Explainable Fairness

Explainable Fairness is a methodological framework within algorithmic fairness that enables the transparent articulation of how and why fairness criteria are satisfied by a model, distinguishing itself from other fairness approaches through its emphasis on human-interpretable justifications for equitable outcomes.

34

Publications

2.7K

Citations

96

Authors

49

Institutions

Publications per year

2017–2026

26

Authors

96

  1. JZ
    Jun Zhao

    University of Oxford, United Kingdom

    3 publications · 862 citations

    3

    h-index

  2. RB
    Reuben Binns

    University of Oxford, United Kingdom

    3 publications · 862 citations

    3

    h-index

  3. UL
    Ulrik Lyngs

    University of Oxford, United Kingdom

    3 publications · 862 citations

    3

    h-index

  4. MV
    Max Van Kleek

    University of Oxford, United Kingdom

    3 publications · 862 citations

    3

    h-index

  5. NS
    Nigel Shadbolt

    University of Southampton, United Kingdom

    3 publications · 862 citations

    3

    h-index

1–5 of 96

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 147 citations

    5

    h-index

  2. Journal of Management

    JOM · 2 publications · 181 citations

    2

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 2 publications · 220 citations

    2

    h-index

  4. Journal of Medical Imaging

    JMI · 1 publications · 40 citations

    1

    h-index

  5. Journal of Organization Design

    1 publications · 28 citations

    1

    h-index

1–5