Cautious optimism: clinician perspectives on barriers and expectations surrounding AI integration in healthcare

Journal article

Background.
The rapid integration of artificial intelligence (AI) into clinical decisionmaking has been accompanied by ongoing debates around fairness, transparency, and trust. However, few studies have captured how these ethical tensions are perceived and negotiated by frontline clinicians, whose insights are essential for responsible AI implementation.
Methods.
Semi-structured interviews were conducted to explore the perspectives of 15 clinicians regarding the fairness and accuracy of healthcare AI systems. Reflective thematic analysis was used to analyze the data.
Results.
Our findings identify a critical but underexplored paradox: while transparency is considered indispensable for informed consent and trust, excessive disclosure can overwhelm patients, reduce confidence, and create cognitive strain for clinicians. Clinicians valued AI as a decision-support tool but highlighted risks of over-reliance, potential biases from non-inclusive datasets, and the erosion of interpersonal care.
Conclusion.
Ultimately, clinicians advocate AI as a supportive tool designed to enhance, rather than replace, human judgment and interpersonal patient interactions.

Authors: Tovmasyan, A; Mittelstadt, B; Weinstein, N

• Publication status: Accepted
• Peer review status: Peer reviewed
• Publisher: Wiley
• Journal: Advances in Public Health
• Acceptance date: 2026-08-21
• EISSN: 2314-7784
• ISSN: 2356-6868
• Language: English
• Keywords: healthcare AI; transparency; fairness; patient-centred care