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Abstract

Artificial intelligence (AI) is reshaping healthcare, promising improved diagnostics, personalized treatments, and streamlined operations. Yet a lack of trust remains a persistent barrier to widespread adoption. This Perspective examines the web of trust in AI-assisted healthcare systems, exploring the relationships it shapes, the systemic inequalities it can reinforce, and the technical challenges it poses. We highlight the bidirectional nature of trust, in which both patients and providers must trust AI systems, while these systems rely on the quality of human input to function effectively. Using models of care-seeking behavior, we explore the potential of AI to affect patients’ decisions to seek care, influence trust in healthcare providers and institutions, and affect diverse demographic and clinical settings. We argue that addressing trust-related challenges requires rigorous empirical research, equitable algorithm design, and shared accountability frameworks. Ultimately, AI’s impact hinges not just on technical progress but on sustaining trust, which may erode if biases persist, transparency falters, or incentives misalign.

Details

Title
Trust in AI-assisted health systems and AI’s trust in humans
Author
Sagona, Madeline 1 ; Dai, Tinglong 2   VIAFID ORCID Logo  ; Macis, Mario 3 ; Darden, Michael 4 

 Johns Hopkins University, Bloomberg School of Public Health, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311); Johns Hopkins University, Hopkins Business of Health Initiative, Washington, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311) 
 Johns Hopkins University, Hopkins Business of Health Initiative, Washington, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311); Johns Hopkins University, Carey Business School, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311); Johns Hopkins University, School of Nursing, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311) 
 Johns Hopkins University, Hopkins Business of Health Initiative, Washington, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311); Johns Hopkins University, Carey Business School, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311); Johns Hopkins University, Berman Institute of Bioethics, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311) 
 Johns Hopkins University, Hopkins Business of Health Initiative, Washington, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311); Johns Hopkins University, Carey Business School, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311) 
Pages
10
Publication year
2025
Publication date
Dec 2025
Publisher
Nature Publishing Group
e-ISSN
30051959
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3225849541
Copyright
Copyright Nature Publishing Group Dec 2025