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https://dx.doi.org/10.48550/ar...
Article . 2021
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
DBLP
Article . 2022
Data sources: DBLP
DBLP
Article . 2021
Data sources: DBLP
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Conceptualising Contestability

Perspectives on Contesting Algorithmic Decisions
Authors: Henrietta Lyons; Eduardo Velloso; Tim Miller 0001;

Conceptualising Contestability

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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Keywords

FOS: Computer and information sciences, Computer Science - Computers and Society, Computers and Society (cs.CY)

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    popularity
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    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
66
Top 1%
Top 10%
Top 1%
Green
bronze