Artificial Intelligence Governance in Indonesian Education: Regulatory Analysis and the Strengthening of Academic Integrity in the Era of Generative AI
Abstract
The development of Generative Artificial Intelligence (Generative AI) technologies, such as ChatGPT, Gemini, Claude, and Copilot, has brought significant transformation to the Indonesian education sector. These technologies offer numerous benefits, including supporting personalized learning, enhancing the efficiency of educational administration, and facilitating the retrieval and processing of academic information. However, the increasing use of AI has also raised concerns regarding academic integrity, including AI-assisted plagiarism, information fabrication, excessive dependence on technology, and the decline of students’ critical thinking skills. These challenges highlight the necessity of an AI governance framework that can accommodate technological advancement while safeguarding fundamental academic values. This study aims to analyze the governance of Artificial Intelligence in Indonesian education through an examination of existing regulatory frameworks and to formulate a model for strengthening academic integrity in the era of Generative AI. The research employs a normative legal method using statutory, conceptual, and comparative approaches, supported by an extensive literature review of relevant legislation, legal doctrines, and scholarly publications. The findings reveal that AI regulation in Indonesia remains fragmented and sector-specific, lacking a comprehensive legal framework to govern the use of AI in educational settings. In contrast, regulatory practices in various countries emphasize the importance of transparency, accountability, personal data protection, fairness, and human oversight as fundamental principles of AI governance. Based on these findings, this study proposes a model for strengthening academic integrity through five key pillars: institutional policy development, AI literacy and digital ethics, transparency and accountability, adaptive learning and assessment design, and continuous monitoring and evaluation. This model is expected to serve as a foundation for developing educational policies that are adaptive, ethical, and responsible in responding to the rapid advancement of artificial intelligence technologies
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