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Generative AI

When and What to Cite from Generative AI

While some citation and referencing styles have published interim direction on how AI generated materials should be cited, many still do not have specific guidelines. In general, though, you should treat AI-generated materials as a non-recoverable source and/or akin to personal communication, and follow guidelines for how to cite those resource types with your chosen reference style.

Below are some suggestions on citing generative AI materials in some of the major citation styles. Please note that UBC Library has a more comprehensive guide on how (and when) to cite other resources here. As always, please be sure to check with your instructor if in doubt about when to cite AI and what style to use. 

Citing AI Generated Materials

AIs and Authorship

As of June 2023, several publishers have offered guidance on how AI tools should be considered for publications

  • Cambridge University Press states that AI must be declared and clearly explained, and does not meet the requirements for authorship in terms of accountability (Link to Cambridge Authorship and Contributorship Guidelines)
  • Taylor & Francis states that AI tools cannot be listed as an author, and their use must be acknowledge and documented appropriately (Link to Taylor and Francis AI Policy)
  • Nature and other Springer Journals advise that Large Language Models (LLMs) like ChatGPT will not be accepted as credited authors on research papers. However, researchers using LLM tools should document their use in the methods or acknowledgement section (Link to Nature statement on use of AI)
  • Science has created an Artificial Intelligence (AI) policy which states: “AI-assisted technologies [such as large language models (LLMs), chatbots, and image creators] do not meet the Science journals’ criteria for authorship... authors who use AI-assisted technologies as components of their research study or as aids in the writing or presentation of the manuscript should note this in the cover letter and in the methods section or acknowledgments section of the manuscript” (Link to Science statement)

Technical Standards

The Coalition for Content Provenance and Authenticity is developing an open technical standard for greater transparency in how media or documents have been altered. The MIT Technology Review has described this as a "nutritional label" for AI.