Search Like a Librarian: AI

Large language models (LLMs) use generative artificial intelligence (GenAI) to synthesize, summarize, predict, and generate large amounts of text and data to perform tasks in place of human effort. Because of its apparent ability to automate and speed up such tasks, GenAI is quickly being adapted into researcher workflows. Evidence synthesis is not immune or unique to this new technology, and some search tools have AI implemented into their platforms or products.  

A core step of most evidence syntheses is search, which traditionally was performed by a human and manually created from scratch or with the aid of existing search blocks known as hedges. AI can be used to create and modify these or to act as a starting place. Several AI platforms will be covered, with special emphasis on Elicit, which will be demonstrated.  

In this session, participants will gain insight into how GenAI is being incorporated into evidence synthesis tools, benefits and drawbacks to using such tools, and ethical considerations. This session is designed for students, clinicians, and researchers engaged in evidence-synthesis reviews or research projects who want to become more knowledgeable about how AI is being used in search.   

No prior AI search experience required. 

This workshop will be offered as an online session via Zoom. You must register for this workshop. You will receive a registration confirmation email, which includes the Zoom link. This workshop will  be recorded, and a copy of the slides will be emailed after the workshop concludes. 

Please email Travis Nace, travis.nace@temple.edu, with any questions. 

Workshop is recommended for: Undergraduate and graduate students, faculty, staff, and Temple Hospital staff.