Conditionalization Does Not Maximize Expected Accuracy

Mind 126 (504):1155-1187 (2017)
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Abstract

Greaves and Wallace argue that conditionalization maximizes expected accuracy. In this paper I show that their result only applies to a restricted range of cases. I then show that the update procedure that maximizes expected accuracy in general is one in which, upon learning P, we conditionalize, not on P, but on the proposition that we learned P. After proving this result, I provide further generalizations and show that much of the accuracy-first epistemology program is committed to KK-like iteration principles and to the existence of a class of propositions that rational agents will be certain of if and only if they are true.

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Miriam Schoenfield
University of Texas at Austin

Citations of this work

Rational Polarization.Kevin Dorst - 2023 - Philosophical Review 132 (3):355-458.
Lockeans Maximize Expected Accuracy.Kevin Dorst - 2019 - Mind 128 (509):175-211.
What is conditionalization, and why should we do it?Richard Pettigrew - 2020 - Philosophical Studies 177 (11):3427-3463.
The Value of Biased Information.Nilanjan Das - 2023 - British Journal for the Philosophy of Science 74 (1):25-55.

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References found in this work

Knowledge and its limits.Timothy Williamson - 2000 - New York: Oxford University Press.
Laws and symmetry.Bas C. Van Fraassen - 1989 - New York: Oxford University Press.
Accuracy and the Laws of Credence.Richard Pettigrew - 2016 - New York, NY.: Oxford University Press UK.
Scientific reasoning: the Bayesian approach.Peter Urbach & Colin Howson - 1993 - Chicago: Open Court. Edited by Peter Urbach.
Knowledge and Its Limits.Timothy Williamson - 2000 - Philosophy 76 (297):460-464.

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