Vollständiger Abstract
Worum geht es in dieser Arbeit?
With the deep integration of artificial intelligence into ideological and political education in higher education institutions, innovative dynamics are stimulated. In contrast, multiple practical risks emerge simultaneously, including the mainstream ideological front being under attack, privacy breaches that violate students’ rights, algorithmic bias that exacerbates social discrimination, and standardized quantitative assessments that stifle natural talent. This paper argues that the pivotal approach for integrating artificial intelligence into ideological and political education lies in adhering to putting people first and innovating on the basis of what has worked in the past. Building upon this, systematic innovation pathways are explored: strengthening the mainstream ideological front, safeguarding students’ data security and privacy rights and interests, preventing algorithmic bias and social discrimination, and establishing a diverse evaluation framework based on Human-Machine Collaboration. Only through the coordinated implementation of these multiple pathways can artificial intelligence be guaranteed to function as a booster rather than a substitute for fostering virtue through education. Ultimately, high‑quality development of ideological and political education can be achieved under the unity of technological empowerment and value guidance.
Bibliografischer Nachweis
Publikationsdaten
- Autor:innen
- Meiling Liu, Yuxuan Liu
- Quelle
- Journal of Artificial Intelligence and Information
- Publikation
- 2026-01-01
- Band / Ausgabe
- Nicht angegeben
- Seiten
- Nicht angegeben
- ISSN / ISBN
- 3064-8033
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Zitierfähiger Nachweis
Meiling Liu, Yuxuan Liu (2026). Exploring Pathways for the Deep Integration of Artificial Intelligence into Ideological and Political Education in Higher Education Institutions. Journal of Artificial Intelligence and Information. https://doi.org/10.66069/ojspub.1137260817
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Lizenzhinweise: Lizenz 1