Biases and debiasing in policy decision-making.

Abstract

Policy decision-making should use the best evidence obtained with the most rigorous and reproducible science and should be applied with minimal bias to maximize positive outcomes. This is particularly important in public health and other major decisions. Reality, however, is usually far from this ideal. The quality and use of scientific evidence to address wicked problems and sticky crises have been the focus of intense debate. Policymakers often succumb to fallacies, leading to suboptimal decision-making and maladaptive practices. We map the key biases involved at three different, but communicating, domains: the scientific evidence itself, the policymakers and the citizens. Biases may be classified along two axes pertaining to the perception of the risk and the perception of the effectiveness of the intervention: minimizing risk (e.g. crisis denial), maximizing risk (e.g. moral panic), minimizing intervention effectiveness (e.g. anti-medicine, anti-government) and maximizing effectiveness (e.g. drug lobbyism). We discuss common cognitive biases, including normalcy bias, ostrich effect, negativity bias, Just World Fallacy, false consensus effect, action bias and death spiral effect. Furthermore, we present an overview of potential debiasing processes and tools. Debiasing may help enhance the quality of implementations and trust in institutions, to the benefit of both science and society at large.