underlying natural systems, led many to see this as the wrong experiment at the wrong time. Third, after the project was approved, it was discovered that an investigator and others involved in the project had submitted a patent application on the experimental mechanism. This raised concerns that profit motives might be driving the research and that commercial interests might control the development and use of a potentially world-changing technology. As debate sharpened, UK funders postponed the project on the recommendation of the stage-gate panel in September 2011. Eight months later, the principal investigator pulled the plug on the balloon experiment, while continuing other aspects of the project.
SPICE has so far turned out to be less a physical experiment than an experiment in governance. The way the balloon experiment was born, debated, and died illuminated key questions concerning the control of research and the substantive standards that should apply to it. The stage gate had a messy, ad hoc character that scientists saw as a difficult moving target. On the other hand, it opened an important space for public dialogue, norm formation, and social learning.
Many in the United Kingdom and elsewhere agree that a trusted oversight framework should be established before further outdoor geoengineering research. But how can this be achieved in a way that is acceptable to stakeholders and the public? New institutions are necessary for creating a platform for oversight and learning in an evolving field, and for providing practical advice as public funders, such as the National Science Foundation, contemplate geoengineering research programs.
The development of a national advisory committee is a promising idea in this context, and there are useful models. The U.S. President’s Council on Bioethics, established by George W. Bush, is one instructive precedent. Many liberal bioethicists criticized the council for its conservative orientation, often neglecting its important procedural innovations. Whereas most government bioethics councils in the United States have focused on providing specific policy recommendations, the President’s Council explicitly sought to foster public deliberation. The council’s charter gave it a diverse set of tasks: “advise the President,” “undertake fundamental inquiry,” “explore specific ethical and policy questions,” and “provide a forum for a national discussion.” In its work on stem cells, for example, the council did not insist on consensus but laid out different positions on the moral status of embryos and how that could affect stem cell research and policy. President Bush’s stem cell policy didn’t satisfy many scientists, but his council promoted public discussion of moral disagreements that arguably laid the groundwork for compromise down the road.
Necessary characteristics of a geoengineering advisory committee
The overarching goal of an advisory body on geoengineering should be to recommend principles, policies, and practices that help make research more safe, ethical, and publicly legitimate. But the procedures of such a body will be just as important as the content of its recommendations, and both will receive intense public scrutiny. An advisory committee on geoengineering will be more effective and legitimate to the extent that it is independent, transparent, deliberative, publicly engaged, and broadly framed. We discuss each of these qualities in turn.
• Independent. The authority of expert advice depends on the public perception that it has not been unduly influenced by professional, economic, or political interests, including the interests of researchers, public officials, or the sponsoring agency itself. An advisory body that is seen as merely echoing the views of its sponsors would have little public credibility. In particular, an institution charged with monitoring and assessing research on geoengineering must not become, or be seen as becoming, an advocate for the deployment of geoengineering technologies. This requires including people with no direct involvement in geoengineering research.
Of course, expert advisory bodies cannot remain entirely insulated from the controversial issues they address, and it would be impractical to exclude everyone with a perceived interest in either promoting or opposing geoengineering research or deployment. Many of those most knowledgeable about geoengineering also have personal, professional, or political stakes in the issue. Committee independence should be understood, therefore, not with respect to individual committee members but rather as an institutional feature of the committee as a whole. An advisory body is independent when diverse perspectives and interests balance each other out, so that no particular view is able to dominate the others. This approach is echoed in the advisory committee guidelines of the National Academy of Sciences, which allow a fairly high degree of potential bias among committee members, as long as they are not entirely committed to a certain position. The best way to ensure independence is by appointing a balance of perspectives representing diverse disciplinary, experiential, geographic, and political orientations.
• Transparent. One way to help establish the independence and legitimacy of advisory committees is to make their proceedings publicly accessible and transparent. As Jane Long and Dane Scott have argued in these pages, sunshine is a good disinfectant for lurking vested interests. Further, citizens are more likely to trust advisory processes that remain open to public scrutiny. To be sure, transparency alone is never enough: Providing public access to information on geoengineering research will do nothing unless those who are concerned and affected actually have the means to make use of such information. Additionally, in some cases, excessive transparency requirements may make it difficult for committee members to openly discuss controversial issues. Generally speaking, however, secrecy breeds distrust, and advisory committee procedures should be as transparent as possible.
• Deliberative. The authority of expert advice depends not primarily on the credentials of advisory committee members but on the reasons and arguments with which they defend their views. Indeed, given that advisory committees have no decisionmaking power, whatever authority they have rests primarily on their persuasive capacity. Advisory bodies are thus deliberative in a double sense; ideally, the members deliberate among themselves, and they inform and promote deliberation among policymakers and the general public. Although advisory committee members may have strong views on matters of either fact or value, they should remain open to alternative views and seek consensus.
Of course, when it comes to controversial issues such as geoengineering, characterized by both moral disagreement and scientific uncertainty, a reasonably diverse advisory body is unlikely to reach consensus on many issues. Moreover, excessive pressure to reach consensus may result in the suppression of minority views. It is important, therefore, that advisory committees balance the deliberative goal of consensus against the political need to represent diverse perspectives. This can be done in part by preparing reports that outline a range of policy options, accompanied by the best reasons for each option, rather than insisting on a single consensus recommendation. Similarly, an advisory committee on geoengineering should take care to clearly and publicly explain the technical and political uncertainties associated with different possible courses of action.
The President’s Council on Bioethics pursued its deliberative mandate through a variety of means: It solicited extensive public input, included majority and minority perspectives in its reports, outlined a range of policy options on various issues, and produced publications intended for a broad audience.
• Publicly engaged. Most advisory committees address themselves primarily to policymakers, but controversial public issues such as geoengineering require a different approach. Geoengineering, especially solar radiation management, involves a wide range of moral disagreements and scientific uncertainties, and it potentially affects people around the world. In addition, the relevant technical, political, and environmental conditions are in considerable flux. Given this context, efforts to restrict the participants in decisionmaking to a narrow group of elites are bound to fail. SPICE was a case in point.
Potential avenues for public engagement include holding public hearings at diverse locations, publishing accessible reports and educational materials, and fostering contacts with mass media outlets. An advisory committee cannot be expected to generate societal consensus on a complex issue such as geoengineering, but it may be able to promote well-informed debate and compromise.
• Broadly framed. Technologies for SRM raise numerous safety concerns, especially with regard to the potential impact on global precipitation patterns, which could have disastrous consequences for vulnerable populations. Such concerns also apply to research that could lead to deployment, as well as research occurring on a scale large enough to qualify as deployment. Although commentators often call for balancing the efficacy of geoengineering technologies against risks to public safety, it would be a mistake to limit public discussion to questions of safety and efficacy. Much of the public concern about geoengineering rests on more fundamental questions about global inequality and the human relationship to nature. If global warming is the result of humans treating nature as a mere resource to be manipulated at will, does geoengineering represent more of the same? Will it offer a way for rich countries to avoid their historical responsibility for the problem? An expert advisory body cannot provide definitive answers to such questions, but it can facilitate constructive public engagement with them.
