On the Inequity of Predicting A While Hoping for B
Sendhil Mullainathan, Ziad Obermeyer
Abstract
Algorithms trained to predict mismeasured proxy variables can reproduce and scale up racial bias. This mechanism of algorithmic bias is distinct from others in the literature and harder to detect. We show this using examples from health care, but the forces we consider apply to a range of other important social sectors.
Topics & Concepts
Proxy (statistics)Racial biasComputer scienceMechanism (biology)Range (aeronautics)EconometricsScale (ratio)Data sciencePsychologyMachine learningSociologyEconomicsRacismEpistemologyGeographyEngineeringGender studiesPhilosophyAerospace engineeringCartographyArtificial Intelligence in Healthcare and EducationArtificial Intelligence in HealthcareHealth Systems, Economic Evaluations, Quality of Life