1. Angwin, J., Larson, J., Mattu, S., Kirchner, L.: Machine bias: there’s software used across the country to predict future criminals, and it’s biased against blacks (2016). https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
2. Calders, T., Verwer, S.: Three Naive Bayes approaches for discrimination-free classification. Data Min. Knowl. Discov. 21(2), 277–292 (2010)
3. Chouldechova, A.: Fair prediction with disparate impact: a study of bias in recidivism prediction instruments. Big Data 5(2), 153–163 (2017)
4. Corbett-Davies, S., Goel, S.: The measure and mismeasure of fairness: a critical review of fair machine learning. arXiv preprint arXiv:1808.00023 (2018)
5. Deb, K.: Multi-objective Optimization Using Evolutionary Algorithms. Wiley, New York (2002)