As students and faculty increasingly rely on LLM AI tools to support their research, they risk being fed hallucinated citations masking as scholarly sources. If not caught, these can propagate and amplify misinformation, poison scholarly databases, and lead to reputational consequences for scholars. This presentation will help attendees understand what AI hallucinated citations are and how they can go about verifying sources provided to them by AI tools. This talk will also encourage attendees to consider the limits in scope that large language models offer as tools to find scholarly sources and ways to go beyond these models to locate scholarship.

Facilitator: Natalie Ornat Bitting is the Humanities Librarian and an Associate Professor at J. Murrey Atkins Library and holds a Master’s of Science in Library Science (MSLS) from UNC-Chapel Hill. In her role as a research and instruction librarian, she frequently works with students and faculty on how to locate, evaluate, and use scholarly sources for their research.

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