group-fairness

This paper theoretically and empirically studies the relationship between counterfactual fairness (CF) and group fairness (GF) in image classification, introducing new CF evaluation datasets (CelebA-CF and LFW-CF). It finds that CF does not imply GF in images due to latent attributes correlated with sensitive attributes, and proposes Counterfactual Knowledge Distillation (CKD) to mitigate this.