The Obstacles of Generative Artificial Intelligence to the Governance of Academic Misconduct and Countermeasures

生成式人工智能对学术不端治理的妨碍及对策

Abstract

Generative artificial intelligence (GenAI) has rapidly penetrated academic practice, reshaping how ideas are produced, drafted, and disseminated. While these tools can enhance efficiency, accessibility, and creativity in research and learning, they also pose new and complex obstacles to the governance of academic misconduct. This paper critically examines how GenAI challenges traditional norms, detection mechanisms, and regulatory frameworks for academic integrity. First, it analyzes the ways GenAI obscures authorship boundaries, facilitates AI-assisted plagiarism, contract cheating, and automated paper mills, and complicates the identification of data fabrication and falsification. Second, it explores institutional and technical governance dilemmas, including limitations of AI-detection tools, conflicts between privacy and surveillance in monitoring practices, and discrepancies between rapidly evolving technologies and slow-moving policy and legal responses. Based on this analysis, the paper proposes a multi-layered system of countermeasures. At the normative level, it calls for clear definitions of AI-assisted misconduct and updated codes of conduct that distinguish legitimate support from deceptive practices. At the institutional level, it recommends integrating GenAI literacy into research training, redesigning assessment and supervision practices, and strengthening whistleblowing and reporting mechanisms. At the technical level, it suggests combining AI-based detection tools with metadata tracking, authorship forensics, and transparent disclosure standards. Finally, at the governance level, it advocates collaborative regulation involving universities, journals, funding agencies, and technology providers to co-develop standards, audit mechanisms, and accountability frameworks. The study aims to provide a forward-looking roadmap for safeguarding academic integrity in an era of pervasive generative AI.