The global landscape of academic guidelines for generative AI and Large Language Models
arxiv(2024)
Abstract
The integration of Generative Artificial Intelligence (GAI) and Large
Language Models (LLMs) in academia has spurred a global discourse on their
potential pedagogical benefits and ethical considerations. Positive reactions
highlight some potential, such as collaborative creativity, increased access to
education, and empowerment of trainers and trainees. However, negative
reactions raise concerns about ethical complexities, balancing innovation and
academic integrity, unequal access, and misinformation risks. Through a
systematic survey and text-mining-based analysis of global and national
directives, insights from independent research, and eighty university-level
guidelines, this study provides a nuanced understanding of the opportunities
and challenges posed by GAI and LLMs in education. It emphasizes the importance
of balanced approaches that harness the benefits of these technologies while
addressing ethical considerations and ensuring equitable access and educational
outcomes. The paper concludes with recommendations for fostering responsible
innovation and ethical practices to guide the integration of GAI and LLMs in
academia.
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