A Theory of Epistemic Risk
Published online by Cambridge University Press: 01 January 2022
I propose a general alethic theory of epistemic risk according to which the riskiness of an agent’s credence function encodes her relative sensitivity to different types of graded error. After motivating and mathematically developing this approach, I show that the epistemic risk function is a scaled reflection of expected inaccuracy (a quantity also known as generalized information entropy). This duality between risk and information enables us to explore the relationship between attitudes to epistemic risk, the choice of scoring rules in epistemic utility theory, and the selection of priors in Bayesian epistemology more generally (including the Laplacean principle of indifference).
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I would like to thank Jim Joyce for his invaluable support and guidance in developing this project. I have also received helpful feedback from Sara Aronowitz, Gordon Belot, Daniel Drucker, Frederick Eberhardt, Dmitri Gallow, Rich Gonzalez, Hilary Greaves, Christopher Hitchcock, Simon Huttegger, Sarah Moss, Matt Parker, Richard Pettigrew, Peter Railton, Julia Staffel, Anubav Vasudevan, Brian Weatherson, and audiences at the University of Michigan, University of Chicago, London School of Economics, and California Institute of Technology. Special thanks are also due to two anonymous reviewers from Philosophy of Science for their very helpful comments and feedback. Research for this project was supported by the Social Sciences and Humanities Research Council of Canada.