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Cited by 279Ethics and Social Impacts of AIGame Theory and Voting SystemsNames, Identity, and Discrimination Research

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Algorithmic Fairness

Kleinberg, Jon, Ludwig, Jens, Mullainathan, Sendhil, Rambachan, Ashesh·2018·AEA Papers and Proceedings
DOI 10.1257/pandp.20181018
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Abstract

Concerns that algorithms may discriminate against certain groups have led to numerous efforts to ‘blind’ the algorithm to race. We argue that this intuitive perspective is misleading and may do harm. Our primary result is exceedingly simple, yet often overlooked. A preference for fairness should not change the choice of estimator. Equity preferences can change how the estimated prediction function is used (e.g., different threshold for different groups) but the function itself should not change. We show in an empirical example for college admissions that the inclusion of variables such as race can increase both equity and efficiency.

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Research works printed but not linked: 2

  1. Selbst Andrew D., 2016, California Law Review, 104, 671
  2. Mullainathan Sendhil, 2017, Proceedings of the 8th Conference on Innovation in Theoretical Computer Science, 43, 1

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Metadata

Authors
Kleinberg, J., Ludwig, J., Mullainathan, S., & Rambachan, A.
Affiliations
  • Cornell University (US)
  • University of Chicago (US)
  • Harvard University (US)
ORCID
Venue
AEA Papers and Proceedings
Publisher
American Economic Association
Published
2018-05-01
Volume
108
Pages
22-27
ISSN
  • 2574-0768 (ISSN-L)
  • 2574-0776
DOI
10.1257/pandp.20181018
OpenAlex
W4248633940
Cited by
278
References
8
Citations by year
2026: 23 · 2025: 35 · 2024: 50 · 2023: 43 · 2022: 44 · 2021: 42 · 2020: 27 · 2019: 10 · 2018: 4
FWCI
41.26
Type
journal article
Language
en
Open access
closed
Locations
  • AEA Papers and Proceedings (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Game Theory and Voting Systems
  • Social Sciences › Sociology and Political Science › Names, Identity, and Discrimination Research
Keywords
algorithmic fairness, algorithmic discrimination, race, equity-efficiency trade-off, university admission, prediction function, thresholding, estimator selection, equity preferences

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