1. Adebayo, J.A.: FairML: ToolBox for diagnosing bias in predictive modeling. Master’s thesis, Massachusetts Institute of Technology (2016)
2. Adebayo, J.A.: FairML: auditing black-box predictive models (2017)
3. Aïvodji, U., Arai, H., Fortineau, O., Gambs, S., Hara, S., Tapp, A.: Fairwashing: the risk of rationalization. In: ICML, pp. 161–170 (2019)
4. Aïvodji, U., Ferry, J., Gambs, S., Huguet, M., Siala, M.: Learning fair rule lists. CoRR abs/1909.03977 (2019). http://arxiv.org/abs/1909.03977
5. Angelino, E., Larus-Stone, N., Alabi, D., Seltzer, M., Rudin, C.: Learning certifiably optimal rule lists for categorical data. J. Mach. Learn. Res. 18, 234:1–234:78 (2017)