Formalising Anti-Discrimination Law in Automated Decision Systems
Keywords: Law and Machine Learning, Law and AI, Anti-Discrimination Law, Justice, AI Governance, Algorithmic Fairness, Algorithmic Bias
Abstract: We study the legal challenges in automated decision-making by analysing conventional algorithmic fairness approaches and their alignment with anti-discrimination law in the United Kingdom and other jurisdictions based on English common law. By translating principles of anti-discrimination law into a decision-theoretic framework, we formalise discrimination and propose a new, legally informed approach to developing systems for automated decision-making. Our investigation reveals that while algorithmic fairness approaches have adapted concepts from legal theory, they can conflict with legal standards, highlighting the importance of bridging the gap between automated decisions, fairness, and anti-discrimination doctrine.
Primary Area: Fairness
Submission Number: 2866
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