Algorithms as discrimination detectors.
algorithms
discrimination
machine learning
Journal
Proceedings of the National Academy of Sciences of the United States of America
ISSN: 1091-6490
Titre abrégé: Proc Natl Acad Sci U S A
Pays: United States
ID NLM: 7505876
Informations de publication
Date de publication:
01 12 2020
01 12 2020
Historique:
pubmed:
30
7
2020
medline:
30
7
2020
entrez:
30
7
2020
Statut:
ppublish
Résumé
Preventing discrimination requires that we have means of detecting it, and this can be enormously difficult when human beings are making the underlying decisions. As applied today, algorithms can increase the risk of discrimination. But as we argue here, algorithms by their nature require a far greater level of specificity than is usually possible with human decision making, and this specificity makes it possible to probe aspects of the decision in additional ways. With the right changes to legal and regulatory systems, algorithms can thus potentially make it easier to detect-and hence to help prevent-discrimination.
Identifiants
pubmed: 32723823
pii: 1912790117
doi: 10.1073/pnas.1912790117
pmc: PMC7720101
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
30096-30100Déclaration de conflit d'intérêts
The authors declare no competing interest.
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