III. Who should sit on a national advisory committee?
Given the many controversies involved, the membership of an advisory committee on geoengineering is likely to receive considerable public scrutiny. Membership balance will be crucial for both scientific and political reasons. Scientifically, addressing complex issues such as geoengineering depends on multiple disciplines. Researchers with different disciplinary training and commitments can address different aspects of the issue and identify each other’s blind spots. Politically, including diverse perspectives promises to enhance legitimacy, insofar as it reassures outsiders that no single perspective or interest has dominance. Of course, exactly which perspectives to include often becomes controversial. Indeed, interest groups have occasionally filed legal suit to be represented on federal advisory committees, which under the U.S. Federal Advisory Committee Act must be “fairly balanced” in terms of the points of view represented and the functions performed.
A geoengineering advisory body should include members representing a few key categories:
• Experts from the natural sciences, social sciences, and humanities. As noted previously, a geoengineering advisory body should include members with diverse views and interests, including both proponents and critics of geoengineering research. And even if we set aside the interests of individual researchers, every scientific subfield has biases associated with its particular theories and methods. Therefore, illuminating all sides of a complex issue such as geoengineering requires balanced participation across a range of scientific subfields. Moreover, governance discussions draw on not only the technical possibilities and effects of research and possible deployment, but also social and moral questions regarding the purpose and effects of experiments and the motives and goals of researchers. What norms are most likely to produce cooperation and effective compliance within the United States and across the globe? Will geoengineering undermine public support for climate mitigation and adaptation efforts? Addressing such questions depends in part on the social sciences and humanities.
• Experienced-based experts. Not all expertise involves disciplinary credentials. Experts associated with environmental groups, business interests, or community organizations, for example, may have valuable knowledge that rests primarily on practical experience. Such experts are essential for effectively addressing the complex political challenges associated with geoengineering research.
• Representatives of potentially affected communities. Many government advisory committees include representatives of constituencies with a potential stake in the issue before the committee. Such representatives may be experts of one kind or another, but their expected contribution to committee deliberation rests in part on their familiarity with a potentially affected constituency. The potential impact of geoengineering on global precipitation patterns is likely to affect different populations in very different ways. A geoengineering advisory body should thus include people with knowledge and experience of diverse regions around the globe. Although the members of a U.S. government advisory committee are likely to reside in the United States, at least some members should have personal familiarity with other parts of the world, especially the poor countries most vulnerable to climate change.
• Representatives of diverse political viewpoints. The standard view of expert advisory committees as insulated from politics makes it difficult to explicitly consider the political views of committee members. Most people would rather insist that committee members leave their politics at the door, and of course committee members should not be partisan advocates. Geoengineering is not currently a partisan issue, and it would be valuable for an advisory body to maintain a nonpartisan status. But with regard to controversial issues such as geoengineering, the political views of committee members are bound to receive public scrutiny. Therefore, rather than avoiding consideration of the committee members’ political views, it makes sense to seek a balance of political orientations. An advisory committee is likely to enjoy greater public legitimacy to the extent that it includes members with diverse political orientations.
TABLE 1
Membership:
Specific member recommendations
Natural scientists
• Researchers currently involved in geoengineering projects
• Other climate scientists
• Ecologists and environmental scientists
Social scientists and humanists
• Environmental and regulatory law experts
• International legal scholars
• Political scientists, international relations scholars, and policy analysts
• Science and technology studies scholars
• Science policy experts
• Philosophy and ethics scholars
Academic research administrators with expertise in emerging technologies
Business and military leaders
Environmental NGOs
• Environmental NGOs with climate change focus
• Environmental justice and equity organizations
Former government officials with experience in diplomacy and administration
What should a national advisory committee do?
Such a national advisory committee would not regulate directly but provide detailed advice to the Executive Branch and government agencies on an oversight framework before the conception and funding of geoengineering research. Guidelines could be implemented either as a voluntary code or through formal regulations. Granger Morgan, Robert Nordhaus, and Paul Gottlieb, –in the previous issue of this journal, –outlined a set of policies that should be in place before the development of an SRM research agenda. Here we build on their suggestions and also outline longer-term functions.
• Scope of application. Part of the challenge of producing a clear and credible governance framework is determining the scope of application; that is, defining what kinds of experiments are even subject to review as a geoengineering experiment. The Royal Society defines geoengineering as “the deliberate large-scale manipulation of the planetary environment to counteract anthropogenic climate change.” But this does not sufficiently clarify the issue. Does this definition apply to the activities’ effects, intentions, or both? Also, does it include research on familiar measures intended to affect climate, such as painting roofs white or reforestation?
• Experiment categories for triaging oversight. As others have frequently argued, a pressing governance priority should be to demarcate a first-tier category of research that poses little or no concern, perhaps including computer modeling, laboratory experiments, and/or very small outdoor experiments that pose no significant risks and require no government oversight. An advisory committee would be well positioned to make such recommendations and also to articulate a tier of clearly prohibited research, such as for outdoor SRM research of a given size. The process of setting these tiers of concern and developing a corresponding oversight approach should be informed by public outreach and engagement activities.
• Values. There will be a temptation to divorce these line-drawing activities from the explicit definition of values, principles, and priorities that necessarily underwrite them. But one of the most important functions of the advisory committee should be to promote public deliberation and debate about values and goals. A good place to start is the Oxford Principles, a code of ethics for geoengineering governance developed in 2011 by a team of Oxford academics. Another is the list of principles developed by the Bipartisan Policy Center task force. Drawing on environmental ethics, bioethics, and existing international law, this discussion of values should encourage open-ended deliberation.
• Intellectual property. As part of a framework for research oversight, the advisory committee should develop recommendations on intellectual property and research transparency. Intellectual property and financial interests can shape the conduct and direction of research. As the SPICE experience shows, it can also undermine public trust. Accordingly, as part of an oversight framework, an advisory committee should develop a range of possible options for the disclosure and management of financial and other conflicts of interest, as well as for how intellectual property rights arising from federally funded research might best be allocated.
• Transparency. An advisory committee should recommend requirements for public notification and transparency regarding research proposals, funding, procedures, data, publications, or all of the above. Such requirements should specify when and how the public should be notified and whether they pertain to privately funded research. The committee should also include annual or biannual reports on the science and politics of geoengineering, assessing both publicly and privately funded research activities around the world.
• International communication and coordination. A final crucial activity of a national advisory committee will be to engage with the international community of political and scientific actors, many of whom have already done serious thinking about governance. Because some geoengineering technologies such as SRM would involve large-scale transboundary effects, related research activities necessarily have international implications. International coordination is especially important in light of the possibility that a single country could undertake SRM unilaterally. Many nations have already begun, or are likely to begin, programs of research, raising challenges of trust and cooperation.
A national advisory committee will be well positioned to facilitate connections, build norms, and promote cooperation across national borders. It should tap into existing international networks of nongovernment actors who have laid important groundwork, such as the SRMGI initiative mentioned previously.
