Science for a Proper Recovery: Post-Normal, not New Normal
Standard notions of science undercut our ability to respond to COVID-19. Post-normal science offers a vision that matches the complexity of science, society, and nature.
In the midst of COVID-19, science is obviously not at all the same as we have always understood it. Rather than being able to make “evidence-based decisions,” we find that many crucial facts are uncertain at best, values are in violent dispute, stakes run to hundreds of billions of dollars and hundreds of thousands of lives, and the daily death toll makes even personal decisions vitally urgent. Should I wear a mask? Should I visit my grandmother? How shall I protect my children, my business, my university?
“Normal” science is totally inadequate to cope with this complexity, and needs to be supplemented with a broadened awareness of solutions and problems alike. Managing the pandemic requires not only the acquiescence of the populace in the restrictions of their social and economic lives but also the active participation of a great many people in making those restrictions effective and bearable. The diffusion of uncertain facts into society turns all of us into an “extended peer community.”
In the context of global climate change and now COVID-19, there has been much talk of “the new normal”; that is, the situation we’ll all need to get used to when things settle in and we get accustomed to what’s changed. But the new normal is an exercise in nostalgia—for a time that never was.
Many years ago, the mathematician Silvio Funtowicz and I were trying to understand why science often didn’t seem to be helping with some tough social problems. We had two sorts of events mainly in mind. One was the “zero-infinity” risks, where experts claim the probability of an event occurring is extremely low (almost zero) but the consequences of such an event are potentially catastrophic (almost infinite). The nuclear accident at Three Mile Island is an example of this kind of event. The other category was “housewives’ epidemiology,” which helped discover disease clusters resulting from the toxic waste dump in the Love Canal community of Niagara Falls, New York, and the mysterious tick-borne disease named after its identification by two mothers in Lyme, Connecticut.
In all such cases the established experts got it wrong, and in the latter cases the locals got it right. Funtowicz and I wanted to show, first, that mathematical reductionism (such as risk calculations for low-probability, high-consequence disasters) is an inappropriate strategy for policy-relevant science. And second, that the way forward is an extension of the scientific peer community to assess quality (to include, for instance, people in communities affected by environmental hazards). After much thought and experiment, we finally came up with the term “Post-Normal Science” to describe this different sort of science.
Back then, we chose this term as a nod to Thomas Kuhn, the philosopher of science whose famous book The Structure of Scientific Revolutions developed the conception of “‘normal’ science” to describe what most scientists do: puzzle-solving within a dogmatically imposed paradigm. In Kuhn’s normal science, the scientists share the paradigm (say, Newtonian physics, or the germ theory of disease) that determines what they study, what questions they ask, and what kind of answers they come up with. This has allowed scientists to go about solving various scientific puzzles in isolation from society. We wanted to think about and describe a very different science, where the facts were uncertain, the social stakes were high, decisions were urgent, and values were in dispute. Will the nuclear reactor be safe? Why are the children in my neighborhood getting sick?
To get a sense of the difference between normal and post-normal science, consider the difference between the concepts of risk and safety. Risk has been understood by experts as a quantifiable property of situations, the product of multiplying the probability of an event by the magnitude of the harm it might create. The social and political aspects are managed by the idea of the “perception of risk” or the “acceptability of risk.” The logic is that if people accept a risk of a certain magnitude, say automobile accidents, then they are being irrational or malign if they reject one of smaller magnitude, say nuclear power.
By contrast, safety is a complex concept, partly pragmatic, partly scientific, partly ethical. It relates to the whole context in which the hazard is created, managed, endured, and contested. Now that pandemic-related lockdown restrictions are being relaxed, the key decisions are about safety. Parents do not ask, Do I accept the quantified risk of my child returning to school? but rather, Given all the trade-offs, complexities, and uncertainties, do I believe it is safe to send my child back to school? The judgment of safety is eminently post-normal because it cannot be reduced to a number. In such decisions, the parents, individually and collectively, become members of the extended peer community, deciding on the combined basis of uncertain facts, particular sets of values, and the need to act.
With the post-normal science approach, we can find it natural to accept that the social and political aspects of the pandemic are as important as the biological. That is: the great variety of societal responses to this virus that we have seen are not secondary phenomena to its molecular structure. It is not only several nations of East Asia that have organized an effective communal defense; we also have New Zealand and even impoverished Greece as success stories.
What patterns can we discern from their experiences? As a first guess we can observe that among affluent nations, the hardest hit include those with a political culture that venerates economic efficiency, which was long ago identified by the economist John Kenneth Galbraith as “private opulence, public squalor.” The “vulnerable” who are most affected by the virus include the “thrown-away” groups, such as the homeless and the inhabitants of institutions (voluntary or involuntary); those whose jobs (frequently essential) are despised for their content or their remuneration; and finally those who are an embarrassment, such as poorer immigrants and the nonexterminated aboriginals. In this sense the microscopic viral predators cull our populations, as ever, but with a selection that is not natural but social and political.
Even as the initial COVID-19 peak has passed in many places, pitfalls still lurk. For a proper recovery we will need a post-normal science understanding of the pandemic as essentially a complex entity where the social, ethical, and ideological dimensions interact strongly, sometimes decisively, with the biological. Recovery must be done piecemeal, and then policy-makers will continuously confront contingency, complexity, error, and uncertainty in their situations. And the affected public must be integrated into the recovery effort as an extended peer community; otherwise the inevitable variations and exceptions become the occasion for resentment, evasion, and failure.
In this sense the pandemic has profoundly ethical elements, as Albert Camus’s novel The Plague made plain with its characters who found integrity and decency in the midst of meaningless suffering and death. It is not a coincidence that David Waltner-Toews, an epidemiologist whose insights are both deep and practical, is also a poet. He wrote in 2017 that “there is no generic [emerging infectious disease], and there will be no single solution to … prevent the emergence and spread of infectious diseases. There will always be conflicts. It is in our human solidarity, and the ways in which scholars and policy-makers manage those conflicts, that the maturity of our science, and indeed of our civilization, is reflected.”
It is also possible to take a longer view. The ecologist C. S. Holling recognized that some ecosystems, such as forests, undergo periodic collapse from infestations or fire. But they regenerate, and for some species, such as the sequoia, the catastrophe is part of a long-term life-cycle. This cyclic-systems “resilience” perspective teaches us that when a restricted set of systems properties—such as economic efficiency—is singled out for optimization, the result is a lack of systemic robustness. The ensuing response to external stressors is inevitable disruption and even collapse.
Consider that in the United States and the United Kingdom alike, efforts to maximize economic efficiency in medical care have led to a system that has no spare capacity with which to accommodate the surge of patients from the pandemic. This lack of capacity alone had the potential to cause society-wide chaos in the absence of draconian social and economic interventions.
In world-historical terms we also see periodic collapse and regeneration. A half-millennium of European economic and cultural expansion came to its end with the Great War. Its American extension has been brief, and the twin crises of the Great Recession of 2007–2008 and the coronavirus have now left the US heartland financially debilitated. The initial conquest of the Western hemisphere was facilitated by the susceptibility of indigenous peoples to European microbes. Now we all suffer in turn because the consensus among rulers of leading nations about the importance of economic liberalism has created a culture so devoted to being economically efficient that it had no way to prepare for inevitable new microbial perils.
Normal science, with its fantasy of reduction of all qualities to numbers, has functioned both as the method and ideology of this self-destructive regime. Any “new normal” regime that seeks to resuscitate this fantasy will blunder into its same failings. Can we learn from COVID-19 and move to a post-normal science conception of knowledge and its place in the world?