The Privacy-Bias Tradeoff: Data Minimization and Racial Disparity Assessments in U.S. Government
This academic paper examines how federal privacy laws restrict data collection needed for assessing racial disparities, creating a tradeoff between protecting individual privacy and enabling algorithmic fairness in government programs.
The paper investigates how the U.S. government’s long-standing commitment to data minimization, rooted in privacy law, hinders its ability to assess and address racial disparities in public services.
Through case studies of federal agencies and responses to Executive Order 13985, it documents significant institutional, legal, and technical barriers to collecting demographic data for equity assessments. The authors offer concrete policy recommendations, such as amending the Privacy Act, enhancing data infrastructure, and enabling limited inter-agency data sharing to reconcile privacy protections with fairness goals in government decision-making.
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