生成式人工智能在高校教学中的法律风险与规制路径

Legal Risks and Regulatory Pathways of Generative Artificial Intelligence in Higher Education Teaching

摘要: 近年来生成式人工智能发展迅速，极大提高了高校教学中知识获取和传播的效率，但也对高校教学秩序与责任承担机制提出了新的挑战。与传统教育信息化工具相比，生成式人工智能不仅改变了教学资源的生产方式，还在一定程度上重塑了高校教学中的权利义务结构与责任分配逻辑。基于此，文章立足高校教学场景，阐述生成式人工智能进入高校教学后的主体关系重构，重点分析个人信息保护、著作权、新型学术不端以及责任认定四个方面的法律风险；并提出建立数据治理与知识产权审查机制、完善学术规范与教学评价机制、构建协同参与的责任配置机制的规制路径，以推动生成式人工智能在高校教学中的规范应用。

Abstract: In recent years, generative artificial intelligence has developed rapidly and has greatly improved the efficiency of knowledge acquisition and dissemination in higher education teaching. At the same time, it has also posed new challenges to the teaching order of universities and the mechanisms of responsibility allocation. Compared with traditional educational informatization tools, generative artificial intelligence not only changes the mode of production of teaching resources, but also, to a certain extent, reshapes the structure of rights and obligations as well as the logic of responsibility distribution in higher education teaching. Based on this, this paper, from the perspective of higher education teaching scenarios, explains the reconstruction of subject relationships after the introduction of generative artificial intelligence into university teaching, and focuses on analyzing four major legal risks, namely personal information protection, copyright, emerging forms of academic misconduct, and the determination of liability. On this basis, it proposes regulatory approaches including the establishment of data governance and intellectual property review mechanisms, the improvement of academic norms and teaching evaluation mechanisms, and the construction of a collaborative responsibility allocation mechanism, so as to promote the standardized application of generative artificial intelligence in higher education teaching.