Fundamental Limits of Fairness Interventions in Machine Learning: Separating Aleatoric and Epistemic Discrimination
The fairness Pareto frontier delineates the optimal performance achievable by a classifier under group fairness constraints, separating inherent biases in the data distribution (aleatoric discrimination) from biases introduced by algorithmic choices (epistemic discrimination).