Model Accountability

Model Accountability is a formal governance framework that specifies the mechanisms, responsibilities, and auditability procedures governing the development, deployment, and monitoring of machine learning models to ensure transparency, compliance, and answerability to stakeholders.

20

Publications

1K

Citations

88

Authors

49

Institutions

Publications per year

2017–2026

11

Authors

88

  1. SP
    Siani Pearson

    Hewlett-Packard (United States), United States

    2 publications · 50 citations

    2

    h-index

  2. MD
    Monica Di Fiore

    University of Bergen, Norway

    1 publications · 467 citations

    1

    h-index

  3. AT
    Anvith Thudi

    Vector Institute, Canada

    1 publications · 11 citations

    1

    h-index

  4. ES
    Erik S. Reinert

    Tallinn University of Technology, Estonia

    1 publications · 467 citations

    1

    h-index

  5. IM
    Ian Molloy

    IBM (United States), United States

    1 publications · 18 citations

    1

    h-index

1–5 of 88

Venues

  1. Policy & Governance Review

    1 publications · 14 citations

    1

    h-index

  2. The American Naturalist

    AN · 1 publications · 24 citations

    1

    h-index

  3. Huan jing ke xue= Huanjing kexue

    1 publications · 22 citations

    1

    h-index

  4. PLoS ONE

    1 publications · 12 citations

    1

    h-index

  5. European Journal of Operational Research

    1 publications · 23 citations

    1

    h-index

1–5