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  2. School of Engineering
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  4. Publikationen School of Engineering
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dc.contributor.authorViganò, Eleonora-
dc.contributor.authorHertweck, Corinna-
dc.contributor.authorHeitz, Christoph-
dc.contributor.authorLoi, Michele-
dc.date.accessioned2023-12-15T08:56:33Z-
dc.date.available2023-12-15T08:56:33Z-
dc.date.issued2022-06-23-
dc.identifier.isbn9781450393522de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/29380-
dc.description.abstractIn 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.de_CH
dc.language.isoende_CH
dc.publisherAssociation for Computing Machineryde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectFairness metricsde_CH
dc.subjectDiscriminationde_CH
dc.subjectDecision-makingde_CH
dc.subjectArtificial intelligencede_CH
dc.subjectFair predictionde_CH
dc.subjectMoral principlede_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.subject.ddc170: Ethikde_CH
dc.titlePeople are not coins : morally distinct types of predictions necessitate different fairness constraintsde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Datenanalyse und Prozessdesign (IDP)de_CH
zhaw.publisher.placeNew Yorkde_CH
dc.identifier.doi10.1145/3531146.3534643de_CH
zhaw.conference.details5th ACM Conference on Fairness, Accountability, and Transparency (FAccT), Seoul, Republic of Korea, 21–24 June, 2022de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end2301de_CH
zhaw.pages.start2293de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedingsFaact '22: Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparencyde_CH
zhaw.funding.snf187473de_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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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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