Equalised Odds is not Equal Individual Odds: Post-processing for Group and Individual Fairness-Reference-Cited by-同舟云学术

Equalised Odds is not Equal Individual Odds: Post-processing for Group and Individual Fairness

Published:2024-06-03 Issue: Volume: Page:
ISSN:
Container-title:The 2024 ACM Conference on Fairness, Accountability, and Transparency
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Author:

Small Edward¹^ORCID,Sokol Kacper²^ORCID,Manning Daniel¹^ORCID,Salim Flora D.³^ORCID,Chan Jeffrey¹^ORCID

Affiliation:

1. RMIT University, Australia

2. ETH Zürich, Switzerland

3. University of New South Wales, Australia

Funder

Australian Research Council

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3630106.3658989

Reference46 articles.

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2. Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner. 2016. Machine bias. ProPublica 23 (May 2016).

3. Pranjal Awasthi, Matthäus Kleindessner, and Jamie Morgenstern. 2020. Equalized odds postprocessing under imperfect group information. In Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, Vol. 108. PMLR, 1770–1780.

4. Pablo Barceló, Mikaël Monet, Jorge Pérez, and Bernardo Subercaseaux. 2020. Model Interpretability through the lens of computational complexity. In Advances in Neural Information Processing Systems, Vol. 33. Curran Associates, Inc., 15487–15498.

5. Joachim Baumann, Anikó Hannák, and Christoph Heitz. 2022. Enforcing Group Fairness in Algorithmic Decision Making: Utility Maximization Under Sufficiency. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency. 2315–2326.