Responsible Governance of Artificial Intelligence in the Design and Delivery of Higher Education Curricula in Vietnam
DOI:
https://doi.org/10.65150/EP-jmrr/V2E10/2026-07Keywords:
Artificial intelligence, AI governance, responsible AI, higher education, curriculum, data protection, Vietnam.Abstract
Purpose: This study examines the risks that artificial intelligence (AI) creates across the curriculum lifecycle in higher education and identifies the governance mechanisms required for its responsible adoption in Vietnam.
Design/methodology/approach: The study combines a literature review, qualitative document analysis, and comparative policy benchmarking of the UNESCO Recommendation on the Ethics of Artificial Intelligence, the OECD AI Principles, the European Union Artificial Intelligence Act, and Vietnam’s Law on Artificial Intelligence, Law on Personal Data Protection, and National Artificial Intelligence Ethics Framework.
Findings: AI can support needs analysis, learning outcome mapping, personalized learning pathways, instructional delivery, and assessment. However, its use gives rise to six groups of risks: personal data violations, algorithmic bias, lack of transparency and explicability, diffused accountability, unequal access, and the erosion of academic autonomy. Vietnam established a general legal and ethical foundation for AI governance in 2025–2026; the main remaining gap lies in translating these general provisions into operational procedures specific to higher education.
Practical implications: The study proposes a ten-step, lifecycle-based governance framework comprising problem definition, risk classification, data mapping, impact assessment, pedagogical validation, technical and fairness testing, controlled piloting, accountable approval, post-deployment monitoring, and audit or discontinuation, together with a tiered allocation of responsibilities and the evidence required at each step.
Originality/value: The framework links international principles and Vietnam’s newly enacted legal requirements to the concrete stages of curriculum design and delivery, providing higher education institutions and policymakers with a practical basis for transparent, fair, and accountable AI adoption that preserves academic integrity and learner autonomy.
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