Recommendations for Social Work Researchers and Journal Editors on the Use of Generative AI and Large Language Models

Abstract

Generative artificial intelligence (AI) and large language models (LLMs) are poised to significantly impact social work research. These technologies can produce high-quality written materials and support qualitative and quantitative data analysis with simple, plain-language prompts from users. However, they also introduce challenges, such as potential bias, data privacy concerns, and generation of misinformation. In this paper, we use a disruptive–disrupting framework to discuss the dual nature of generative AI and LLMs and offer recommendations for social work researchers and journal editors that include guidance around data collection, analysis, interpretation, and dissemination. Researchers must use great caution when deploying generative AI technologies, meticulously examining, verifying, and taking accountability for the text and analyses produced by these instruments. Likewise, journal editors will need to implement quality control procedures and ethical standards to guide and evaluate the use of these technologies in social work research. We consider the recommendations offered here as a point of departure for disciplinary conversations about the role of generative AI and LLMs in social work research.