AI-Enhanced Social Work: Developing and Evaluating Retrieval-Augmented Generation (RAG) Support Systems
Brian E. Perron, Barbara Hiltz, Erin M. Khang, Sue Ann Savas
Abstract
This article introduces the application of retrieval-augmented generation (RAG) technology, aiming to enhance decision making and client support through artificial intelligence (AI)–enhanced tools. RAG addresses the critical challenge of ensuring accuracy and reliability in AI-generated content by integrating generative AI with domain-specific knowledge bases. Through a case study, we explore the development and assessment of a RAG-powered tool designed to improve faculty advising, highlighting the importance of collaboration between social workers and technologists. The adaptability of RAG to various social work challenges is discussed alongside considerations for the maintenance of the knowledge base. Our work underscores the potential of RAG to revolutionize social work practices by providing accurate and reliable information to serve individuals and communities better.