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Tens of thousands of people in 600 cities around the world marched for science on 22 April. More than four-and-a-half centuries after the start of at least one scientific revolution, people took to the streets to defend what should be something to celebrate.
The March for Science and related movements focus on threats to the flow of knowledge, but there is also a more fundamental question—why are we not using the stock of evidence already produced by science more effectively? What larger social context makes it acceptable to build a wall to halt immigration, use tape and thermocol sheets to limit surface evaporation of water, or impose price caps on drugs and medical devices and hope that the relevant entities will then supply more?
This is the era of alternative facts, evidence-free debates, and use of sovereign authority to promote ideas that look better as slogans than under scientific scrutiny. Why? The barriers to absorption of science in public-interest decision making—the collective pursuit of social welfare, often but not exclusively undertaken by states—are just as important to address as the threats to its production.
There are three broad categories of issues: demand inhibitors, supply-side distortions, and transactional challenges.
First, on the demand side, the pressure to perform is both too weak and too strong. It is too weak to drive an ongoing search for the best information or latest evidence. Performance and tenure are correlated in political and social impact worlds, but imperfectly so. The power of narrative softens the edges. Moreover, policies and social impact are generally collective efforts, which mean that there are always contexts and collaborators to be blamed. There is no equivalent of the cold, hard, precise reality of financial results that pushes, say, large agri-business or the re-insurance industry to keep up with climate science.
The pressure to perform is too strong, however, to encourage innovation. Science is not certainty, and sometimes new ideas fail. In a world that often withholds the benefit of the doubt and generally cannot think back to consider ex-ante reasoning in the face of ex-post failure, sticking with the tried and true is the safest way to avoid the fallout from failure. This caution inhibits demand for science-backed approaches that require a departure from precedent.
On the supply side, the production of science for general public consumption (distinguishing from specific commissioned studies) is often driven by the internal logic of the academic community. This community, populated by people who essentially require the approval of their peers to advance, looks within itself for guidance as much as to the world at large. Public funding of science—the flows of funds that the current movements seek to protect—mitigate these incentives somewhat but not entirely. Policymaker or donor efforts to direct these funds often attract accusations of politicization, or purchase of science. There is merit to these claims, but the hue and cry also limits constructive communication about public priorities and the application of the scientific method to addressing them.
Much “useful” science also fails the glamour test. Donors, funders, and much of the science community itself focus on discovery. But discovery and its impact on decisions is just one small part of the larger science-policy interface. The science required for setting regulatory standards, for example, involves much more mundane reiteration and verification of knowledge. Meta-analyses of the overall findings in the literature are useful for policy guidance but also relatively thankless in terms of professional advancement within most fields.
Finally, there are transaction barriers to matching supply and demand. The first is that expertise often comes from experience, and experience may very well be gained in the industries and other arenas that public-interest decision making seeks to affect. The detailed knowledge required to effectively regulate biotechnology or undertake cost-effective pollution remediation may come from people who have worked in the communities that contributed to the problem in the first place. Their application of expertise to public purpose cannot always be policed —by definition they are the experts who know more.
This is an old problem in political economy and there are a variety of institutional designs to align interests, but none are perfect in eliminating the pursuit of particular interests disguised as expert advice. More importantly, the appearance of conflict of interest that can be used to rationalize rejection of inconvenient advice is nearly impossible to eliminate.
Scale differences also complicate the meeting of supply with demand. Scientific inquiry focuses on the scale that makes the most sense for characterizing the problem and designing a reasonable experiment. Public decision making, and policy in particular, focus on the geographic or sectoral area where one has jurisdiction. The world gets lucky when these two things match. Both science and jurisdictional boundaries evolve, often in an effort to match each other, but not always fast enough to effectively harness science for public decision making.
There are important exceptions to these sweeping generalizations. But the basic point remains. We need to do more than protect the flow of knowledge in progress—we need systemic solutions for better using the stock of science we have already.
Jessica Seddon is managing director of Okapi Research and Advisory and visiting fellow at IDFC Institute. She writes fortnightly on patterns in public affairs.
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