The Bias Problem

AI systems learn from historical data, and history carries bias. A model trained on biased decisions can reproduce those patterns at scale, not because it is malicious, but because biased data became its teacher.

This is not a rare edge case. Facial recognition has been measured with error rates up to about 34% for dark-skinned women versus under 1% for light-skinned men. Predictive policing algorithms disproportionately target minority neighborhoods because the arrest data they trained on was already biased.