An Impossibility Theorem for Base Rate Tracking and Equalized Odds

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Abstract

There is a theorem that shows that it is impossible for an algorithm to jointly satisfy the statistical fairness criteria of Calibration and Equalised Odds non-trivially. But what about the recently advocated alternative to Calibration, Base Rate Tracking? Here, we show that Base Rate Tracking is strictly weaker than Calibration, and then take up the question of whether it is possible to jointly satisfy Base Rate Tracking and Equalised Odds in non-trivial scenarios. We show that it is not, thereby establishing an even more general impossibility theorem.

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Author Profiles

Benjamin Eva
Duke University
Reuben Stern
Duke University
Shanna Slank
University of North Carolina, Chapel Hill
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Citations of this work

New Possibilities for Fair Algorithms.Michael Nielsen & Rush Stewart - 2024 - Philosophy and Technology 37 (4):1-17.
Spanning in and Spacing out? A Reply to Eva.Michael Nielsen & Rush Stewart - 2024 - Philosophy and Technology 37 (4):1-4.

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References found in this work

Algorithmic Fairness and Base Rate Tracking.Benjamin Eva - 2022 - Philosophy and Public Affairs 50 (2):239-266.
Identity and the Limits of Fair Assessment.Rush T. Stewart - 2022 - Journal of Theoretical Politics 34 (3):415-442.
On the Possibility of Testimonial Justice.Rush T. Stewart & Michael Nielsen - 2020 - Australasian Journal of Philosophy 98 (4):732-746.

Add more references