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Ignorance: Lessons from the Laboratory of Literature
Devjani Roy and Richard Zeckhauser
Economists, psychologists, and decision theorists try to distill the ways in which people in the real world make decisions. When outcomes are known, decision making is pretty straightforward. Hence, across a broad range of circumstances, prescriptive decision making approximates rational prescriptions. When outcomes are unknown, however, grave difficulties intrude. People choose poorly, at least as judged from the standpoint of the well-developed prescriptive theories built on Bayesian decision and expected utility.
Unknown outcomes can be further classified into risk and uncertainty. Risk applies when probabilities are known, as they are at gambling tables, or for insurance companies that have vast amounts of data on individual risks. Uncertainty prevails when even those probabilities are unknown, as they are for virtually all real-life decisions. Some of the best analytical minds of the twentieth century—Frank P. Ramsey, John Maynard Keynes, John von Neumann, and Leonard Jimmie Savage—grappled with the problem of how individuals should make choices under uncertainty; they formulated axioms and prescriptions for effective decision making. Toward the end of that century, eminent psychologists Amos Tversky and Daniel Kahneman and those whofollowed in their footsteps documented the significant and systematic deviations of the decisions of ordinary mortals from the prescriptions of those great mathematical minds. Such deviations are disturbing since those prescriptions are now widely—though not universally—accepted by economists and decision theorists as showing how people should decide.