Patient perspectives

What patients think about AI use in their healthcare and resources for integrating patients into the AI deployment process.

Collective AI Rights for Patients

The Light Collective. Collective AI Rights for Patients. 2024 Jun.

This document by the Light Collective establishes a framework of seven fundamental rights for patients regarding how AI in healthcare is used. This includes transparency, self-determination, and legal accountability. The Light Collective advocates for patient-led governance and a strict loyalty to improving patient outcomes to ensure that AI technologies are safe, equitable and aligned with the real world needs and values of the communities they serve.

Factors for Patient Trust and Acceptance of Medical Artificial Intelligence

Bracic A, Spector-Bagdady K, Towle S, et al. Factors for patient trust and acceptance of medical AI. JAMA Netw Open. 2026;9(3):e260815.

This survey examines factors associated with patient trust regarding medical artificial intelligence. For a hypothetical AI-assisted diagnosis scenario, respondents were presented with two visit options defined by a combination of six randomized attributes, including a clinician making the final decision, AI performance, governance, and AI data quality. Respondents explained their choices and rated their trust in the resulting diagnosis. Respondents were 18.4% more likely to choose a visit with a clinician involved as opposed to AI use without a clinician. Respondents also preferred: 1) AI with some form of governance rather than no governance at all, and 2) AI trained on a US population dataset over an AI for which they received no training data information. Overall, AI performance was the most significant factor, with participants showing more trust in AI that had the performance level of a specialist or more than a specialist in the field. These findings suggest that combining key factors such as AI performance, clinician presence, disclosure of representative data, and systemic governance is important in increasing patient trust in medical AI.