The unseen Black faces of AI algorithms

An audit of commercial facial-analysis tools found that dark-skinned faces are misclassified at a much higher rate than are faces from any other group. Four years on, the study is shaping research, regulation and commercial practices. Pivotal study of facial recognition algorithms revealed racial bi...

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Bibliographic Details
Published inNature (London) Vol. 610; no. 7932; pp. 451 - 452
Main Author Birhane, Abeba
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 20.10.2022
Nature Publishing Group
Subjects
631/114/1305
639/705/117
639/705/258
706/689/179
Algorithms
Artificial intelligence
Automation
Bias
Computer vision
Consumer protection
Datasets
Deep learning
Furuncles
Humanities and Social Sciences
Machine learning
multidisciplinary
News And Views
Pattern recognition
Science
Software
United States > US
San Francisco California
California
Computer science
Ethics
Information technology
Machine learning
Online AccessGet full text
ISSN0028-0836
1476-4687
1476-4687
DOI10.1038/d41586-022-03050-7

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Summary:An audit of commercial facial-analysis tools found that dark-skinned faces are misclassified at a much higher rate than are faces from any other group. Four years on, the study is shaping research, regulation and commercial practices. Pivotal study of facial recognition algorithms revealed racial bias.
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ISSN:0028-0836
1476-4687
1476-4687
DOI:10.1038/d41586-022-03050-7