ArticleJournal of the American Medical Informatics Association : JAMIA2021
Trust in AI: why we should be designing for APPROPRIATE reliance.
Article in Journal of the American Medical Informatics Association : JAMIA, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
28 citing papers in PubMed.
- Factors Associated With Pediatric Health Care Professionals' Intention to Adopt Socially Assistive Robots: Mixed Methods Study.Journal of medical Internet research · 2026Article
- Explainable Artificial Intelligence (XAI) in Medical Education: A Multi-Modal Framework for Enhancing Human-AI Collaboration.Research square · 2026Article
- Explainability in context: calibrating appropriate trust and reliance in artificial intelligence.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Determinants of Trust and Reliance on Artificial Intelligence in Clinical Settings: A Study on Physicians' Use of Large Language Model in Psychiatric Symptom Assessment.Psychiatry investigation · 2026Article
- Factors influencing the effectiveness of artificial intelligence-assisted decision-making in medicine: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Perception of AI Symptom Models in Oncology Nursing: Mixed Methods Evaluation Study.JMIR nursing · 2026Article
- Nursing Educators' Perceptions of AI in Research: Risks and Benefits.Nursing research and practice · 2026Article
- Identifying conceptual dimensions of trust in artificial intelligence from qualitative content analysis of open-ended responses.Discover artificial intelligence · 2026Article
- Medical students' perceptions of AI-based feedback and feedforward on communication skills in doctor-patient consultation - an acceptance study in a video-based simulation.Medical education online · 2025Article
- Factors Influencing the Effectiveness of AI-Assisted Decision-Making in Medicine: A Scoping Review.medRxiv : the preprint server for health sciences · 2025Article
- We Need a Healthcare System That Supports Patients and Health Professionals in Using AI (If They Choose).Journal of general internal medicine · 2025Article
- Psychological Factors Influencing Appropriate Reliance on AI-enabled Clinical Decision Support Systems: Experimental Web-Based Study Among Dermatologists.Journal of medical Internet research · 2025Article
- A Cross-sectional Study of Patient Perspectives on Artificial Intelligence: A Comparison of Somatic Versus Mental Health Care.Journal of general internal medicine · 2025Article
- Patient Perspectives on AI for Mental Health Care: Cross-Sectional Survey Study.JMIR mental health · 2024Article
- Public comfort with the use of ChatGPT and expectations for healthcare.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Leveraging large language models to foster equity in healthcare.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Artificial Intelligence in Anesthesiology: Field of Dreams or Fire Swamp? Preemptive Strategies for Optimizing Our Inevitable Future.Anesthesiology · 2024Article
- Patient and Caregiver Perceptions of an Interface Design to Communicate Artificial Intelligence-Based Prognosis for Patients With Advanced Solid Tumors.JCO clinical cancer informatics · 2024Article
- Visualizing machine learning-based predictions of postpartum depression risk for lay audiences.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Artificial intelligence, ChatGPT, and other large language models for social determinants of health: Current state and future directions.Cell reports. Medicine · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Use of artificial intelligence in healthcare, such as machine learning-based predictive algorithms, holds promise for advancing outcomes, but few systems are used in routine clinical practice. Trust has been cited as an important challenge to meaningful use of artificial intelligence in clinical practice. Artificial intelligence systems often involve automating cognitively challenging tasks. Therefore, previous literature on trust in automation may hold important lessons for artificial intelligence applications in healthcare. In this perspective, we argue that informatics should take lessons from literature on trust in automation such that the goal should be to foster appropriate trust in artificial intelligence based on the purpose of the tool, its process for making recommendations, and its performance in the given context. We adapt a conceptual model to support this argument and present recommendations for future work.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.