| Publication type: | Conference paper |
| Type of review: | Peer review (publication) |
| Title: | Gradual (in)compatibility of fairness criteria |
| Authors: | Hertweck, Corinna Räz, Tim |
| et. al: | No |
| DOI: | 10.1609/aaai.v36i11.21450 |
| Proceedings: | Proceedings of the 36th AAAI Conference on Artificial Intelligence : Vol. 36 No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations |
| Volume(Issue): | 36 |
| Issue: | 11 |
| Page(s): | 11926 |
| Pages to: | 11934 |
| Conference details: | 36th AAAI Conference on Artificial Intelligence, online, 22 February–1 March 2022 |
| Issue Date: | 25-Feb-2022 |
| Publisher / Ed. Institution: | Association for the Advancement of Artificial Intelligence |
| Publisher / Ed. Institution: | Palo Alto, CA |
| ISBN: | 978-1-57735-876-3 |
| ISSN: | 2374-3468 2159-5399 |
| Language: | English |
| Subjects: | Fairness; Discrimination; Statistical parity; Accuracy; Mutual information; Entropy; Separation; Sufficiency; Independence |
| Subject (DDC): | 006: Special computer methods 170: Ethics |
| Abstract: | Impossibility results show that important fairness measures (independence, separation, sufficiency) cannot be satisfied at the same time under reasonable assumptions. This paper explores whether we can satisfy and/or improve these fairness measures simultaneously to a certain degree. We introduce information-theoretic formulations of the fairness measures and define degrees of fairness based on these formulations. The information-theoretic formulations suggest unexplored theoretical relations between the three fairness measures. In the experimental part, we use the information-theoretic expressions as regularizers to obtain fairness-regularized predictors for three standard datasets. Our experiments show that a) fairness regularization directly increases fairness measures, in line with existing work, and b) some fairness regularizations indirectly increase other fairness measures, as suggested by our theoretical findings. This establishes that it is possible to increase the degree to which some fairness measures are satisfied at the same time -- some fairness measures are gradually compatible. |
| Further description: | AAM of the article with technical appendix can be found here: https://arxiv.org/abs/2109.04399 |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/29379 |
| Fulltext version: | Published version |
| License (according to publishing contract): | Licence according to publishing contract |
| Departement: | School of Engineering |
| Organisational Unit: | Institute of Data Analysis and Process Design (IDP) |
| Published as part of the ZHAW project: | Socially acceptable AI and fairness trade-offs in predictive analytics |
| Appears in collections: | Publikationen School of Engineering |
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Hertweck, C., & Räz, T. (2022). Gradual (in)compatibility of fairness criteria [Conference paper]. Proceedings of the 36th AAAI Conference on Artificial Intelligence : Vol. 36 No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations, 36(11), 11926–11934. https://doi.org/10.1609/aaai.v36i11.21450
Hertweck, C. and Räz, T. (2022) ‘Gradual (in)compatibility of fairness criteria’, in Proceedings of the 36th AAAI Conference on Artificial Intelligence : Vol. 36 No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations. Palo Alto, CA: Association for the Advancement of Artificial Intelligence, pp. 11926–11934. Available at: https://doi.org/10.1609/aaai.v36i11.21450.
C. Hertweck and T. Räz, “Gradual (in)compatibility of fairness criteria,” in Proceedings of the 36th AAAI Conference on Artificial Intelligence : Vol. 36 No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations, Feb. 2022, vol. 36, no. 11, pp. 11926–11934. doi: 10.1609/aaai.v36i11.21450.
HERTWECK, Corinna und Tim RÄZ, 2022. Gradual (in)compatibility of fairness criteria. In: Proceedings of the 36th AAAI Conference on Artificial Intelligence : Vol. 36 No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations. Conference paper. Palo Alto, CA: Association for the Advancement of Artificial Intelligence. 25 Februar 2022. S. 11926–11934. ISBN 978-1-57735-876-3
Hertweck, Corinna, and Tim Räz. 2022. “Gradual (in)Compatibility of Fairness Criteria.” Conference paper. In Proceedings of the 36th AAAI Conference on Artificial Intelligence : Vol. 36 No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations, 36:11926–34. Palo Alto, CA: Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/aaai.v36i11.21450.
Hertweck, Corinna, and Tim Räz. “Gradual (in)Compatibility of Fairness Criteria.” Proceedings of the 36th AAAI Conference on Artificial Intelligence : Vol. 36 No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations, vol. 36, no. 11, Association for the Advancement of Artificial Intelligence, 2022, pp. 11926–34, https://doi.org/10.1609/aaai.v36i11.21450.
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