Explainability Methods to Detect and Measure Discrimination in Machine Learning Models

Sofie Goethals, David Martens, Toon Calders. Explainability Methods to Detect and Measure Discrimination in Machine Learning Models. In Jose M. Alvarez, Alessandro Fabris, Christoph Heitz, Corinna Hertweck, Michele Loi, Meike Zehlike, editors, Proceedings of the 2nd European Workshop on Algorithmic Fairness, Winterthur, Switzerland, June 7th to 9th, 2023. Volume 3442 of CEUR Workshop Proceedings, CEUR-WS.org, 2023. [doi]

@inproceedings{GoethalsMC23,
  title = {Explainability Methods to Detect and Measure Discrimination in Machine Learning Models},
  author = {Sofie Goethals and David Martens and Toon Calders},
  year = {2023},
  url = {https://ceur-ws.org/Vol-3442/paper-11.pdf},
  researchr = {https://researchr.org/publication/GoethalsMC23},
  cites = {0},
  citedby = {0},
  booktitle = {Proceedings of the 2nd European Workshop on Algorithmic Fairness, Winterthur, Switzerland, June 7th to 9th, 2023},
  editor = {Jose M. Alvarez and Alessandro Fabris and Christoph Heitz and Corinna Hertweck and Michele Loi and Meike Zehlike},
  volume = {3442},
  series = {CEUR Workshop Proceedings},
  publisher = {CEUR-WS.org},
}