| Publication type: | Conference paper |
| Type of review: | Peer review (publication) |
| Title: | People are not coins : morally distinct types of predictions necessitate different fairness constraints |
| Authors: | Viganò, Eleonora Hertweck, Corinna Heitz, Christoph Loi, Michele |
| et. al: | No |
| DOI: | 10.1145/3531146.3534643 |
| Proceedings: | Faact '22: Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency |
| Page(s): | 2293 |
| Pages to: | 2301 |
| Conference details: | 5th ACM Conference on Fairness, Accountability, and Transparency (FAccT), Seoul, Republic of Korea, 21–24 June, 2022 |
| Issue Date: | 23-Jun-2022 |
| Publisher / Ed. Institution: | Association for Computing Machinery |
| Publisher / Ed. Institution: | New York |
| ISBN: | 9781450393522 |
| Language: | English |
| Subjects: | Fairness metrics; Discrimination; Decision-making; Artificial intelligence; Fair prediction; Moral principle |
| Subject (DDC): | 006: Special computer methods 170: Ethics |
| Abstract: | In a recent paper [1], Brian Hedden has argued that most of the group fairness constraints discussed in the machine learning literature are not necessary conditions for the fairness of predictions, and hence that there are no genuine fairness metrics. This is proven by discussing a special case of a fair prediction. In our paper, we show that Hedden's argument does not hold for the most common kind of predictions used in data science, which are about people and based on data from similar people; we call these “human-group-based practices.” We argue that there is a morally salient distinction between human-group-based practices and those that are based on data of only one person, which we call “human-individual-based practices.” Thus, what may be a necessary condition for the fairness of human-group-based practices may not be a necessary condition for the fairness of human-individual-based practices, on which Hedden's argument is based. Accordingly, the group fairness metrics discussed in the machine learning literature may still be relevant for most applications of prediction-based decision making. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/29380 |
| 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) |
| Appears in collections: | Publikationen School of Engineering |
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Viganò, E., Hertweck, C., Heitz, C., & Loi, M. (2022). People are not coins : morally distinct types of predictions necessitate different fairness constraints [Conference paper]. Faact ’22: Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency, 2293–2301. https://doi.org/10.1145/3531146.3534643
Viganò, E. et al. (2022) ‘People are not coins : morally distinct types of predictions necessitate different fairness constraints’, in Faact ’22: Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency. New York: Association for Computing Machinery, pp. 2293–2301. Available at: https://doi.org/10.1145/3531146.3534643.
E. Viganò, C. Hertweck, C. Heitz, and M. Loi, “People are not coins : morally distinct types of predictions necessitate different fairness constraints,” in Faact ’22: Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency, Jun. 2022, pp. 2293–2301. doi: 10.1145/3531146.3534643.
VIGANÒ, Eleonora, Corinna HERTWECK, Christoph HEITZ und Michele LOI, 2022. People are not coins : morally distinct types of predictions necessitate different fairness constraints. In: Faact ’22: Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency. Conference paper. New York: Association for Computing Machinery. 23 Juni 2022. S. 2293–2301. ISBN 9781450393522
Viganò, Eleonora, Corinna Hertweck, Christoph Heitz, and Michele Loi. 2022. “People Are Not Coins : Morally Distinct Types of Predictions Necessitate Different Fairness Constraints.” Conference paper. In Faact ’22: Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency, 2293–2301. New York: Association for Computing Machinery. https://doi.org/10.1145/3531146.3534643.
Viganò, Eleonora, et al. “People Are Not Coins : Morally Distinct Types of Predictions Necessitate Different Fairness Constraints.” Faact ’22: Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency, Association for Computing Machinery, 2022, pp. 2293–301, https://doi.org/10.1145/3531146.3534643.
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