Institutional options
There are a number of plausible options for establishing a government advisory body on geoengineering. Whether and how the U.S. Federal Advisory Committee Act (FACA) applies to these options will be important for understanding the regulatory restraints on the composition and activities of such a body. Choices for such a body, therefore, range from more to less formally regulated.
Creating a new committee to provide direct advice to federal officials on geoengineering research would bring the greatest degree of transparency, publicity, and formal legitimacy. It would also be subject to FACA, which applies to “any committee, board, commission, council, conference, panel, task force, or other similar group,” which is established by statute, the president, or one or more agencies, and which is “utilized…in the interest of obtaining advice or recommendations for the President or one or more agencies or officers of the Federal Government” [5 U.S.C. Appendix § 3(2)]. As noted previously, FACA requires that advisory committee membership be fairly balanced. It also requires that committees meet only when convened by a designated officer of the federal government, and it includes various transparency requirements to facilitate public participation in the advisory committee process.
Alternatively, an existing FACA committee could be charged with providing advice on geoengineering research. Candidates for using existing committees include the President’s Council of Advisors on Science and Technology, the Presidential Commission for the Study of Bioethical Issues, and the U.S. Global Change Research Program’s Subcommittee on Global Change Research.
A less formal alternative would be to create a subcommittee or workgroup of an existing FACA committee. FACA committees can have advisory subcommittees and workgroups that are not subject to all the same formal procedural requirements as their parent committees. The activities of subcommittees are generally covered by the charter of the parent committee, and some agencies, such as the Centers for Disease Control, require that they adhere to the notice and open meeting provisions of FACA. If a subcommittee makes recommendations directly to a federal officer or agency, or if its recommendations will be adopted by the parent committee without further deliberations, then the subcommittee’s meetings must be conducted in accordance with all openness requirements. “Workgroups” can meet to gather information, conduct research, draft recommendations, and analyze relevant matters. They are not empowered to make any decisions, and recommendations must be funneled back through, and decided on by, a parent advisory committee or subcommittee.
The most flexible choice would be to seek independent input through established advice brokers such as the Bipartisan Policy Center or the National Academy of Sciences. Committees not actually managed or controlled by the federal government are not governed by FACA, which allows greater leeway in membership and procedures. We think such an option is sensible and workable so long as the design elements discussed above are given due attention.
Conclusion
Geoengineering research is not normal science. The research is characterized by high stakes and scientific and political uncertainty. It raises many red flags, especially in light of the checkered history of efforts to apply technological fixes to complex problems. And it animates larger issues at the heart of climate change politics, engineering ethics, and the problem of democratic governance in a technically complex society.
For these reasons, a technocratic approach to defining acceptable research will not fly, even more so if it is done in an ad hoc or opaque way. For one thing, the SPICE project indicates that this will not work. SPICE is an early indication of how moving forward is not just about funding science but governing it. And governing is not simply about finding the appropriate norms for conducting research, though this is critical, but also about developing trusted institutions. Given the need for public visibility and accountability, we think a governmental advisory body is an appropriate vehicle. In the short term, a national advisory committee, if designed according to the preceding considerations, could help create an effective and legitimate oversight framework. More important, over the long term, it could help establish a trusted architecture for making sound public decisions about this controversial issue.
Making Energy Access Meaningful
In a somewhat inconsequential meeting at the United Nations (UN) in 2009, Kandeh Yumkella, then Director-General of the UN Industrial Development Organization and UN Secretary-General Ban Ki-moon’s informally assigned “energy guy,” noted something obvious and profound: that “the provision of one light to poor people does nothing more than shine a light on poverty.” Yet much of an emerging discussion on the critical importance of global energy access as a pathway out of poverty continues to focus on what are, in effect, “one-light” solutions. In this essay, we seek to help clarify the challenge of energy access, expose assumptions that are informing policy design in the development and diplomatic communities, and offer a framework for future discussions rooted in the aspirations of people around the world to achieve energy access that is compatible with a decent standard of living.
Our distinctly uncomfortable starting place is that the poorest three-quarters of the global population still use only about 10% of global energy—a clear indicator of deep and persistent global inequity. Because a modern energy supply is foundational for economic development, the international development and diplomatic community has rightly placed the provision of modern energy services at the center of international attention focused on a combined agenda of poverty eradication and sustainable development. This priority has been expressed primarily in the launching of the UN Sustainable Energy for All initiative (SE4All). Still, areas of tension and conflict in such an agenda demand further attention, particularly in relation to climate change, as we discuss later in this essay.
Compounding the difficulty of decisionmaking in such a complex space is that the concept of “energy access” is often defined in terms that are unacceptably modest. Discussions about energy and poverty commonly assume that the roughly two to three billion people who presently lack modern energy services will only demand or consume them in small amounts over the next several decades. This assumption leads to projections of future energy consumption that are not only potentially far too low but therefore imply, even if unintentionally, that those billions will remain deeply impoverished. Such limited ambition risks becoming self-fulfilling, because the way we view the scale of the challenge will strongly influence the types of policies, technologies, levels of investment, and investment vehicles that analysts and policymakers consider to be appropriate.
As Wolfram and colleagues observe in a recent study, “The current forecasts for energy demand in the developing world may be understated because they do not accurately capture the dramatic increase in demand associated with poverty reduction.” The point is that energy access is not an end per se; rather it is a necessity for moving to vibrant and sustainable social and economic growth. The lower the assumed scale of the challenge, the more likely it is that the focus will turn to incremental change that amounts to “poverty management,” rather than the transformational changes that will be necessary if we are to help billions climb out of poverty.
Old numbers
A first step to better understanding the scale of the energy access challenge is to ask how much energy is actually needed to enable poverty alleviation—a level we will term “modern energy access”? To answer this question we focus, for simplicity, on electricity services, rather than energy for heat and cooling or transport. Still, answering the question is not simple. World Bank data indicate that some countries with relatively low levels of access have high levels of electricity use, whereas some countries considered to have full access have extremely low average electricity use. This considerable spread in average annual household consumption levels at different levels of access makes comparing some of the existing analyses tricky.
Let’s turn to places that have modern energy access by any definition of the term, with essentially 100% of residents and the broader economy under full electrification. The average resident of the United States consumes about 13,400 kWh per year, with a large variation by state (for example, households in Maine consume about 40% of those in Louisiana). On average, Europeans generally consume considerably less energy than Americans. For instance, based on 2010 data, the average resident of Germany consumes about 7,200 kWh per year, with Swedes consuming about 15,000 kWh and Greeks about 5,200 kWh, and on the low end the Bulgarians at about 4,500 kWh, or about 60% of German and a third of U.S. levels. For comparison, the global average in 2010 was just under 3,000 kWh per capita per year, which is three-quarters of Bulgarian consumption, but of course this number is strongly skewed by the enormous concentration of energy use in the industrialized world as well as the large number of people with no access at all.
