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Addressing algorithmic discrimination

Published: 17 December 2021 Publication History

Abstract

Considering the intersection of technical design and civil rights when building and using classification algorithms.

References

[1]
Ali, M. et al. Discrimination through optimization: How Facebook's ad delivery can lead to biased outcomes. In Proceedings of the ACM on Computer-Human Interaction 3, 199 (2019).
[2]
Angwin, J. et al. Machine bias. ProPublica (2016); https://bit.ly/3c1zXE2
[3]
Kim, P.T. Data-driven discrimination at work. William & Mary Law Review 58 (2017), 857.
[4]
Kim, P.T. Race-aware algorithms: Fairness, nondiscrimination and affirmative action. California Law Review 110 (2022).
[5]
Obermeyer, Z. et al. Dissecting racial bias in an algorithm used to manage the health of populations. Science 366 (2019), 447.

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      Published In

      cover image Communications of the ACM
      Communications of the ACM  Volume 65, Issue 1
      January 2022
      106 pages
      ISSN:0001-0782
      EISSN:1557-7317
      DOI:10.1145/3507640
      Issue’s Table of Contents
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 17 December 2021
      Published in CACM Volume 65, Issue 1

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