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Impact based fairne...
Impact based fairness framework for socio-technical decision making
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- Brännström, Mattias (author)
- Umeå universitet,Institutionen för datavetenskap
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- Jiang, Lili (author)
- Umeå universitet,Institutionen för datavetenskap
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- Aler Tubella, Andrea, 1990- (author)
- Umeå universitet,Institutionen för datavetenskap
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- Dignum, Virginia, Professor (author)
- Umeå universitet,Institutionen för datavetenskap
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(creator_code:org_t)
- CEUR-WS, 2023
- 2023
- English.
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In: Proceedings of the 1st workshop on fairness and bias in AIco-located with 26th european conference on artificial intelligence (ECAI 2023). - : CEUR-WS.
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Abstract
Subject headings
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- 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.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Keyword
- decision-making system
- Fairness
- information-flow
- socio-technical factors
Publication and Content Type
- ref (subject category)
- kon (subject category)
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