2025
When majority rules, minority loses: bias amplification of gradient descent
NeurIPS 2025poster
Despite growing empirical evidence of bias amplification in machine learning, its theoretical foundations remain poorly understood. We develop a formal framework for majority-minority learning tasks, showing how standard training can favor majority groups and produce stereotypical predictors that ne…