Foundations of Epistemic Risk
My goal in this dissertation is to start a conversation about the role of risk in the
decision-theoretic assessment of partial beliefs or credences in formal epistemology.
I propose a general theory of epistemic risk in terms of relative sensitivity
to different types of graded error. The approach I develop is broadly inspired
by the pragmatism of the American philosopher Charles Sanders Peirce and his
notion of the "economy of research." I express this framework in informationtheoretic
terms and show that epistemic risk, so understood, is dual to information
entropy. As a result, every unit increase in risk comes with a corresponding unit
decrease in information entropy and epistemic risk may be expressed in terms of
entropic change. I explain the significance of this for the selection of priors and
the Laplacian principle of indifference. I also extend this notion of epistemic risk
to the assessment of updating rules, where a similar duality between risk and information
holds. In the dynamic context, epistemic risk is given by cross-entropic
change. Here I explore the relationship between risk, the Value of Knowledge
Theorem, dynamic coherence, and the role of expected accuracy in the selection
of update rules. Finally, I apply these considerations to a social institution where
attitudes to error are especially salient - namely, legal decision-making - and argue
that considerations regarding the relative severity of different types of error
are central to understanding evidentiary burdens of proof and the probative value
of statistical evidence.
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