Data Augmentation for Fairness

Augment data to reduce bias. Learn counterfactual data augmentation (swap protected attribute, keep label), demographic name swapping for NLP, image attribute editing for vision, eval guardrails, and the failure modes (label leakage, distribution shift, mode collapse) that mask but do not actually fix bias.