生成式AI在个性化学习资源智能化推荐中的伦理风险与治理框架

Ethical Risks and Governance Framework of Generative AI in Intelligent Recommendation of Personalized Learning Resources

摘要: 本文以生成式AI在个性化学习资源推荐中的应用为研究对象，探讨其引发的伦理风险及治理路径。随着生成式AI技术在教育领域的快速渗透，数据隐私泄露、算法偏见、学术诚信危机等问题日益凸显，亟需系统性治理框架。基于案例分析与文献综述，研究提出多维治理方案：技术层面融合联邦学习与差分隐私保护数据安全，政策层面构建分级分类监管体系，教育层面通过教师AI素养培训与学生数字公民教育强化主体责任，行业层面倡导算法公平优化与开源社区共建。该框架为平衡AI教育创新与伦理风险提供了实践参考，对推动教育智能化健康发展和教育公平具有重要现实意义。

Abstract: This paper takes the application of generative AI in personalized learning resource recommendation as the research object, and discusses the ethical risks and governance paths caused by it. With the rapid penetration of generative AI technology in the education field, problems such as data privacy leakage, algorithmic bias, and academic integrity crisis are becoming increasingly prominent, and a systematic governance framework is urgently needed. Based on case analysis and literature review, this paper proposes a multi-dimensional governance scheme: integrating federated learning and differential privacy to protect data security at the technical level, building a hierarchical and classified supervision system at the policy level, strengthening the main responsibility through teachers’ AI literacy training and students’ digital citizenship education at the education level, and advocating fair optimization of algorithms and co-construction with open source communities at the industry level. This framework provides a practical reference for balancing AI education innovation and ethical risks, and is of great practical significance for promoting the healthy development of intelligent education and educational equity.