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Extrinsic trust as a contractual framework for accountable AI in health care: viewpoint

Date
2026-03-05
Abstract
Artificial intelligence (AI) promises efficiency and equity in health care. However, adoption remains fragmented due to weak foundations of trust. This Viewpoint highlights the gap between intrinsic trust, based on interpretability, and extrinsic trust, based on functional validation. We propose a contractual framework between AI systems and users defined by 3 promises: reliability, scope and equity, and shift and uncertainty. Illustrated through a vignette, we show how health systems can operationalize these promises through structured evidence and governance, translating trustworthy AI into accountable clinical deployment.
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Description
Publisher
JMIR Publications
Citation
Journal of Medical Internet Research 28, e83903
Collections
Electronic & Computer Engineering
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Kelly_2026_Extrinsic.pdf
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Keywords
artificial intelligence, AI, explainable artificial intelligence, explainable AI, XAI, trust, machine learning, mental health, decision support system, intrinsic trust
ULRR Identifiers
https://hdl.handle.net/10344/31674
 https://doi.org/10.34961/19311
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Funding Information
Sustainable Development Goals
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License
Attribution-NonCommercial-ShareAlike 4.0 International
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