by Jacob Ladd | Apr 12, 2022 | Commentary |
Countless State and Federal regulations and statutes—not to mention the U.S. Constitution—prohibit discrimination against protected groups. However, AI systems might slip discrimination past current laws through “proxy discrimination” without new regulatory and statutory approaches. Today’s AI systems and algorithms are capable of dredging oceans of big data to find statistical proxies for protected characteristics and create algorithms that disparately impact protected groups. AI systems with such capabilities already exist in the fields of health and automobile insurance, lending, and criminal justice, among others. In Proxy Discrimination in the Age of Artificial Intelligence and Big Data, Anya E.R. Prince and Daniel Schwarcz address this particularly “pernicious” phenomenon of proxy discrimination. Current anti-discriminatory regimes which simply deny AI systems the ability to use the protected characteristics or the most inuitive proxies will fail in the face of increasingly sophisticated AI systems. They provide a coherent definition for proxy discrimination by AI: usage of a variable whose statistical significance for prediction “derives from its correlation with membership in a suspect class.” For instance, consider a hiring algorithm for a job where a person’s height is relevant to job performance, but where the algorithm does not have access to height data. In attempting to factor height, the algorithm might discover the correlation between height and sex, and correlations between sex and other data. This would be an example of proxy discrimination because the statistical significance of the other data derives from its correlation with sex, a protected class. Prince and Schwarcz first foray into the pre-AI system history of proxy discrimination, i.e. human actors intentionally using proxies to discriminate. This discussion is interesting...
