Re-centering End Users in Artificial Intelligence and Decision Support: Examples in Maternal Health Research

The use of automated decision support and artificial intelligence (AI) for health purposes is rapidly increasing. Several studies have assessed the attitudes of health professionals but far fewer have explored perspectives of patients. For example, OpenAI reports that over 230 million people ask ChatGPT health-related questions every week. Despite these tools’ potential, they present a great risk for intervention-generated inequity,  such that already disadvantaged groups may face greater disparities by benefiting less from new interventions. In this talk, we also argue that there is an ethical imperative to ensure patients understand how their data are being used, what AI may show, and what this means for their health. This talk will describe various user studies for maternal health regarding the implementation of clinical decision support and AI with a focus on equity. 

Dr. Natalie Benda is an Assistant Professor of Health Informatics in Columbia’s School of Nursing. She is cross trained in human factors engineering and health informatics, completing her PhD at the University at Buffalo in 2018 with Dr. Ann Bisantz. Dr. Benda’s program of research utilizes human factors methods to improve the quality, safety, and inclusivity of healthcare, with a special focus on developing health technologies and artificial intelligence (AI). Her work has been funded by NSF, NIH, and AHRQ and includes over 75 peer-reviewed publications.