Abstract

Recent work in the behavioral sciences asserts that we are subject to a variety of cognitive biases. For example, we mourn losses more than we prize equivalently sized gains; we are more inclined to believe something if it matches our previous beliefs; and we even relate more warmly or coldly to others depending on whether the coffee cup we are holding is warm or cold. Drawing on this work, case law and legal scholarship have asserted that we have reason to select legal norms, or revise existing norms, so as to eliminate the influence of these and other cognitive biases. In this Article, I critically evaluate whether and when this reaction is warranted. I begin by contrasting predominantly descriptive definitions of bias, on which bias is merely deviation from a predictive model, with prescriptive definition of bias, on which biased conduct is conduct that actors ought not do. I then similarly contrast the behavioral-scientific concepts of statistical significance and effect size with the concept of significance required to justify legal conclusions. With this apparatus in place, I go on to consider a variety of examples where legal commentators and decisionmakers have worried about the effects of cognitive bias on law. I argue that many of these cognitive biases (for example, our aversion to losses), while reflecting deviations from behavioral scientists’ models of human behavior, are not normatively objectionable and so give us no reason to revise our legal norms to eliminate their effect. Others (e.g., the effect of judges’ hunger on their decisionmaking), however, constitute biases under both descriptive and prescriptive definitions and therefore give us good reason to revise our legal norms. I conclude by contrasting my conclusion — that evaluation of cognitive biases’ legal significance must explicitly evaluate the normative arguments for and against the model of decisionmaking in question on a case-by-case basis — with the arguments of influential scientists and legal commentators like Daniel Kahneman and John Mikhail, who treat cognitive heuristics and biases as more broadly desirable or objectionable.