Algorithmic Bias

A powerful work by NYU professor, data scientist, and one of the few Black women AI researchers, Meredith Broussard. Reveals how tech neutrality is a myth and algorithms need accountability. From facial recognition only trained on lighter skin tones, to mortgage algorithms encouraging discriminatory lending, to dangerous feedback loops in medical diagnostic algorithms. Solution isn't making omnipresent tech more inclusive, but rooting out algorithms that target demographics as 'other.'

Safiya Umoja Noble begins with the stigmatization of Black girls in commercial search to expose how advertising markets, platform monopoly, and knowledge classification produce algorithmic oppression.

Cathy O’Neil explains how scoring, prediction, and risk models amplify existing inequalities across work, education, finance, and policing.