The realities of risk-cost-benefit analysis

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Science  30 Oct 2015:
Vol. 350, Issue 6260, aaa6516
DOI: 10.1126/science.aaa6516

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Setting policy, knowing risks

Policy-makers often commission formal analyses to estimate the costs, risks, and benefits of proposed projects or policies. Applications range from estimating the risks of commercial nuclear power, to setting priorities among environmental risks, to comparing technologies for generating electricity, to weighing the benefits and risks of prescription drugs. In the United States, analyses are required for all major federal regulations. Fischhoff reviews how such analyses are limited by the scientific and ethical judgments inherent in the process and require collaboration between those who generate the analyses and those who want to use them.

Science, this issue p. 10.1126/science.aaa6516

Structured Abstract


Synthetic biology, nanotechnology, geoengineering, and other innovative technologies share a property: Their effects must often be inferred long before they are experienced. If those inferences are sound, then informed decisions are possible. If not, then decision-makers may incur risks and costs far greater than any expected benefits. Risk, cost, and benefit analysis can offer transparent ways to assemble and integrate relevant evidence to support complex decision-making All forms of analysis have the same logic: Decompose complex systems into manageable components and then calculate how they might perform together. All require scientific judgment to bound the set of components and assess the limits to those bounds. All require ethical judgment to determine which outcomes to predict and to extract the policy implications of the results. The usefulness of any analysis depends on how well its underlying assumptions and their implications are understood by those hoping to use its results. The present review uses historical examples to illustrate the roles of judgment in analyses that address four basic questions: (i) How large are the risks from a single technology?(ii) Which risks merit the greatest attention? (iii) Which technology produces the least risk per unit of benefit? (iv) Are a technology’s expected benefits acceptable, given its risks and other expected costs?


Analyses are always incomplete. They neglect concerns that are hard to quantify. They define terms in ways that serve some interests more than others. They consider some sources of uncertainty but not others. Advances in the science of analysis have often occurred after critics unhappy with the results of an analysis challenged the legitimacy of its assumptions. Awareness of the role of judgment in analysis has grown over time, in parallel with improvements in the sophistication of analytical calculations. Progress has been made in some areas, but more is needed, to include developing better ways to model human behavior, elicit expert judgments, articulate decision-makers’ preferences, characterize the robustness of conclusions, and communicate with decision-makers. The practice of analysis draws on the sciences of public participation and science communication, both shaped by the challenges faced in securing a fair hearing for science in issues where it plays a central role.


The pace of advances will depend on the degree of collaboration among the sciences relevant to these problems, including not only the sciences underlying the technology in question but social, behavioral, and economic science as well. How well the science of analysis aids its practice will depend on how well analysts collaborate with decision-makers so as to produce the estimates that decision-makers need and ensure that analytical results are properly understood. Over time, those interactions will help decision-makers understand the capabilities and limitations of analysis while helping analysts become trusted allies, dedicated to producing relevant, properly qualified estimates of cost, risk, and benefit.

An analytical-deliberative process in which analysts and decision-makers collaborate in managing risks.

The process begins by defining the terms of the analysis (initiation), proceeds to preliminary analysis, identifying the issues meriting greatest attention, and continues through estimation of the magnitude of the risks, evaluation of their acceptability, and consideration of control mechanisms, improving the risk-cost-benefit trade-offs. Once an action has been selected, monitoring assesses how well the ensuing reality corresponds to the analytical conclusions. At all stages, analysts communicate with those potentially affected by the risks in question. Analogous processes apply to cost and benefit analyses. [Adapted from Canadian Standards Association, Risk Management: Guidelines for Decision Makers (Q850) (CSA, Ottawa, Canada, 1997)]


Formal analyses can be valuable aids to decision-making if their limits are understood. Those limits arise from the two forms of subjectivity found in all analyses: ethical judgments, made when setting the terms of an analysis, and scientific judgments, made when conducting it. As formal analysis has assumed a larger role in policy decisions, awareness of those judgments has grown, as have methods for making them. The present review traces these developments, using examples that illustrate the issues that arise when designing, executing, and interpreting analyses. It concludes with lessons learned from the science and practice of analysis. One common thread in these lessons is the importance of collaborative processes, whereby analysts and decision-makers educate one another about their respective needs and capabilities.

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