The global landscape of academic guidelines for generative AI and LLMs

Abstract

The integration of generative AI and large language models (LLMs) in academia enhances access and collaboration but also raises concerns about misinformation and academic integrity. Analyzing 80 academic guidelines, we recommend balanced approaches for their responsible use in education.

Team

Junfeng Jiao, Saleh Afroogh, Kevin Chen, David Atkinson & Amit Dhurandhar

Acknowledgments

This research is funded by the National Science Foundation (NSF) under grant number 2125858. The authors express their gratitude for the NSF’s support, which made this study possible. Furthermore, in accordance with MLA (Modern Language Association) guidelines, we note the use of OpenAI’s applications for assistance in editing and brainstorming.

Author contributions

J.J. and S.A. conceived and developed the main idea, contributed to the conceptualization and methodology, and conducted both qualitative and quantitative analyses. K.C., D.A. and A.D. contributed to the methodology and carried out qualitative and quantitative analyses.

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For more information, please visit: https://www.nature.com/articles/s41562-025-02124-6