Developing research questions and effective search strategies can be challenging, and the growing use of generative AI adds a new layer of complexity to the research process. While these tools can help you find, evaluate, and work with the health sciences literature, knowing when and how to use them effectively is not always straightforward. This workshop will explore how generative AI can complement traditional research methods while navigating important considerations around accuracy, transparency, privacy, and reliability.
Join us for a practical session exploring how generative AI can support the research and literature search process. Learn how to use AI to develop research questions, identify search terms, build database search strategies, discover and evaluate evidence, and plan for the publishing process, all while recognizing the limitations and risks of these tools.
Topics include:
- Developing research questions and search strategies with AI
- Finding keywords, synonyms, and subject headings with AI
- Exploring AI features in health sciences databases and search tools
- Using AI research tools like OpenEvidence, Gemini Notebook, and Elicit
- Evaluating AI-generated information and verifying citations
- Recognizing privacy, bias, hallucinations, and other risks
- Using AI responsibly in research and publishing
From coursework and literature reviews to clinical questions, research projects, teaching, and scholarly publishing, you will leave with practical strategies for using AI as a research assistant while knowing when to rely on library resources, authoritative sources, and your own critical judgment.
This session is designed for students, faculty, researchers, and clinicians across the health sciences. No prior experience with generative AI is required.