Artificial Intelligence, Qualitative Analysis, and Implementation Research in Applied Health Settings

• In Event: 40264 - Advancing Sociological Practice through Computational Research and Community Engagement

Abstract

The rise of artificial intelligence (AI)–both traditional and generative–offers extraordinary opportunities to reimagine the future of work. For researchers implementing evidence-based interventions in applied health settings, AI has elicited intrigue as a technology to assist with qualitative analysis, a task that requires considerable human resources, namely time, labor, and expertise. Although qualitative approaches remain vital for implementation methodologies, these resource-intensive methods are often at odds with applied health research’s reliance on limited budgets, condensed timelines, and scarcity of qualitative research proficiency. Given these constraints, practitioners have turned to AI as a hopeful solution.

While scholars have begun exploring the effectiveness (Cristou 2023; Morgan 2023; Siiman et al. 2023; Wachinger et al. 2024) and ethics (Marshall and Naff 2023) of AI in qualitative analysis, in this talk, we consider implications of using AI to produce knowledge about people’s health and healthcare based on qualitatively collected data. Recognizing AI holds much promise, we demonstrate how sociology can help applied health researchers navigate this emerging and rapidly changing workplace landscape. First, drawing upon the sociology of knowledge, we identify key issues to consider when using AI for qualitative health research, as well as corresponding stakes. This includes issues related to power and bias in the research process. Next, we place this discussion within the context of qualitative methodology, focusing on the role of human cognition and emotions in qualitative analysis. Finally, we offer concrete strategies applied health researchers can employ in their qualitative analyses to adopt a rigorous and sociologically informed approach to AI workplace integration. While this talk aims to equip applied qualitative researchers with pragmatic tools—both methodological and conceptual—for leveraging AI in practice settings, we argue that academic sociology can also learn from these applied workplace trends and should integrate AI discussions and tools into methods curriculums and qualitative coursework.

Authors

• Valerie L. Chepp, Cleveland Clinic

• Lester H. Andrist, University of Maryland-College Park