Regulating AI in Nursing Education: Legal and Ethical Challenges of Clinical Decision Support Systems in Indonesia and Malaysia

Abstract

The rapid integration of artificial intelligence (AI) in healthcare education, particularly through Clinical Decision Support Systems (CDSS), has raised critical questions concerning legal adequacy, ethical governance, and institutional accountability. This study examines the regulatory and institutional readiness of Indonesia and Malaysia in governing the ethical use of AI-based CDSS in nursing education. Adopting a normative legal research approach, this study examines primary legal instruments, national policy frameworks, ethical codes, and institutional documents relevant to AI governance in educational contexts. The comparative findings demonstrate a significant disparity between the two countries. Malaysia exhibits a higher level of regulatory preparedness, supported by national AI strategies, ethical guidelines, and structured institutional mechanisms that facilitate the responsible deployment of AI in nursing curricula. Conversely, Indonesia lacks a sector-specific legal framework and institutional protocols, resulting in fragmented practices and normative uncertainty. The study further demonstrates significant variation in institutional responses to algorithmic accountability, professional responsibility, and the protection of care practices grounded in human values within artificial intelligence supported learning environments. These findings underscore the critical importance of coherent legal frameworks and institutional capacity in enabling ethically sound AI integration. The paper concludes by recommending the development of sector-specific regulations, the establishment of interdisciplinary oversight mechanisms, and the implementation of standardized ethical protocols to ensure that AI adoption in nursing education enhances, rather than undermines, professional integrity and ethical accountability.