Babic, Boris and Gaba, Anil and Tsetlin, Ilia and Winkler, Robert (2021) Normativity, Epistemic Rationality, and Noisy Statistical Evidence. [Preprint]

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Abstract

Many philosophers have argued that statistical evidence regarding group char- acteristics (particularly stereotypical ones) can create normative conflicts between the requirements of epistemic rationality and our moral obligations to each other. In a recent paper, Johnson-King and Babic argue that such conflicts can usually be avoided: what ordinary morality requires, they argue, epistemic rationality permits. In this paper, we show that as data gets large, Johnson-King and Babic’s approach becomes less plausible. More constructively, we build on their project and develop a generalized model of reasoning about stereotypes under which one can indeed avoid normative conflicts, even in a big data world, when data contain some noise. In doing so, we also articulate a general approach to rational belief updating for noisy data.

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Item Type:	Preprint
Creators:	Creators Email ORCID Babic, Boris 0000000328001307 Gaba, Anil Tsetlin, Ilia Winkler, Robert
Subjects:	General Issues > Decision Theory General Issues > Ethical Issues Specific Sciences > Probability/Statistics
Depositing User:	Boris Babic
Date Deposited:	15 Mar 2021 04:20
Last Modified:	15 Mar 2021 04:20
Item ID:	18794
Subjects:	General Issues > Decision Theory General Issues > Ethical Issues Specific Sciences > Probability/Statistics
Date:	2021
URI:	https://philsci-archive.pitt.edu/id/eprint/18794

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