Algorithmic Bias

Algorithmic Bias is a systematic and unfair distortion in the outputs of an algorithmic system that results from the design, data, or deployment context, thereby differentiating it from general computational errors or statistical inaccuracies by its ethical and societal implications in decision-making processes.

440

Publications

45.4K

Citations

1.4K

Authors

646

Institutions

Publications per year

2017–2026

418

Variants

Algorithmic Discrimination

Authors

1.4K

  1. SM
    Sendhil Mullainathan

    University of Chicago, United States

    6 publications · 206 citations

    6

    h-index

  2. EF
    Emilio Ferrara

    University of Southern California, United States

    5 publications · 924 citations

    5

    h-index

  3. JK
    Jon Kleinberg

    Cornell University, United States

    5 publications · 910 citations

    5

    h-index

  4. CC
    Carlos Castillo

    Yahoo (Spain), Spain

    4 publications · 453 citations

    4

    h-index

  5. SA
    Shahriar Akter

    University of Wollongong, Australia

    4 publications · 755 citations

    4

    h-index

1–5 of 1.4K

Venues

  1. SSRN Electronic Journal

    Repository · 22 publications · 3.4K citations

    18

    h-index

  2. arXiv (Cornell University)

    Repository · 22 publications · 904 citations

    17

    h-index

  3. Communications of the ACM

    6 publications · 761 citations

    6

    h-index

  4. Internet Policy Review

    4 publications · 223 citations

    4

    h-index

  5. Scientific Reports

    4 publications · 328 citations

    4

    h-index

1–5