TY - JOUR
T1 - Trust and AI in healthcare
T2 - a systematic review
AU - M. Astobiza, Aníbal
AU - Alonso, Marcos
AU - Ortega Lozano, Ramón
N1 - Publisher Copyright:
© The Author(s) under exclusive licence to Monash University 2025.
PY - 2025
Y1 - 2025
N2 - The use of Artificial Intelligence (AI) in healthcare is growing quickly and offers big improvements in medical diagnostics, treatment planning, and patient care. However, people often don’t trust AI systems, which prevents them from being widely used. This article looks at both the philosophical and practical issues of trust in healthcare AI systems. First, we provide an overview of the current state of AI in healthcare. Then, we review existing research on trust in technology. Based on our findings, we identify three main factors that affect trust in AI: Technology-Related Factors (transparency, reliability, safety), Healthcare Context Factors (how well AI fits into healthcare settings, proper training for professionals), and Individual User Factors (user experience and attitudes toward AI). Our results show that continuous human oversight, strong regulations, and ethical considerations are essential. Addressing these areas is key to making sure AI systems in healthcare are reliable, transparent, and trusted by both healthcare professionals and patients.
AB - The use of Artificial Intelligence (AI) in healthcare is growing quickly and offers big improvements in medical diagnostics, treatment planning, and patient care. However, people often don’t trust AI systems, which prevents them from being widely used. This article looks at both the philosophical and practical issues of trust in healthcare AI systems. First, we provide an overview of the current state of AI in healthcare. Then, we review existing research on trust in technology. Based on our findings, we identify three main factors that affect trust in AI: Technology-Related Factors (transparency, reliability, safety), Healthcare Context Factors (how well AI fits into healthcare settings, proper training for professionals), and Individual User Factors (user experience and attitudes toward AI). Our results show that continuous human oversight, strong regulations, and ethical considerations are essential. Addressing these areas is key to making sure AI systems in healthcare are reliable, transparent, and trusted by both healthcare professionals and patients.
KW - Artificial intelligence
KW - Bioethics
KW - Ethics
KW - Healthcare
KW - Medical ethics
KW - Trust
UR - https://www.scopus.com/pages/publications/105021409002
U2 - 10.1007/s40592-025-00272-z
DO - 10.1007/s40592-025-00272-z
M3 - Review article
AN - SCOPUS:105021409002
SN - 1321-2753
JO - Monash Bioethics Review
JF - Monash Bioethics Review
ER -
