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Conceptualising Contestability: Perspectives on Contesting Algorithmic Decisions

Authors:

Henrietta Lyons,

Eduardo Velloso,

Tim MillerAuthors Info & Claims

Proceedings of the ACM on Human-Computer Interaction, Volume 5, Issue CSCW1

Article No.: 106, Pages 1 - 25

https://doi.org/10.1145/3449180

Published: 22 April 2021 Publication History

Abstract

As the use of algorithmic systems in high-stakes decision-making increases, the ability to contest algorithmic decisions is being recognised as an important safeguard for individuals. Yet, there is little guidance on what 'contestability'--the ability to contest decisions--in relation to algorithmic decision-making requires. Recent research presents different conceptualisations of contestability in algorithmic decision-making. We contribute to this growing body of work by describing and analysing the perspectives of people and organisations who made submissions in response to Australia's proposed 'AI Ethics Framework', the first framework of its kind to include 'contestability' as a core ethical principle. Our findings reveal that while the nature of contestability is disputed, it is seen as a way to protect individuals, and it resembles contestability in relation to human decision-making. We reflect on and discuss the implications of these findings.

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Balayn APi YWidder DAlfrink KYurrita MUpadhyay SKarusala NLyons HTurkay CTessono CAttard-Frost BGadiraju UFarzan RLópez CCardoso Llach DQuercia DMustafa MNiu SWong-Villacrés M(2024)From Stem to Stern: Contestability Along AI Value ChainsCompanion Publication of the 2024 Conference on Computer-Supported Cooperative Work and Social Computing10.1145/3678884.3681831(720-723)Online publication date: 11-Nov-2024
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Index Terms

Conceptualising Contestability: Perspectives on Contesting Algorithmic Decisions
1. Human-centered computing
  1. Human computer interaction (HCI)

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cover image Proceedings of the ACM on Human-Computer Interaction

Proceedings of the ACM on Human-Computer Interaction Volume 5, Issue CSCW1

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April 2021

5016 pages

EISSN:2573-0142

DOI:10.1145/3460939

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Published: 22 April 2021

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Alharbi RLor PHerskovitz JSchoenebeck SBrewer R(2024)Misfitting With AI: How Blind People Verify and Contest AI ErrorsProceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility10.1145/3663548.3675659(1-17)Online publication date: 27-Oct-2024
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