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Analysis of the Impact of Generative Artificial Intelligence on Research Integrity Governance in Jiangsu Higher Education Institutions

Author(s)

Tiantian Zhou, Wen Xin*, Liting Lu, Xu Zhao

Affiliation(s)

School of Artificial Intelligence and Software, Ke Wen College of Jiangsu Normal University, Xuzhou, Jiangsu, China *Corresponding Author

Abstract

This paper delves into the application of generative artificial intelligence (AI) technologies in research settings at universities in Jiangsu Province, systematically analyzing their multidimensional impacts on research integrity governance. Findings reveal that generative AI presents opportunities such as technological innovations in detection and enhanced management efficiency, while simultaneously posing challenges including the concealment of academic misconduct, blurred intellectual property boundaries, and lagging governance standards. Through case studies and empirical analysis at institutions like Southeast University and Nanjing University, the paper proposes establishing a "technology - institutional - cultural" collaborative governance framework. This framework encompasses developing intelligent detection tools, refining strategies and regulations, and strengthening ethics education to address emerging issues stemming from technological advancement. The study aims to drive innovation and refinement in Jiangsu universities' research integrity governance systems. These findings hold significant theoretical and practical implications for enhancing research integrity governance and ensuring the healthy development of scientific endeavors in Jiangsu higher education institutions.

Keywords

Generative AI; Jiangsu Universities; Research Integrity Governance; Academic Misconduct; Collaborative Governance

References

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