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Risk Assessment and Uncertainty

Kristin Shrader-Frechette
PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association
Vol. 1988, Volume Two: Symposia and Invited Papers (1988), pp. 504-517
Stable URL: http://www.jstor.org/stable/192908
Page Count: 14
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Risk Assessment and Uncertainty
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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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