Computer Science > Machine Learning
arXiv:2106.00467 (cs)
[Submitted on 1 Jun 2021 (v1), last revised 11 Mar 2022 (this version, v4)]
Title:A Clarification of the Nuances in the Fairness Metrics Landscape
Authors:Alessandro Castelnovo,Riccardo Crupi,Greta Greco,Daniele Regoli,Ilaria Giuseppina Penco,Andrea Claudio Cosentini
View a PDF of the paper titled A Clarification of the Nuances in the Fairness Metrics Landscape, by Alessandro Castelnovo and 5 other authors
View PDFAbstract:In recent years, the problem of addressing fairness in Machine Learning (ML) and automatic decision-making has attracted a lot of attention in the scientific communities dealing with Artificial Intelligence. A plethora of different definitions of fairness in ML have been proposed, that consider different notions of what is a "fair decision" in situations impacting individuals in the population. The precise differences, implications and "orthogonality" between these notions have not yet been fully analyzed in the literature. In this work, we try to make some order out of this zoo of definitions.
| Comments: | 26 pages, 7 figures, 2 tables, title updated: previous title was "The Zoo of Fairness metrics in Machine Learning", authors updated |
| Subjects: | Machine Learning (cs.LG); Computers and Society (cs.CY); Machine Learning (stat.ML) |
| Cite as: | arXiv:2106.00467 [cs.LG] |
| (orarXiv:2106.00467v4 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2106.00467 arXiv-issued DOI via DataCite | |
| Journal reference: | Sci Rep 12, 4209 (2022) |
| Related DOI: | https://doi.org/10.1038/s41598-022-07939-1 DOI(s) linking to related resources |
Submission history
From: Daniele Regoli [view email][v1] Tue, 1 Jun 2021 13:19:30 UTC (182 KB)
[v2] Fri, 11 Jun 2021 21:34:17 UTC (182 KB)
[v3] Mon, 13 Dec 2021 07:25:35 UTC (191 KB)
[v4] Fri, 11 Mar 2022 06:57:19 UTC (175 KB)
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View a PDF of the paper titled A Clarification of the Nuances in the Fairness Metrics Landscape, by Alessandro Castelnovo and 5 other authors
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