Algorithmic Hiring Bias

Algorithmic Hiring Bias is a systematic error in hiring outcomes arising from the design, data, or deployment of algorithmic decision-making systems that disproportionately disadvantages certain demographic groups, thereby perpetuating or amplifying existing social inequities in employment practices.

22

Publications

1.8K

Citations

41

Authors

26

Institutions

Publications per year

2017–2026

21

Authors

41

  1. KL
    Karen Levy

    Cornell University, United States

    2 publications · 773 citations

    2

    h-index

  2. SB
    Solon Barocas

    Cornell University, United States

    2 publications · 773 citations

    2

    h-index

  3. MR
    Manish Raghavan

    Cornell University, United States

    2 publications · 773 citations

    2

    h-index

  4. IA
    Ifeoma Ajunwa

    Internet Society, United States

    2 publications · 125 citations

    2

    h-index

  5. JK
    Jon Kleinberg

    Cornell University, United States

    2 publications · 773 citations

    2

    h-index

1–5 of 41

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 175 citations

    2

    h-index

  2. Journal of Business Ethics

    2 publications · 115 citations

    2

    h-index

  3. SSRN Electronic Journal

    Repository · 2 publications · 125 citations

    2

    h-index

  4. Online Information Review

    1 publications · 118 citations

    1

    h-index

  5. AI Ethics Journal

    AIEJ · 1 publications · 17 citations

    1

    h-index

1–5