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Towards a Flexible Framework for Algorithmic Fairness

dc.contributor.authorHacker, Philipp
dc.contributor.authorWiedemann, Emil
dc.contributor.authorZehlike, Meike
dc.contributor.editorReussner, Ralf H.
dc.contributor.editorKoziolek, Anne
dc.contributor.editorHeinrich, Robert
dc.date.accessioned2021-01-27T13:34:34Z
dc.date.available2021-01-27T13:34:34Z
dc.date.issued2021
dc.description.abstractIncreasingly, scholars seek to integrate legal and technological insights to combat bias in AI systems. In recent years, many different definitions for ensuring non-discrimination in algorithmic decision systems have been put forward. In this paper, we first briefly describe the EU law framework covering cases of algorithmic discrimination. Second, we present an algorithm that harnesses optimal transport to provide a flexible framework to interpolate between different fairness definitions. Third, we show that important normative and legal challenges remain for the implementation of algorithmic fairness interventions in real-world scenarios. Overall, the paper seeks to contribute to the quest for flexible technical frameworks that can be adapted to varying legal and normative fairness constraints.en
dc.identifier.doi10.18420/inf2020_09
dc.identifier.isbn978-3-88579-701-2
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/34803
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofINFORMATIK 2020
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-307
dc.subjectalgorithmic fairness
dc.subjectoptimal transport
dc.subjectdiscrimination
dc.subjectalgorithmic affirmative action
dc.subjectEU law
dc.titleTowards a Flexible Framework for Algorithmic Fairnessen
gi.citation.endPage108
gi.citation.startPage99
gi.conference.date28. September - 2. Oktober 2020
gi.conference.locationKarlsruhe
gi.conference.sessiontitleEthik und KI

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