SUMMARY - Mitigating Bias Through Better Data
A healthcare algorithm trained on data from academic medical centers performs poorly for rural populations whose health patterns differ from urban teaching hospital patients. A facial recognition system achieves 99% accuracy on light-skinned faces but fails on darker-skinned faces because training data dramatically underrepresented people of color. A hiring algorithm learns that successful employees were predominantly male because historical data reflects decades of discriminatory hiring, not because men are actually better candidates.