Title: To Sum Up: An Overview of Generative AI Text Summarization Tools for Literature Reviews

Introduction: The exponential growth of research literature is creating a massive information overload, making the traditional literature review increasingly challenging for researchers, clinicians, faculty, and students. Generative AI summarization tools offer a promising way to manage this information overload by condensing complex information into concise, accessible summaries. However, the wide range of available tools and the complexity of their underlying technology can make it difficult to assess their reliability and determine appropriate uses.

Description: This session provides a practical overview of AI summarization tools for health information professionals. Participants will learn how these tools function and what content they can summarize (e.g. reports, full-text articles). The presentation will also highlight the different ways that summarization capabilities are offered, either through standalone tools or as integrated features in other information resources. Examples will illustrate applications across various stages of the literature review process, such as identifying themes, comparing findings, and generating overviews of search results. The session will also address key limitations, such as accuracy, bias, and over-simplification, and offer guidance on responsible evaluation and use.

Outcomes: Attendees will gain a foundational understanding of generative AI summarization technologies and their potential role in researching and writing literature reviews. They will also learn practical strategies for evaluating, recommending, and integrating these tools into instruction/reference services and research consultations.