Ai Transparency

AI Transparency is a governance framework that specifies the conditions under which the operations, data, models, and decision-making processes of artificial intelligence systems are made accessible, interpretable, and accountable to stakeholders, distinguishing it from related governance mechanisms by its focus on epistemic openness and informational disclosure in AI development and deployment.

546

Publications

40.8K

Citations

1.4K

Authors

685

Institutions

Publications per year

2017–2026

541

Authors

1.4K

  1. QV
    Q. Vera Liao

    Microsoft (Canada), Canada

    5 publications · 843 citations

    5

    h-index

  2. SL
    Stefan Larsson

    Lund University, Sweden

    3 publications · 514 citations

    4

    h-index

  3. HH
    Harry Hemingway

    University College London, United Kingdom

    5 publications · 153 citations

    4

    h-index

  4. OK
    Oddur Kjartansson

    Google (United States), United States

    4 publications · 485 citations

    4

    h-index

  5. ND
    Natalia Díaz-Rodríguez

    Universidad de Granada, Spain

    4 publications · 866 citations

    4

    h-index

1–5 of 1.4K

Venues

  1. arXiv (Cornell University)

    Repository · 21 publications · 607 citations

    17

    h-index

  2. AI & Society

    13 publications · 933 citations

    14

    h-index

  3. SSRN Electronic Journal

    Repository · 20 publications · 835 citations

    14

    h-index

  4. AI and Ethics

    8 publications · 856 citations

    12

    h-index

  5. Computer

    8 publications · 557 citations

    8

    h-index

1–5