AI Governance in Higher Education: A course design exploring regulatory, ethical and practical considerations
Weuts, Raphaël, Bleher, Johannes, Bleher, Hannah, Flores, Rozanne Tuesday, Xuanyang, Guo, Pujszo, Paweł, Almási, Zsolt
–arXiv.org Artificial Intelligence
As artificial intelligence (AI) systems permeate critical sectors, the need for professionals who can address ethical, legal and governance challenges has become urgent. Current AI ethics education remains fragmented, often siloed by discipline and disconnected from practice. This paper synthesizes literature and regulatory developments to propose a modular, interdisciplinary curriculum that integrates technical foundations with ethics, law and policy. We highlight recurring operational failures in AI - bias, misspecified objectives, generalization errors, misuse and governance breakdowns - and link them to pedagogical strategies for teaching AI governance. Drawing on perspectives from the EU, China and international frameworks, we outline a semester plan that emphasizes integrated ethics, stakeholder engagement and experiential learning. The curriculum aims to prepare students to diagnose risks, navigate regulation and engage diverse stakeholders, fostering adaptive and ethically grounded professionals for responsible AI governance.
arXiv.org Artificial Intelligence
Sep-17-2025
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