Risk Assessment and Uncertainty

Abstract
The "prevailing opinion" among decision theorists, according to John Harsanyi, is to use the Bayesian rule, even in situations of uncertainty. I want to argue that the prevailing opinion is wrong, at least in the case of societal risks under uncertainty. Admittedly Bayesian rules are better in many cases of individual risk or certainty. (Both Bayesian and maximin strategies are sometimes needed.) Although I shall not take the time to defend all these points in detail, I shall argue (1) that there are compelling reasons for rejecting Harsanyi's defense of the Bayesian strategy under uncertainty; (2) that it is more rational, in specific types of situations, to prefer the maximin strategy; and (3) that calibrating expert opinions is superior to using the equiprobability assumption or subjective probabilities.
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