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Title: Avoiding Disparity Amplification under Different Worldviews
We mathematically compare four competing definitions of group-level nondiscrimination: demographic parity, equalized odds, predictive parity, and calibration. Using the theoretical framework of Friedler et al., we study the properties of each definition under various worldviews, which are assumptions about how, if at all, the observed data is biased. We argue that different worldviews call for different definitions of fairness, and we specify the worldviews that, when combined with the desire to avoid a criterion for discrimination that we call disparity amplification, motivate demographic parity and equalized odds. We also argue that predictive parity and calibration are insufficient for avoiding disparity amplification because predictive parity allows an arbitrarily large inter-group disparity and calibration is not robust to post-processing. Finally, we define a worldview that is more realistic than the previously considered ones, and we introduce a new notion of fairness that corresponds to this worldview.  more » « less
Award ID(s):
1704985
PAR ID:
10231435
Author(s) / Creator(s):
;
Date Published:
Journal Name:
FAccT '21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency
Page Range / eLocation ID:
273 to 283
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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