Citing AI Search Tools, including genAI
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See alsoIntroductionArtificial intelligence (AI) tools, including generative AI (GenAI) systems based on large language models (LLMs), are increasingly used in academic, clinical, research, and administrative settings. AI tools can support a range of activities, including drafting text, summarization, brainstorming, computer programming, and information synthesis. As their use becomes more widespread, clear acknowledgment and citation of AI-assisted work are important for maintaining academic integrity, transparency, and responsible scholarship. While best practices continue to evolve, a growing body of literature, publisher policies, and institutional guidance is emerging to support the appropriate use and reporting of AI tools. When citing AI-powered search and evidence synthesis tools such as Open Evidence and Perplexity, users should follow established guidance for citing software and digital tools in major citation styles. For biomedical publications, refer to the recommendations of the International Committee of Medical Journal Editors (ICMJE) and the principles underlying Vancouver style. Most citation styles recommend including the name of the AI company or developer, the name and version of the tool (if available), the date of access or interaction, and a persistent or shareable URL to the output when one is available. Users of citation management software such as EndNote may find that the Online Database or Web Page reference type provides the most suitable template for managing citations to AI-generated content. BackgroundAI-generated content differs from traditional scholarly outputs because it is produced dynamically in response to user prompts and does not represent a stable or verifiable publication record. As a result, AI tools are not typically treated as citable sources of authoritative information. Within academic practice, expectations for citing or acknowledging AI tools continue to evolve. However, emerging consensus across major style guides and publishers emphasizes the following principles:
Recommended PracticeWhen documenting AI use in academic work at UBC, consider the following guidance:
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ConclusionThe use of AI tools in academic and professional work requires transparent disclosure and responsible documentation. While citation practices continue to evolve, UBC users should prioritize clarity about how AI tools were used, ensure independent verification of outputs, and follow discipline-specific standards. This supports research integrity and aligns with best practices. Speak to a well-informed librarian. Artificial intelligence is rapidly reshaping how information is discovered, evaluated, synthesized, and communicated across higher education, health care, and research environments. Tools such as ChatGPT, Open Evidence, Perplexity and other AI-powered systems offer new opportunities to enhance productivity, support learning, and accelerate knowledge translation. At the same time, their use raises important questions about transparency, accountability, reproducibility, and the reliability of AI-generated outputs. As AI technologies evolve, users must remain critical and sceptical. AI tools should be viewed as aids to human judgment rather than substitutes for scholarly expertise, professional knowledge, or critical thinking. Clear disclosure and appropriate citation of AI-assisted work help readers understand how information was generated and ensure academic and clinical communication is trustworthy. Guidance on citing and acknowledging AI tools is still developing, and practices may differ across publishers, institutions, and disciplines. Researchers, students, clinicians, and librarians should consult the most current recommendations from journals, professional associations, and their institutions when using AI in their work. References
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