Citing generative AI tools in academic research is essential for maintaining transparency, academic integrity, and reproducibility. Acknowledging the use of AI tools helps clarify how information was generated or synthesized and allows readers to critically evaluate the influence of AI on the research process. Proper citation also distinguishes the researcher’s original contributions from machine-assisted outputs, supporting ethical scholarship.
"Within the contexts of education and research, and particularly within higher education, the citation has long been the standard tool for providing transparency and connection in the transfer of ideas across scholars, framing of arguments, and design of methodologies.
Unfortunately, citations do not fully meet the needs of today’s AI-enabled world. Citations emphasize the fixed form of a tangible output. This is incongruent with today’s generative AI systems, where the specific interplay of prompt, model, and model parameters creates a unique output that is not always repeatable, reproducible, or recallable, depending on the technology. Citations also focus on the ideas posed by an author, whereas generative AI can serve a variety of meaningful functions in the writing process, including researcher, editor, critic, collaborator, and more. While today’s citation practices do help provide some transparency, they are not sufficient, in and of themselves, to capture the varied ways AI tools function or are being used across contexts."
Weaver, K. D. (2024). The Artificial Intelligence Disclosure (AID) Framework: An introduction. College & Research Libraries News, 85(10), 407–411. https://doi.org/10.5860/crln.85.10.407