These numbers for the United States, Germany, and Bulgaria can be compared to the definitions of energy access that typically provide the basis for policy discussions and analyses. The International Energy Agency (IEA) is one of the world’s most influential analytical bodies on energy policy, and its flagship product, the World Energy Outlook, has played a leadership role for more than a decade in providing analysis and data of the energy access issues. It defines an initial threshold for energy access to be 250 kWh per year for rural households and 500 kWh per year for urban households, assuming five people per household. This equates to 50 to 100 kWh per year per person, or about 0.5% of that consumed by the average American or Swede and 1.7% of that of the average Bulgarian.
For its part, the IEA and the other organizations active on this issue have recognized that achieving energy access is a process, noting, “Once initial connection to electricity has been achieved, the level of consumption is assumed to rise gradually over time, attaining the average regional consumption level after five years. This definition of electricity access to include an initial period of growing consumption is a deliberate attempt to reflect the fact that eradication of energy poverty is a long]term endeavour.”
The World Bank presents a useful scheme for considering various levels of energy access, illustrating different tiers of access (Table 1). Still, even the highest level of access in the scheme, Tier 5, implies some 2,121 kWh per year per household of five people, or roughly 420 kWh per capita per year, which, at less than 10% of Bulgarian consumption, is still much lower than what typical energy services would imply in even the least energy-consumptive wealthy countries. More than a billion people lack even the minimal levels of access to electricity, and policy analyses, national plans, and projects must start somewhere. Still, achieving minimal levels of energy access is not to be confused with success in achieving goals of modern energy access. The sorts of policies that would make sense to get large numbers of people over a low and arbitrary threshold are very different from those that will underpin sustained growth in economies and consumption. Consider that we do not label people who live on more than $1 per day as having economic access and address policies toward achieving a $1.25 level, thus still leaving them desperately poor. Everyone understands that $1.25 a day is still not nearly enough. In energy, we often lack such conceptual clarity.
Adding to the challenge of talking clearly about modern energy access and a more realistic level of unmet energy demand in poor countries is the tendency in many analyses to discuss the issue in terms of household energy use. Energy access has links to all sectors of the economy. By focusing on household energy demand, other sectors of a growing economy can end up being ignored in critical power planning exercises and policies. Business and industry growth, for example, is severely constrained in many poor countries not only by a lack of access but also a lack of access to highquality services, meaning those that are reliable enough to meet the needs of private-sector enterprises, from hospitals to factories. Access to modern energy services across an economy, not just in the home, is necessary to sustain and support continued economic growth, a reality that must be accommodated in projections of future energy needs.
TABLE 1
Tiers of electricity service demand (World Bank, 2013)
USE OF ELECTRICITY SERVICES
If we aim too low, then there are risks not just in policy failure but in the opportunity costs of policy success. If more ambitious goals are to be achieved, then some attention must also focus on real transformational change. This type of change is often difficult to conceptualize and difficult to represent in most analytical models using traditional baseline or incremental growth approaches. But our analytical models should not limit our creativity and ambition, especially in light of the reality that many nations, such as Thailand, South Africa, Vietnam, and China, have experienced remarkable economic growth and expansion of truly modern energy access for large populations over relatively short periods of time.
New numbers
We now turn to the quantitative implications of moving toward much higher levels of assumed future energy demand for poor countries. As an example, consider the Obama administration’s recent announcement of a new “Power Africa” initiative, focused on increasing the electricity generation capacity of sub-Saharan Africa by adding 10 gigawatts (GW) of generation capacity in order to “double access to power.” Although such an initiative is to be applauded, placing it into a broader context can help to calibrate the level of ambition.
To raise the entire region of sub-Saharan Africa to the average per-capita electricity access available in South Africa (which in 2010 was about 4,800 kWh, similar to the level of Bulgaria) would require 1,000 GW of installed capacity: about the equivalent electricity of 1,000 medium-sized power plants and 100 times the capacity increase in the plan set forth by President Obama. This means that sub-Saharan Africa would need to increase its installed capacity by 33 times to reach the level of energy use enjoyed by South Africans. A recent study by Bazilian and others (2012) showed that even a less ambitious 10-fold increase, perhaps sufficient to provide full access but at relatively modest levels of electricity consumption, would require a 13% average annual growth rate in generating capacity in sub-Saharan Africa, as compared to a historical one of 1.7% over the past two decades. When looked at from the perspective of energy access as the concept is understood in North America and Europe, the magnitude of the energy access challenge is starkly revealed.
Still another perspective is provided by the International Institute for Applied Systems Analysis in its 2012 Global Energy Assessment, which tracks the historical expansion of energy access in several countries. In 1920, only 35% of Americans had energy access, and full access was achieved in the mid-1950s, a period of about 35 years. In contrast, Mexico, which was at about 35% access in 1930, has yet to reach the 100% mark. China went from 35% in 1970 to nearly 100% by about 2000, reflecting a very fast rate in a very large nation. India is following a much shallower trajectory, going from about 25% in 1980 to 65% in 2010. How fast and how far can truly modern energy access occur under an approach focused on rapidly expanding access to truly modern levels? This is the sort of question where researchers might productively direct their attention.
Accelerating a transition to a radically different, and inclusive, energy system is clearly a generational challenge and provides a just and consequential rationale for much greater attention to innovation in energy systems. A first step in that transition is to properly understand the scale of the challenge. With a sense of scale appropriate to energy access commensurate with the organization of modern economies, we are then in a position to discuss the possible costs of achieving such ambitious goals, recognizing that any such discussion is laden with assumptions about economics, technologies, and politics but also that history is replete with examples of nations moving rapidly to achieve greatly increased levels of access in the context of rapid economic growth.
What sorts of investments might be necessary for achieving modern energy access? Based on recent work done by Bazilian and colleagues, it would cost about 1 trillion dollars to achieve the IEA 2012 World Energy outlook definition of total global access—rising to 750 kWh per capita for new connections by 2030—and 17 times more to achieve a level of worldwide access equivalent to that in South Africa or Bulgaria. This massive difference in estimated costs, which is probably insensitive to the precise accuracy of either number, places a value on the ambition gap that results from the difference between a poverty management approach to energy access and one that takes seriously the development aspirations of people around the world. Of course, it is not just cost that changes in the face of such aspirations, but also the sorts of institutions, technologies, infrastructure, policies, and other systems required to support broad-based energy services.
Climate interactions
Most readers will have already recognized that our discussion has significant implications for the question of climate change. Former NASA scientist James Hansen expressed his view of the issue with typical candor, when he said, “if you let these other countries come up to the level of the developed world then the planet is done for.” For the most part, however, the ambition gap has kept this uncomfortable dilemma off the table. If one assumes that billions will remain with levels of energy consumption an order of magnitude less than even the most modest definition of modern access, then one can understand the oft-repeated claim that universal energy access can be achieved with essentially no increase in the global emissions of carbon dioxide.
For example, the projections of the IEA under its “Universal Access Scenario” for energy consumption and carbon dioxide emissions show minimal consequences to emissions and consumption, but these projections essentially reflect a “poverty maintenance” level of energy service provision. Emissions increase by such a small amount because new energy consumption increases by a very small amount.
