Auditability Of Algorithms

Auditability of Algorithms is a methodological construct within robo-advisory regulation that enables systematic verification and assessment of algorithmic decision-making processes by providing transparent, traceable, and reproducible records of algorithmic operations and governance.

40

Publications

3.2K

Citations

117

Authors

65

Institutions

Publications per year

2017–2026

37

Variants

Algorithmic Auditability

Authors

117

  1. ID
    Inioluwa Deborah Raji

    University of California, Berkeley, United States

    7 publications · 996 citations

    7

    h-index

  2. BV
    Briana Vecchione

    Data & Society Research Institute, United States

    3 publications · 73 citations

    3

    h-index

  3. SB
    Shea Brown

    University of Iowa, United States

    3 publications · 236 citations

    3

    h-index

  4. JD
    Jovana Davidovic

    University of Iowa, United States

    3 publications · 236 citations

    3

    h-index

  5. PT
    Philip Treleaven

    University College London, United Kingdom

    3 publications · 228 citations

    3

    h-index

1–5 of 117

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 242 citations

    4

    h-index

  2. SSRN Electronic Journal

    Repository · 3 publications · 167 citations

    3

    h-index

  3. Proceedings of the ACM on Human-Computer Interaction

    PACMHCI · 3 publications · 209 citations

    3

    h-index

  4. 2022 ACM Conference on Fairness, Accountability, and Transparency

    Conference · 2 publications · 221 citations

    2

    h-index

  5. 2

    h-index

1–5