Building Public Trust in Healthcare AI Tools: Insights from Michigan Community Deliberations

Abstract: The rapid development of artificial intelligence (AI) tools is driving their increasing application in healthcare. However, few studies have explored public perceptions and trust of AI technology and its effects in improving healthcare delivery and outcomes. We hypothesize that strong public trust in AI plays a crucial role in improving health delivery and outcomes. In 2024, we conducted five virtual democratic deliberations with Michigan residents (n = 159) to educate community members on the use of AI in healthcare, gather informed perspectives, and identify key informational elements for developing a health AI label. Each 5.5-hour deliberation session included educational presentations, small group sessions, and online pre- and post-deliberation surveys. Participants prioritized “Privacy and Security,” “Health Equity,” and “Safety and Effectiveness” as the most important label elements, emphasized the importance of transparency in the use of AI in their care, and saw public input as necessary for building trust in health AI. For this enrichment hub, we will replicate the AI tool label prioritization exercise. The session will begin with a 3-minute video about AI in healthcare, followed by instructions and a QR code to complete the AI tool label exercise. Next, results of the prioritization exercise will be presented, leading into a facilitated discussion to explore participant preferences for an AI tool label and refine their AI label priorities through a group consensus-building exercise. Finally, we will share findings from our community deliberation study to compare participant results with broader community preferences.

Keywords: Artificial Intelligence, Healthcare, Deliberative discussions