Conflicts between climate and energy priorities deserve a deeper and more open airing in order to help better frame policy options, including the difficult question of tradeoffs among competing valued outcomes. The issues are playing out right now but remain largely unacknowledged. For instance, under U.S. Senate Bill S.329 (2013) the Overseas Private Investment Corporation, a federal agency responsible for backstopping U.S. companies that invest in developing countries, is essentially prohibited from investing in energy projects that involve fossil fuels, a policy that may have profound consequences in places such as sub-Saharan Africa that are seeking to develop oil and gas resources to help alleviate widespread energy poverty. At the same time, a different U.S. federal agency, the U.S. Export-Import Bank, helped fund a 4.9-GW coal plant (Kusile) in the Republic of South Africa. The coal plant will help serve both industry and households that currently lack access. These simultaneous interventions appear incoherent. Making such issues more transparent and opening them up to debates with multiple stakeholders with multiple values and success criteria offers the promise of enriching the array of policy options on the table.
The UN has attempted to square this circle of climate and energy through the phrase Sustainable Energy for All. Still, because value judgments must be made and priorities established, the UN initiative has explicitly stated a technology-neutral principle and given primacy to national decisionmaking, and implicitly has made the goal of universal energy access a first among equals of the three sustainable energy goals (the other two relating to renewable energy and energy efficiency). In practice, however, as we have emphasized, the tradeoffs involved in policies related to climate and energy have often received less than a full airing in policy debate.
The course of development followed by virtually all nations demonstrates that people around the world desire a high-energy future. Our plea is that we begin to recognize that fact and focus more attention and resources on positively planning for, and indeed bringing about, that future. Achieving universal modern energy access will require transformations; in aspirations, but also, for example, in technological systems, institutions, development theory and practice, and new ways to conceptualize and finance energy system design. Being clear about what modern energy access means and applying that clarity to the policy discussions galvanized by the 2014–2024 UN Decade of Sustainable Energy can create a foundation for making huge strides in bridging the global equity gap not just in energy but in the new wealth, rising standard of living, and improved quality of life that modern energy access can help to bring.
Ultimately, a focus on energy access at a low threshold limits our thinking and thus our options. Adopting a more ambitious conception of energy access brings conflicting priorities, as well as the scale of the challenge, more clearly into focus and makes hidden assumptions more difficult to avoid. Now more than ever the world needs to ensure that the benefits of modern energy are available to all and that energy is provided as cleanly and efficiently as possible. This is a matter of equity, first and foremost, but it is also an issue of urgent practical importance. Economic and technological challenges are hard enough; let us not add a failure of imagination to that mix.
Recommended reading
What Shortages? The Real Evidence About the STEM Workforce
Computer science graduates in 1998 often looked to Microsoft as the hottest employer in town—and as it turned out, for good reason. Within four years of joining the company, they would be part of a team that ushered in an operating system used the world over and become millionaires along the way. By 2002, a future with the company brought a good salary (but not instant millions) and membership on a team that not only could not develop the next New Thing but couldn’t match the achievements of its competitors.
Middle age had crept up on Microsoft and other information technology (IT) companies just a quarter century after the dawn of the microcomputer era. Established IT companies found that they could no longer attract the young, bright, hot graduates from the top universities, who instead flocked to new startups. Feeling the panic of rapidly rising salaries during the dot-com bubble and seeing the young upstart companies lure away the best talent, the IT industry worried about where it would find its future workforce. And thus began the drumbeat of “talent shortages,” supported by a cascade of reports and echoing such cries of earlier decades, but attached to the broader fears of a nation that thought it was losing its dominance in the world.
Today, most policymakers and industry leaders are united in their belief that the United States faces a high-tech talent crisis. The belief has become a central theme in discussions in Congress and the Executive Branch on immigration bills (and attending policies on bringing in high-skill guest workers), on education and the causes of economic stagnation domestically, and on the nation’s competitive position globally. This enduring perception of a crisis of supply might logically lead to some obvious questions. Why is the market not producing graduates in science, technology, engineering, and mathematics—the STEM fields—who would be sufficient in quantity and quality to meet demand? Why does this particular labor market fail to operate as it should?
But there are better questions to ask. Why is the widely accepted view of shortage at odds with study after study that has found the U.S. science and engineering supply to be strong and improving? And why are policymakers and industry leaders offering proposals that go against this solid body of evidence?
STEM market and the economy
Before offering a more detailed analysis, it is worthwhile to examine two widely cited claims about shortages: the headline-grabbing statement by the former head of Apple, Steve Jobs, to President Barack Obama about an engineering shortage, and the recent claim by the president’s Jobs and Competitiveness Council that the economy needs to produce an additional 10,000 engineers each year to address a shortage and thereby spur innovation to jump-start the lackluster jobs market and economy.
At a meeting in February 2011, Jobs told the president that Apple would have located 700,000 manufacturing jobs in the United States instead of China if only the company had been able to find enough U.S. engineers to support its operations. Apart from there being no indication that Apple actually tried to search for engineers, or that it actually has a problem attracting engineers, some simple math suggests that the plausibility of this claim should be reconsidered.
If Apple located its manufacturing in the United States and paid the national average for electronics production worker wages, it would cost the company about $42,000 per worker per year. In China, Apple’s contract manufacturer, Foxconn, pays workers $4,800 per year. Thus, manufacturing in the United States would cost Apple an additional $26 billion each and every year, an amount that is slightly more than the company’s reported net profit for 2011. Even if the company was willing to sacrifice its entire profit for an act of patriotism, would it have been hamstrung by an engineering shortage? Apple surely could have outbid other companies for the 8,700 industrial engineers it said it needed, or it likely could have just matched wages and attracted them because of its reputation and perceived “cool” factor. It does not appear, then, that it was an engineering shortage that led to Apple’s offshoring decision.
The suggestion by the president’s Jobs and Competitiveness Council that the nation’s economy is hampered by a shortage of engineering graduates also earns doubt. To evaluate this claim, it is only necessary to turn to another of the president’s councils, the Council of Advisors on Science and Technology. According to its analysis of the engineering workforce, the nation is currently graduating about 25,000 more engineers every year than find work in that field. Moreover, it seems that some companies suffer from a surfeit of technology workers. In September 2012, Hewlett Packard announced that it planned to lay off 15,000 workers by the year’s end, reaching a total of 120,000 layoffs over the past decade. Or consider General Electric’s recent relocation of its 115-year-old Xx-ray headquarters from Wisconsin to Beijing, after earlier expansion of its corporate R&D labs in India and China. These companies represent the general trend, in industry after industry, of locating STEM-intensive activities offshore while shrinking their U.S. workforces. IBM, for example has reduced its U.S. workforce by 30% and now has four times more offshore than domestic employees. It is thus a rather curious proposition that companies are seeking more STEM employees at the same time that they are laying off huge numbers of STEM workers and increasing the employment of offshore STEM workers who earn a fraction of U.S. salaries. It is not clear what producing another 10,000 engineers would do, especially as fewer engineering graduates find engineering jobs and salaries are flattening for all but a few fields.
