Abstract

Several different Bayesian models of epistemic utilities (see, e.g., [37], [24], [40], [46]) have been used to explain why it is rational for scientists to perform experiments. In this paper, I argue that a model–suggested independently by Patrick Maher [40] and Graham Oddie [46]–that assigns epistemic utility to degrees of belief in hypotheses provides the most comprehensive explanation. This is because this proper scoring rule (PSR) model captures a wider range of scientifically acceptable attitudes toward epistemic risk than the other Bayesian models that have been proposed. I also argue, however, that even the PSR model places unreasonably tight restrictions on a scientist’s attitude toward epistemic risk. As a result, such Bayesian models of epistemic utilities fail as normative accounts–not just as descriptive accounts (see, e.g., [31], [14])–of scientific inquiry.

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