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Fairness and accountability design needs for algorithmic support in high-stakes public sector decision-making

Abstract:

Calls for heightened consideration of fairness and accountability in algorithmically-informed public decisions—like taxation, justice, and child protection—are now commonplace. How might designers support such human values? We interviewed 27 public sector machine learning practitioners across 5 OECD countries regarding challenges understanding and imbuing public values into their work. The results suggest a disconnect between organisational and institutional realities, constraints and needs, ...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Publisher copy:
10.1145/3173574.3174014

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
Publisher:
Association for Computing Machinery Publisher's website
Publication date:
2018-04-21
Acceptance date:
2018-02-12
DOI:
Pubs id:
pubs:827820
URN:
uri:971b98f0-a4ae-4220-ab53-5fbea0296633
UUID:
uuid:971b98f0-a4ae-4220-ab53-5fbea0296633
Local pid:
pubs:827820

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