Managing Artificial Intelligence Ethics in Higher Education: A Systematic Framework for Issues and Policy Recommendations

Abstract

The integration of artificial intelligence (AI) in higher education has raised significant ethical and governance challenges. Despite growing scholarly attention, systematic governance frameworks remain underdeveloped, creating a gap between rapid AI adoption and institutional capacity to manage ethical implications. Guided by PRISMA 2020 guidelines, this systematic review synthesizes 55 peer-reviewed studies from Web of Science (2022-2025) to examine: (1) ethical issues and risks, (2) governance frameworks and policies, (3) governance gaps and limitations, and (4) evidence-based recommendations. Findings reveal research predominantly focuses on individual-level ethical awareness, with privacy, academic integrity, and algorithmic bias most frequently addressed, while institutional governance studies remain scarce. Institutional responses are primarily reactive and provisional rather than strategic. Five persistent governance gaps were identified: limited governance capacity, fragmented coordination, low AI ethics literacy, underrepresentation of equity perspectives, and weak evaluation mechanisms. This study proposes four targeted recommendations: establishing centralized governance committees, developing mandatory ethics literacy programs, implementing systematic evaluation mechanisms, and ensuring equity-oriented approaches. These findings underscore the need for institutions to transition from ad hoc responses to comprehensive, integrated AI ethics frameworks that embed ethical principles into their institutional strategy, ensuring the responsible and equitable use of AI.