Realistic Risks and Optimization Pathways of Artificial Intelligence in Enhancing Ideological and Political Education in Universities

Abstract

Generative artificial intelligence presents new opportunities for the digital and intelligent transformation of ideological and political education in higher education institutions. However, the inherent tension between its technical tool nature and the value-oriented goals of
ideological education has exposed numerous practical challenges in implementing digital-intelligent ideological education. Current developments in intelligent ideological education face risks such as distorted content generation, misalignment of values, imbalance in the educatorlearner relationship, weakened teacher leadership, erosion of education's public welfare character by profit-driven capital, and threats to ideological security. In response, this paper proposes optimization pathways focusing on strict control over content generation and dissemination,
clarifying the boundaries of technology in education, and regulating the biases introduced by capital and algorithms. The aim is to reconcile
the dialectical relationship between technological innovation and value guidance, address potential risks in digital-intelligent ideological education, and promote deeper integration between artificial intelligence and ideological education in universities, thereby enhancing the quality
and effectiveness of ideological education in the new era.