Intersectional Approach to Algorithmic Discrimination in Healthcare

The increasing use of AI in clinical decision-making offers powerful tools to address health challenges but also risks reinforcing inequalities. Clinical algorithms may reproduce intersectional discrimination arising from multiple protected grounds. While intersectionality is well established in social theory, it remains insufficient-ly operationalised in law and computer science. This book proposes an intersectional approach to developing and regulating AI-based clinical algorithms. Focusing on the EU and the US, it examines health disparities, algorithmic fairness, and antidiscrimination law, and proposes an intersectional fairness assessment frame-work for fair clinical AI.