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Impact based fairness framework for socio-technical decision making
Umeå University, Faculty of Science and Technology, Department of Computing Science.
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0002-7788-3986
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0002-8423-8029
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0001-7409-5813
2023 (English)In: Proceedings of the 1st workshop on fairness and bias in AIco-located with 26th european conference on artificial intelligence (ECAI 2023) / [ed] Roberta Calegari; Andrea Aler Tubella; Gabriel González Castañe; Virginia Dignum; Michela Milano, CEUR-WS , 2023Conference paper, Published paper (Refereed)
Abstract [en]

Avoiding bias and understanding the consequences of artificial intelligence used in decision making is of high importance to avoid mistreatment and unintended harm. This paper aims to present an impact focused approach to model the information flow of a socio-technical decision system for analysis of bias and fairness. The framework roots otherwise abstract technical accuracy and bias measures in stakeholder effects and forms a scaffold around which further analysis of the socio-technical system and its components can be coordinated. Two example use-cases are presented and analysed.

Place, publisher, year, edition, pages
CEUR-WS , 2023.
Series
CEUR Workshop Proceedings, ISSN 16130073 ; 3523
Keywords [en]
decision-making system, Fairness, information-flow, socio-technical factors
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-217267Scopus ID: 2-s2.0-85177071301OAI: oai:DiVA.org:umu-217267DiVA, id: diva2:1815668
Conference
1st Workshop on Fairness and Bias in AI, AEQUITAS 2023, Krakow, 1 October, 2023.
Funder
EU, Horizon 2020, 101070363Available from: 2023-11-29 Created: 2023-11-29 Last updated: 2023-11-30Bibliographically approved

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fulltext(382 kB)150 downloads
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Brännström, MattiasJiang, LiliAler Tubella, AndreaDignum, Virginia

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
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  • Other style
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Language
  • de-DE
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  • nn-NB
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More languages
Output format
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  • text
  • asciidoc
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