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Date of Award
5-6-2026
Document Type
Video Recording
Abstract
The rapidly evolving landscape of AI search engines offers the potential to streamline evidence synthesis projects by generating searches and providing immediate, synthesized answers within a single platform. However, the integrity of evidence-based practice depends on two critical elements: reproducibility of results and relevance of retrieved sources. This study evaluates two AI platforms by assessing citation accuracy and result replicability. Preliminary findings highlight limitations and risks in AI-assisted searching for evidence synthesis projects. The session provides practical guidance for librarians seeking to responsibly integrate AI tools into workflows while maintaining methodological rigor and transparency.
Recommended Citation
LaPreze, Dani, "Reproducibility and Utility of AI Search Tools in Evidence Synthesis: A Comparative Study of Consensus and Preplexity" (2026). 2026 Southeastern Conference (SEC) AI Library Summit. 19.
https://scholarsjunction.msstate.edu/sec-ai-2026/19
