生成式人工智能融入高校思政课的潜在伦理风险及其应对策略研究

Research on Potential Ethical Risks and Countermeasures of Integrating Generative Artificial Intelligence into Ideological and Political Courses in Colleges and Universities

摘要: 思政课是高校落实立德树人根本任务的核心课程，同时也是高校思想政治工作的关键抓手和重要途径。在当前技术快速发展的背景下，生成式人工智能融入高校思政课成为一个需要辩证看待的议题。作为一种“智能技术工具”，生成式人工智能重塑思政时空场域，创新思政内容精准供给，优化思政评价体系，为高校思想政治理论课的改革与创新提供了重要支撑。然而，在其融入思政课的过程中，也面临智能算法技术缺陷、数据质量与安全隐患、教育主体异化与人工智能的越位、教育主体间情感联结弱化、技术理性僭越价值理性等不同维度的伦理挑战。因此，为不断强化技术应用的伦理规范，有效提升思政课教学质量和水平，必须构建生成式人工智能算法伦理风险全过程监管体系、构建高质量数据与全方位安全保障体系、强化教育主体与人工智能的协同共生、重建教育主体间的情感联结、坚守价值理性，防止技术理性僭越。

Abstract: Ideological and political education courses are the core curriculum for universities to fulfill the fundamental task of cultivating students’ moral character, and they are also a key lever and important approach for ideological and political work in universities. In the current context of rapid technological development, the integration of generative artificial intelligence (AI) into ideological and political education courses has become a topic that requires dialectical consideration. As an “intelligent technological tool”, generative AI reshapes the ideological and political education space-time field, innovates the precise supply of ideological and political content, optimizes the evaluation system of ideological and political education, and provides important support for the reform and innovation of ideological and political theory courses in universities. However, in the process of integrating it into ideological and political education courses, it also faces ethical challenges in different dimensions such as technical defects of intelligent algorithms, data quality and security risks, alienation of educational subjects and offside of AI, weakening of emotional connections between educational subjects, and the arrogation of technical rationality over value rationality. Therefore, in order to continuously strengthen the ethical norms of technological application and effectively improve the teaching quality and level of ideological and political education courses, it is necessary to construct a whole-process supervision system for the ethical risks of generative AI algorithms, build a high-quality data and comprehensive security guarantee system, strengthen the collaborative symbiosis between educational subjects and AI, rebuild emotional connections between educational subjects, adhere to value rationality, and prevent the arrogation of technical rationality.