News / January 15, 2026

Workshop at SSWR 2026: Implementing LLMs for social work research

At the SSWR Annual Conference in Washington, DC, Nari Yoo (University of Michigan) and Cheng Ren (University at Albany, SUNY), with Gaurav Sinha (University of Georgia), led a workshop on implementing AI-based large language models for social work research.

The session covered three layers of working with LLMs as a researcher:

• Foundations: what large language models are and what they can and cannot do for text-heavy social work research tasks
• Local deployment of open-source models: running models on your own machine, which matters when data cannot leave a secure environment (case notes, clinical text, IRB-restricted data)
• Practical considerations: cost, reproducibility, validation, and the judgment calls involved in using LLMs responsibly in research

The local-deployment focus reflects a recurring theme in SIG conversations: much of the text data social work researchers care about is sensitive, and privacy-preserving workflows are a precondition for using these tools at all.