Ai Red-teaming

AI Red-Teaming is a systematic evaluative practice in artificial intelligence governance wherein adversarial testing methodologies are employed to proactively identify, analyze, and mitigate potential safety, security, and ethical risks in AI systems prior to deployment.

34

Publications

1.1K

Citations

185

Authors

23

Institutions

Publications per year

2017–2026

23

Variants

Ai Red Teaming

Authors

185

  1. CS
    Chwee Seng Choo

    DSO National Laboratories, Singapore

    6 publications · 91 citations

    6

    h-index

  2. HA
    Hussein A. Abbass

    UNSW Sydney, Australia

    4 publications · 119 citations

    4

    h-index

  3. PH
    Peter Henderson

    Butler University, United States

    2 publications · 60 citations

    3

    h-index

  4. EP
    Ethan Perez

    Rice University, United States

    3 publications · 382 citations

    3

    h-index

  5. CL
    Ching Lian Chua

    DSO National Laboratories, Singapore

    3 publications · 53 citations

    3

    h-index

1–5 of 185

Venues

  1. arXiv (Cornell University)

    Repository · 10 publications · 358 citations

    11

    h-index

  2. SSRN Electronic Journal

    Repository · 2 publications · 37 citations

    2

    h-index

  3. Winter Simulation Conference

    Conference · 2 publications · 26 citations

    2

    h-index

  4. 1

    h-index

  5. IEEE Transactions on Dependable and Secure Computing

    TDSC · 1 publications · 29 citations

    1

    h-index

1–5