It is shown that if one applies decision theory to epistemic utilities measured by a strictly proper scoring rule, the two theories will deviate in their recommendations in cases that any Bayesian agent can easily put themselves in.
Abstract
Causal and Epistemic Decision theories differ in their recommendations in a large number of cases, the most famous of which is Newcomb’s Problem. These cases, including the original one, tend to be outlandish and unusual. We show that if one applies decision theory to epistemic utilities measured by a strictly proper scoring rule, the two theories will deviate in their recommendations in cases that any Bayesian agent can easily put themselves in. Moreover, the recommendations of Causal Decision Theory in these cases are implausible: it recommends that we perform the action whose performance gives us no information regarding the hypothesis with respect to which we are maximizing our epistemic utility. We shall see that requiring choices to be ratifiable, or using Barnett’s recent graded ratifiability criterion, does not help either. Nor is it completely clear that Evidential Decision Theory is off the hook.
It is concluded that cascades are not only likely to occur but are sometimes unavoidable by “rational” means: in some situations, the group’s inability to track the truth is the direct consequence of each agent’s rational attempt at individual truth-tracking.
It is concluded that cascades are not only likely to occur but are sometimes unavoidable by “rational” means: in some situations, the group’s inability to track the truth is the direct consequence of each agent’s rational attempt at individual truth-tracking.
It is concluded that cascades are not only likely to occur but are sometimes unavoidable by “rational” means: in some situations, the group’s inability to track the truth is the direct consequence of each agent’s rational attempt at individual truth-tracking.
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