Explainable Fairness
Explainable Fairness is a methodological framework within algorithmic fairness that enables the transparent articulation of how and why fairness criteria are satisfied by a model, distinguishing itself from other fairness approaches through its emphasis on human-interpretable justifications for equitable outcomes.
34
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2.7K
Citations
96
Authors
49
Institutions
Publications per year
2017–2026
26
Parents
34
'It's Reducing a Human Being to a Percentage'
Reuben Binns, Max Van Kleek, Michael Veale et al. · 2018 · 577 citations · Full text
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49
University College London
London, United Kingdom
4 h-index
4 publications
883 citations
University of Oxford
Oxford, United Kingdom
3 h-index
15 publications
4.3K citations
University of Florida
Gainesville, United States
3 h-index
3 publications
210 citations
The Ohio State University
Columbus, United States
2 h-index
2 publications
270 citations
Elisava Barcelona School of Design and Engineering
Barcelona, Spain
1 h-index
1 publications
13 citations

University of Calgary
Calgary, Canada
1 h-index
4 publications
160 citations

Appalachian State University
Boone, United States
1 h-index
1 publications
67 citations

Alberta Children's Hospital
Calgary, Canada
1 h-index
1 publications
40 citations
1–8 of 49
Repository · 5 publications · 147 citations
5
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JOM · 2 publications · 181 citations
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Conference · 2 publications · 220 citations
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JMI · 1 publications · 40 citations
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1 publications · 28 citations
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