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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-21961
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dc.contributor.authorHertweck, Corinna-
dc.contributor.authorHeitz, Christoph-
dc.contributor.authorLoi, Michele-
dc.date.accessioned2021-03-11T16:10:18Z-
dc.date.available2021-03-11T16:10:18Z-
dc.date.issued2021-03-
dc.identifier.isbn978-1-4503-8309-7de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/21961-
dc.descriptionThe final publication is available in the ACM Digital Library via https://dl.acm.org/doi/10.1145/3442188.3445936.de_CH
dc.description.abstractA crucial but often neglected aspect of algorithmic fairness is the question of how we justify enforcing a certain fairness metric from a moral perspective. When fairness metrics are proposed, they are typically argued for by highlighting their mathematical properties. Rarely are the moral assumptions beneath the metric explained. Our aim in this paper is to consider the moral aspects associated with the statistical fairness criterion of independence (statistical parity). To this end, we consider previous work, which discusses the two worldviews "What You See Is What You Get" (WYSIWYG) and "We're All Equal" (WAE) and by doing so provides some guidance for clarifying the possible assumptions in the design of algorithms. We present an extension of this work, which centers on morality. The most natural moral extension is that independence needs to be fulfilled if and only if differences in predictive features (e.g. high school grades and standardized test scores are predictive of performance at university) between socio-demographic groups are caused by unjust social disparities or measurement errors. Through two counterexamples, we demonstrate that this extension is not universally true. This means that the question of whether independence should be used or not cannot be satisfactorily answered by only considering the justness of differences in the predictive features.de_CH
dc.language.isoende_CH
dc.publisherAssociation for Computing Machineryde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectFairnessde_CH
dc.subjectIndependencede_CH
dc.subjectStatistical parityde_CH
dc.subjectDistributive justicede_CH
dc.subjectBiasde_CH
dc.subject.ddc005: Computerprogrammierung, Programme und Datende_CH
dc.subject.ddc170: Ethikde_CH
dc.titleOn the moral justification of statistical parityde_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.doi10.1145/3442188.3445936de_CH
dc.identifier.doi10.21256/zhaw-21961-
zhaw.conference.details4th ACM Conference on Fairness, Accountability, and Transparency (FAccT), online, 3-10 March 2021de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end757de_CH
zhaw.pages.start747de_CH
zhaw.publication.statusacceptedVersionde_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedingsProceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparencyde_CH
zhaw.funding.snf187473de_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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Hertweck, C., Heitz, C., & Loi, M. (2021). On the moral justification of statistical parity [Conference paper]. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 747–757. https://doi.org/10.1145/3442188.3445936
Hertweck, C., Heitz, C. and Loi, M. (2021) ‘On the moral justification of statistical parity’, in Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. New York: Association for Computing Machinery, pp. 747–757. Available at: https://doi.org/10.1145/3442188.3445936.
C. Hertweck, C. Heitz, and M. Loi, “On the moral justification of statistical parity,” in Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, Mar. 2021, pp. 747–757. doi: 10.1145/3442188.3445936.
HERTWECK, Corinna, Christoph HEITZ und Michele LOI, 2021. On the moral justification of statistical parity. In: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. Conference paper. New York: Association for Computing Machinery. März 2021. S. 747–757. ISBN 978-1-4503-8309-7
Hertweck, Corinna, Christoph Heitz, and Michele Loi. 2021. “On the Moral Justification of Statistical Parity.” Conference paper. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 747–57. New York: Association for Computing Machinery. https://doi.org/10.1145/3442188.3445936.
Hertweck, Corinna, et al. “On the Moral Justification of Statistical Parity.” Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, Association for Computing Machinery, 2021, pp. 747–57, https://doi.org/10.1145/3442188.3445936.


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