These examples illustrate the quandary of trying to understand the STEM shortage debates. On one hand, the claims of shortages and of an apparent failure of the market to produce enough workers do not appear to be supported by the available evidence. On the other hand, authoritative voices on shortages and the constant repetition of the claims are proving compelling enough for policymakers. Assessing the supply of—and demand for—STEM workers requires a broader look at the context and evidence.
Brief history of skill shortages
At the turn of the 20th century, U.S. industrialists were faced with skill shortages. The robber barons, facing a paucity of tile makers and other highly skilled craftsmen, had to bring in European tradesmen as guest workers to construct their mansions. Henry Ford also faced a skills shortage when developing plans to produce automobiles in Michigan. Automobile production at the time depended on highly skilled craftsmen, bicycle builders, for the most part, to build handcrafted and expensive vehicles. Unable to find skilled workers in the nation’s interior or to attract them to the region, Ford considered how he could build a high-technology product with workers drawn from the farms, lacking craft or industrial skills. His solution–the production line–changed the face of production the world over, although its success also required national networks of technology support services provided by shade-tree mechanics who learned auto repair by tinkering with engines in their yards at home.
At the turn of the current century, high-technology industries were facing many of the same dilemmas and choices of the past: how to develop a skilled workforce, and how to have highly engineered products produced and supported more widely and at lower cost. For its part, the IT industry was composed of several different segments: a product market that depended on a high-skill craft production model and a large services market that was a mix of legions of programmers performing routine development and higher-skilled analysts and custom systems and services developers. During the 1990s, demand increased across the IT industry, as new products were developed, PCs proliferated, and inexperienced users needed ever greater levels of support.
Toward the end of the 1990s, the demand for programmers was exacerbated by the Y2K crisis, which necessitated the modification of existing software systems or the transition to new enterprise-wide software packages (or both) that required extensive customization, debugging, implementation, and support across entire organizations. Along with these challenges, the industry faced steeply increasing salaries, further exacerbated by the emergence of the dot-com bubble, which had distorted this labor market by the lure of turning its workforce into nearly instant millionaires and creating a surge in labor demand that was not sustainable over the longer term. Genuine panic spread beyond the IT industry as forecasters, caught up in the enthusiasm of the “new economy,” predicted vast expansion of the IT industry and growth of an “information economy” that would require knowledge workers in numbers exceeding the size of the rest of the economy.
The industry responded to the challenges in similar fashion as its forbears: It trained legions of capable, if unskilled, workers in the interior (but of India, not the United States) and imported guest workers, often by routing them through colleges that could give them the industry-relevant skills to be employable. This shift in IT resulted in moving the more routine and lower-skilled work offshore and using lower cost offshore firms to do the service work onshore.
There was widespread political reaction. In the course of a single year, 2004, the legislatures in 40 states introduced a total of more than 200 bills restricting offshoring (as compared with legislation proposed in only 4 states the year before). And the presidential candidate John Kerry, in a speech to his supporters, denounced offshoring firms and promised to eliminate tax loopholes for any “Benedict Arnold company or C.E.O. who take the jobs and money overseas and sticks you with the bill.”
It is in this context that it is possible to understand the genesis of the talent shortage claims. Initially, firms were focused on cost as the justification for moving operations offshore, and Wall Street analysts reacted favorably to every offshoring announcement. But in the face of growing public opposition to offshoring operations and layoffs, government and industry messaging about offshoring shifted from cost savings to the need for a talent search to compensate for a lack of sufficient supply of trained workers in the United States. Notably, the National Research Council in 2005 issued a report called Rising Above the Gathering Storm, which identified a need for the country to invest more in research and innovation and to train more people to do the work. And five years later, a follow-up report by committee chair Norm Augustine likened a perceived deepening of these problems to a Category 5 storm capable of wreaking untold destruction on the nation’s economy. The conclusions dominated the public narrative and continue to do so to this day, giving support to a peculiar claim that workforce shortages can best be met—and perhaps only be met—by increasing the inflow of high-skill guest workers.
Truth in the evidence
But researchers have time and again examined such claims and failed to find much evidence to support them. Examples of such reports include Into the Eye of the Storm: Assessing the Evidence on Science and Engineering Education, Quality, and Workforce Demand, published by the Urban Institute in 2007, and Will the Scientific and Technology Workforce Meet the Requirements of the Federal Government? by RAND in 2004. Studies that Lindsay Lowell and I have conducted also have found not only significant progress in STEM education and workforce development, but an ample supply of top-performing STEM graduates for what is, in fact, the small segment of industries in the economy (employing about 4 to 5% of the entire workforce) that depend on STEM workers.
FIGURE 1
Number of science and engineering freshmen and graduates in 2003 college cohort (graduating within six years)
SOURCE: U.S. Department of Education, National Center for Education Statistics, 2003/04 Beginning Postsecondary
Students Longitudinal Studies, Second Follow-ups (BPS:04/09); tabulations by authors )
Reviewing the empirical research in context, focusing on three key areas, may be useful for arriving at the facts needed to truly inform policy decisions about STEM-related issues.
The first area to consider is the broad notion of a supply crisis in which the United States does not produce enough STEM graduates to meet industry demand. In fact, the nation graduates more than two times as many STEM students each year as find jobs in STEM fields. For the 180,000 or so openings annually, U.S. colleges and universities supply 500,000 graduates. Accepting that STEM field definitions are overly restrictive and that in even marginally related occupations there could be a productive use of workers with STEM degrees, these numbers still represent a 50 to 70% greater supply than demand. Engineering has the highest rate at which graduates move into STEM occupations, but even here the supply is over 50% higher than the demand. IT, the industry most vocal about its inability to find enough workers, hires only two-thirds of each year’s graduating class of bachelor’s degree computer scientists. By comparison, three-quarters or more of graduates in health fields are hired into related occupations (see Figure 1).
But proponents of supply crisis claims push even further, arguing that STEM is a “leaking pipeline,” with students fleeing science and engineering fields in college because the courses are too difficult, the students are not prepared, or the students lose interest because society somehow has not provided them the motivation of a compelling national interest similar to the Cold War, with leaders now proclaiming a need for a new “Sputnik moment.”
Although the argument may sound plausible, the evidence once again is not quite aligned. Today’s students are taking more science and math courses (and performing better in them) than in any past generation. The extensive STEM enhancement programs funded by the National Science Foundation and other government and nongovernmental foundations and organizations appear to have raised the general level of STEM education across a wide range of disciplines (for example, half of all college STEM credit hours are taken by non-STEM majors) and significantly increased STEM studies among underrepresented minorities and women.
FIGURE 2
Occupational field of STEM college majors one year after graduation, 2009
Source: National Center for Education Statistics. (2013). 2003–2004 Baccalaureate and Beyond Survey (B&B)
[Restricted data file]. Washington, DC: U.S. Department of Education.; tabulations by authors.
Remarkably, the number of STEM majors, from first year through graduation, expands rather than shrinks. And among students who graduate within six years of enrollment, the number who start with a non-STEM major but graduate with a STEM degree is greater than the number who start in a STEM major and graduate with a non-STEM degree (see Figure 2). Even in the demanding field of engineering at a top school such as Stanford University, one of every nine graduates did not start as an engineering major but transferred into the program after the first year. So, yes, some students enter college thinking they want to be a scientist or engineer and then move to another major for one reason or another, but it seems that a greater number of other students find at some point in their studies that a STEM degree is more attractive.
