Building Trust: Public Priorities for Health Care AI Labeling
Building Trust: Public Priorities for Health Care AI Labeling
https://www.ajmc.com/view/building-trust-public-priorities-for-health-care-ai-labeling
Publish Date: 2026-01-27 16:00:00
Source Domain: www.ajmc.com
ABSTRACT
Objectives: Labeling and the use of model cards have been promoted as ways to increase transparency for multiple end users. This study aimed to identify key content for a health artificial intelligence (AI) tool label based on public perspectives and expectations.
Study Design: We used a mixed-methods study design, combining public deliberation and pre-/post surveys to inform participants about AI in health care and gather input on key information for a health AI tool label.
Methods: In 2024, we conducted 5 virtual community deliberations across Michigan, engaging 159 participants in facilitated small-group discussions that were qualitatively coded. Participants completed a 20-minute survey before and after the deliberation to assess changes in knowledge, attitudes, and trust regarding AI in health care.
Results: Participants prioritized information regarding privacy and security, health equity, and safety and effectiveness of AI tools for inclusion on a health AI tool label. An AI label is, therefore, a familiar and transparent mechanism to build trust and address patients’ desire for notification.
Conclusions: The findings highlight ethical gaps in using AI in health care settings and the value of publicly informed, patient-centered solutions. There is strong demand for clear, accessible information on how AI tools are used and their risks and benefits. A patient-informed label may address these ethical challenges and improve transparency, trust, and patient-centered communication as AI reshapes health care.
Am J Manag Care. 2026;32(1):e18-e24. https://doi.org/10.37765/ajmc.2026.89875
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Takeaway Points
Patients want transparency when artificial intelligence (AI) tools are used in their health care. We identified strong public support for a clear, accessible label that outlines benefits, risks, and equity implications of how AI is used.
- An AI label is a familiar and transparent mechanism to build trust and address patients’ desire for notification.
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