Algorithmic Bias and Equal Protection: Rethinking Anti-Discrimination Law for the Age of Artificial Intelligence

Abstract

As artificial intelligence (AI) systems increasingly mediate access to credit,
employment, education, and criminal justice, algorithmic bias has emerged as a constitutional question of first order. Traditional equal protection jurisprudence—built upon intentional discrimination and suspect classifications—struggles to address structural harms generated by opaque and data-driven decision processes. This article examines how the Fourteenth Amendment’s Equal Protection Clause can be reinterpreted for an algorithmic state. It traces doctrinal limits of intent-based discrimination tests, evaluates the constitutional treatment of disparate-impact analysis, and explores the normative potential for algorithmic accountability within the existing constitutional framework. Drawing upon U.S. Supreme Court precedent, interdisciplinary scholarship, and comparative lessons from data-governance theory, the article argues for a reconstructed constitutional paradigm that embeds transparency, fairness, and algorithmic due process within equal protection analysis. Ultimately, it calls for the evolution of constitutional interpretation that recognizes algorithmic systems as potential instruments of state action demanding heightened scrutiny and procedural safeguards.