Indeed, this loose coupling of students’ initial disciplinary choices and ultimate career paths might be expected, because college is often a period of exploration. The U.S. education and employment system is not designed to be tightly coupled as in other countries such as Germany, with its highly proscribed education and career tracks (beginning at age 14 and involving a national curriculum of sequenced courses and skill development for most jobs, and credentialing of jobs throughout the skill spectrum). Instead, the United States has a fluid system in which career paths can be pursued through a range of disciplines and educational experiences. Among students entering college undecided or unknowledgeable about future careers, it seems that the attraction of STEM is more compelling than popularly claimed. Importantly, this may well be a strength of the U.S. system: It allows those who are not passionate about the field to exit early and those who take longer to find their calling the ability to pursue it, and to bring with them a broader educational background.
The nation graduates more than two times as many STEM students each year as find jobs in STEM fields.
Failing to find current shortages, the argument then is turned to the qualifications of “STEM-eligible” students, and specifically to the idea that U.S. students, on average, do not perform well on international tests. But the evidence for this claim fails for a number of reasons. First, average scores of the students tested (mostly middle-schoolers) do not indicate the performance of the actual population that finds its way into STEM occupations. Of the students tested, about 25% will graduate with a four-year college degree; of those students, about 17% will graduate in a STEM field; and of those students, about half will enter a STEM or STEM-related field. This suggests that the performance of one very small segment—2 to 4%—of the overall student population is actually sufficient for evaluating the supply potential for the STEM labor force.
Second, the performance of the upper portion of the U.S. student distribution is world-class, and this segment is larger than most of the relevant populations in the oft-touted high-performing countries, such as Singapore, South Korea, Finland, or any of the central or eastern European countries formerly part of the Soviet Union.
Third, the average test scores of the countries that are of most concern as economic competitors would be dismal if a more representative sample of their students were tested, as is the case in the United States. China and India, in particular, have very large illiterate populations that would lead to devastatingly low averages.
Fourth, and of special interest, there is no credible evidence that scores on these tests have any relevance for the outcomes of interest: science and engineering performance, innovation, and economic competitiveness. A quick scan of the top-performing countries on education tests makes this apparent, because the list contains Slovenia, Estonia, the Czech Republic, and many other former Soviet countries, but not Brazil, Chile, or Israel. Moreover, the rotating list of top performers over the past decade does not appear to correspond to the rotating list of economic or innovation top-performing countries.
Perhaps even more telling, despite decades of supposedly low performance by U.S. students, the world has seen no credible competitors to the nation’s innovation regions (Silicon Valley in California, Route 128/Kendall Square in Massachusetts, Research Triangle Park in North Carolina, the biopharma corridor of New York and New Jersey). No doubt there will be innovation hubs emerging in other parts of the world in the near future. But that will not be prevented by improving the average scores of U.S. students, nor is there a reason why the United States should try to prevent the rise of other global innovation hubs or the overall improvement of other national economies. As my colleague Leonard Lynn and I have argued, we need a new global innovation strategy to achieve collaborative advantage with rising technology powers.
The second area to consider is the argument that even if STEM graduates are not employed in a STEM job, there are individual and social benefits to obtaining a STEM degree. But again, the evidence is thin, at best. Analyses typically compare STEM graduate salaries with those of all graduates, or STEM occupations with all occupations. An analysis conducted by my colleague Lindsay Lowell examined the average incomes among two sets of students: one group who started college interested in STEM, got a STEM degree, and entered a STEM field; and another group that started with similar interests but then chose another, non-STEM occupation. He found that the students not entering a STEM occupation went into fields that paid more than STEM occupations. A STEM career, then, does not seem to offer pay advantages for high-performing students.
Even for STEM graduates who do not go into STEM fields, it is claimed that they will still do better economically than non-STEM graduates. There is some truth to that, but it is not the entire story. STEM graduates make up about 17% of four-year undergraduates and about 5 to 7% of the overall workforce. It is a reasonable premise that the selectivity of STEM fields will result in a group of students with above-average academic performance. It may be that STEM graduates are, on average, higher-performing and go into higher-paying fields than those chosen by other students.
My colleague Leonard Lynn and I have additional evidence from interviews and some quantitative evidence about the purported advantages of STEM training and jobs. Our interviews with engineers, technology managers, and others in STEM fields find a broad and deep consensus that these fields are not highly attractive as careers financially or for employment stability. In the IT industry, a common view among managers and workers is that the occupation was great for their generation but the ride is now over, and they would not recommend an IT or engineering career to their sons and daughters. The threat of offshoring and an influx of guest workers are paramount in their assessment of the prospects in these fields. In life sciences, the perception is much the same, as most Ph.D. graduates will be likely to hold one or two postdoctoral positions, earning $50,000 a year for half a decade or more, and then be thrown into a poor job market in their mid-30s. These might be careers worth pursuing if one loves the work and is willing to play the job lottery, but they are not occupations attractive to those for whom the pay and conditions (relative to their other options) weigh strongly in the decision.
It may not be surprising, then, that some STEM students are showing a decline in persistence to stay in the field. Among recent cohorts we have studied, there has been a significant and dramatic decline in top-performing STEM students who make the transition to STEM occupations. This is in contrast to medical fields, which maintain their allure for the best and brightest, are still highly competitive, and have not significantly increased the number of degrees awarded for the past several decades. Although there may be a social cost in restricting the supply of workers, this must be evaluated in the context of the benefits of a market that continues to attract highly qualified students. In other words, in the market for STEM graduates, there is a price/quality tradeoff.
So if you are a STEM-capable student, what type of education will provide you with the best occupational options? Remarkably, there is no in-depth research addressing this question. My colleagues and I will be conducting that analysis in an upcoming project and can then provide a much more accurate assessment of the actual value-added of a STEM education (versus selection bias). But the current bottom line is that there is little compelling evidence to support efforts to herd into STEM majors any students who do not have an abiding interest in a STEM career.
The third area to consider is whether the customary market forces are, as claimed, not having their usual effect on supply and demand in STEM fields. This may be the most important claim, but what is the evidence that labor markets are not responsive? Would it not be logical to expect a rather high bar of evidence of market failure before advocating government intervention to distort the market-responsive level of supply? Here again, there is substantial evidence that the STEM labor market appears to work reasonably well. In the IT industry, from the 1990s through the peak of the dot-com bubble, wages climbed steeply. So, too, did the number of computer science graduates. After the bubble burst, wages fell, followed by a decline in the number of computer science graduates. Since then, wages have stayed well below their earlier peak and now hover around wage levels of the late 1990s.
