
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).


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fundamental-limits-of-fairness-interventions-in-machine-learning-separating-aleatoric-and-epistemic-discrimination


Fundamental Limits of Fairness Interventions in Machine Learning: Separating Aleatoric and Epistemic Discrimination
