Bias Detection
Bias Detection is a methodological construct in the ethics of automated decision-making that identifies systematic distortions in algorithmic outcomes attributable to prejudicial assumptions or skewed data representations, thereby distinguishing it from general error detection by focusing specifically on fairness-related deviations rooted in historical, social, or technical inequities.
556
Publications
54.6K
Citations
1.7K
Authors
689
Institutions
Publications per year
2017–2026
358
556
SYRCLE’s risk of bias tool for animal studies
Carlijn R. Hooijmans, Maroeska M. Rovers, Rob BM de Vries et al. · BMC Medical Research Methodology · 2014 · 4.1K citations · Full text
Solon Barocas, Andrew D. Selbst · SSRN Electronic Journal · 2016 · 2.1K citations · Full text
Certifying and Removing Disparate Impact
Michael Feldman, Sorelle A. Friedler, John Moeller et al. · 2015 · 1.8K citations
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University of Pennsylvania
Philadelphia, United States
12 h-index
24 publications
4.9K citations

University of Toronto
Toronto, Canada
9 h-index
12 publications
1.9K citations
Carnegie Mellon University
Pittsburgh, United States
9 h-index
24 publications
2K citations
Yale University
New Haven, United States
9 h-index
17 publications
2.2K citations

Centre National de la Recherche Scientifique
Paris, France
8 h-index
22 publications
1K citations
University of Southern California
Los Angeles, United States
8 h-index
13 publications
1.5K citations
Princeton University
Princeton, United States
8 h-index
21 publications
9.6K citations
Columbia University
New York, United States
8 h-index
21 publications
1.5K citations
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Repository · 40 publications · 1.3K citations
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Repository · 20 publications · 3K citations
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7 publications · 773 citations
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5 publications · 379 citations
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5 publications · 3.7K citations
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