This track examines the ethical, legal, social, and institutional challenges associated with AI-supported education. It welcomes research on fairness, bias, privacy, transparency, explainability, accountability, safety, accessibility, and academic integrity. Contributions may address governance frameworks, regulation, standards, procurement, auditing, and responsible innovation. The track also considers the effects of AI on educational equity, professional roles, institutional practices, and learner rights. Interdisciplinary studies connecting technology, pedagogy, ethics, law, and public policy are strongly encouraged.

Focus: Frameworks and practices for ensuring that educational AI is trustworthy, equitable, transparent, and accountable. The track aims to connect responsible system design with effective governance and evidence-informed policy.