Fairness Assessment

Fairness Assessment is a methodological framework within human-robot interaction evaluation that systematically identifies, measures, and evaluates biases in robotic systems' behaviors or decision-making processes to ensure equitable treatment across diverse user groups.

155

Publications

8.2K

Citations

598

Authors

292

Institutions

Publications per year

2017–2026

109

Authors

598

  1. JS
    Jakob Schoeffer

    The University of Texas at Austin, United States

    4 publications · 95 citations

    4

    h-index

  2. ZW
    Zhenjiang Wang

    Guangdong Academy of Agricultural Sciences, China

    3 publications · 46 citations

    3

    h-index

  3. JW
    Jennifer Wortman Vaughan

    Carnegie Mellon University, United States

    3 publications · 561 citations

    3

    h-index

  4. CJ
    Cornelius J. König

    Saarland University, Germany

    3 publications · 227 citations

    3

    h-index

  5. MJ
    Malte Jung

    Cornell University, United States

    3 publications · 61 citations

    3

    h-index

1–5 of 598

Venues

  1. arXiv (Cornell University)

    Repository · 9 publications · 161 citations

    9

    h-index

  2. AI and Ethics

    3 publications · 98 citations

    3

    h-index

  3. Computers in Human Behavior

    3 publications · 141 citations

    3

    h-index

  4. 2

    h-index

  5. SSRN Electronic Journal

    Repository · 2 publications · 45 citations

    2

    h-index

1–5