If there were a talent shortage, where are the market indicators (namely wage increases) that signal students there is an opportunity to pursue a career in this industry that is better than their alternatives? Or has government policy restructured this labor market to supply seemingly endless numbers of guest workers who, coming from low-wage countries and constrained in their employment options, will understandably flock to these jobs even if wages are stagnant? With current policies that provide guest workers in numbers equal to as much two-thirds of new jobs in IT, it becomes less important for the IT industry to use the domestic market to supply its workforce. The petroleum industry also claims to be experiencing a sharp rise in its demand for petroleum engineers as new exploration increases and its current workforce starts to retire. But unlike the IT industry, petroleum companies stepped up the wages offered to new graduates by 40% over five years. As a result, the number of graduates more than doubled. These natural experiments provide strong evidence that STEM labor markets are responsive to market signals.
Guest workers provide benefits to the companies that hire them in the form of lower wages, but there is little evidence to suggest that they strengthen the nation’s science, engineering, or technology workforces.
Immigration versus guest workers
A final claim is that the success of the United States as an immigrant nation speaks to the benefits of an expansive guest worker program. It is this argument that presents the greatest confusion and conflicting claims that are genuinely difficult to disentangle. Distinguishing between labor policy and immigration policy is key to analyzing why the history of benefits from immigration is unlikely to occur from the new guest worker policies in some of the legislation now being developed.
Immigration policy addresses broad issues of diversity, equity, opportunity, and the long-term vibrancy of the United States. Historically, the nation’s essential experience (for other than Native Americans) is the immigrant story in nearly everyone’s family history, intertwined with the country’s success as the beneficiary of talented immigrants fleeing social, economic, and political unrest in their home countries and seeking the opportunities particular to U.S. society. Immigration from high-skill diasporas has varied from accomplished Soviet émigrés fleeing a crumbling régime to Nazi scientists who were extracted from Germany as part of Operation Paperclip to advance strategic and military advantage in the Cold War. Research on immigration identifies a range of positive (and some negative) impacts, and the numerous examples of immigrant-founded companies and illustrious achievements of immigrants across different areas, from the arts to the sciences to business, testify to the benefits of a society that welcomes them.
In contrast, many policymakers are promoting much narrower policies to promote an inflow of high-skill guest workers, even proposing such actions as awarding automatic green cards to any foreign STEM graduate of a U.S. university. But guest workers targeted to a specific industry sector and filling the vast majority of openings, unlike their immigrant counterparts, are likely to have a significantly negative impact on STEM (and particularly IT) labor markets, occupations, and careers. Thus, guest worker policy is vastly different from broader immigration policy, and the contributions of immigrants are also different from the impact of a large flow of high-skill guest workers targeted to one or several industries, particularly in the absence of compelling evidence of shortages. It is, in fact, the important role of immigration to the nation—socially and economically—that may be undermined by high-skill guest worker programs.
In terms of labor market impact, particularly in hightechnology industries, a further distinction arises from the difference between the permanent domestic labor force (native and immigrant, citizen and permanent resident alike) and the temporary guest worker labor force. The various cases of notable immigrants typically involve those who came to become permanent members of the nation, and they generally migrated as children and grew up as part of U.S. society. People who immigrate to the United States become part of the domestic workforce, whereas guest workers are brought in for a specific sector of the labor market.
Another important distinction is the difference between the “push” and “pull” drivers of immigration. Most of the broad waves of immigration, particularly high-skill immigration, have been push-driven, with people leaving their home country because of inhospitable conditions. In contrast, guest workers are recruited, or pulled, in large numbers, often for a particular industry. They will have a different impact on the labor force, and the effects may not be as nationally advantageous as widely proclaimed.
The actual use of guest workers makes this clear. For example, the guest worker programs are being driven primarily by a small industry segment that is targeting largely entry-level workers; two-thirds of current entering IT guest workers are under the age of 30 (see Figure 3) Moreover, Ron Hira, an engineer and policy analyst who focuses on these issues, has found that the companies that bring in over half of all H-1B visa holders appear to have no need for them in their permanent U.S. workforce and do not sponsor them for permanent residency. Norman Matloff, a professor of computer science who follows immigration and high-tech workforce interactions, has observed that guest workers have lower rates of innovation than their U.S. counterparts.
Broad, diverse immigration policies can strengthen the nation, whereas targeted, restrictive guest worker policies are more likely to undermine it.
In addition, in earlier research my colleague Radha Biswas and I found that a large portion of IT guest workers are the necessary conduit for offshoring IT work, because an offshore project requires about a third of the team to be onshore to work with the client, do requirements analysis, and liaise with the offshore team. One might argue that offshoring provides some benefit to the U.S. economy (for example, by lowering wages and thus reducing product prices), but it does not expand or strengthen the domestic STEM workforce. In fact, it has quite the opposite effect. The only clear impact of the large IT guest worker inflows over this decade can be seen in salary levels, which have remained at their late-1990s level and which dampen incentives for domestic students to pursue STEM careers (and, ultimately, for truly talented global students to come to the United States). Guest workers provide benefits to the companies that hire them in the form of lower wages, but there is little evidence to suggest that they strengthen the nation’s science, engineering, or technology workforces. Moreover, it is underrepresented minorities and recent permanent immigrants who are most likely to be disadvantaged through lower-paying jobs and job loss due to newly arriving guest workers.
Basing policy on evidence
It seems clear, then, that broad, diverse immigration policies can strengthen the nation, while targeted, restrictive guest worker policies are more likely to undermine it. It also seems clear that because evidence supposedly informs policy, the past failures of shortage predictions should serve as further caution to policymakers who may overlook the costs of ill-founded conclusions. For all the unknowns and uncertainties of labor market projections and supply/demand analyses, there is still a substantial and solid body of research and experience that should caution policymakers about being swayed by conventional wisdom offered by prominent advocates for a particular policy that may have limited or short-term benefit and that can have deeply negative and longlasting impacts.
Finally, policymakers and industry leaders may want to reconsider the notion that science and engineering development and national competitiveness are best served by such a concentrated focus on one or just a few disciplines or workforces. Rather, it may be the range of disciplines and talents that provides the United States some of its dynamism, innovativeness, and creativity. William J. Baumol, an economist who has written extensively on labor markets and technology, has argued (especially in a notable article published by the National Bureau of Economic Research in 2004) that entrepreneurs, who are disproportionately responsible for major innovations over the past century, are innovative because they have not gone through formal science and engineering education. In his view, this is because “education for mastery of scientific knowledge and methods…can impede heterodox thinking and imagination,” and because “large-firm R&D requires personnel who are highly educated in extant information and analytic methods, while successful independent entrepreneurs and inventors often lack such preparation.”
In the same vein, Steve Jobs has famously said that Apple, which is among the world’s most highly valued companies, represents the intersection between technology and the humanities. And before him, Edwin Land, a pioneering figure behind Polaroid and a developer of the nation’s first advanced aerial imaging technology, as well as a key adviser in founding NASA, pointed to the importance of “standing at the intersection of humanities and science.”
The achievements by these and other truly innovative individuals who often reached success through different and unexpected routes should be seen as the strength of the fluidity of the U.S. education and career system. They should also be seen as coming from a broadly focused immigration policy and investment in the domestic workforce, rather than from finding narrow substitutions for the domestic workforce.
“Whatever the enemy may be planning, American science will be equal to the challenge.”
