Perceived risk and mitigation of AI-supported clinical decision-making among radiologists: an exploratory study
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Date
2026-05-19
Authors
Alshamrani, Abdullatif
Treacy, Stephen
Rowan, Wendy
O’Flaherty, Brian
England, Andrew
Journal Title
Journal ISSN
Volume Title
Publisher
Taylor and Francis Ltd.
Published Version
Abstract
Artificial intelligence (AI) promises to revolutionise radiology practices. However, the AI implementation to support clinical decision-making relies on radiologists’ understanding of associated risks, as it has a pivotal role in providing outstanding healthcare outcome delivery. This study aims to explore the perception of risks related to AI and how to mitigate them from radiologists’ perspective via semi-structured interviews for more in-depth information. Preliminary findings indicate that most of the literature for the most part focused on attitudes and beliefs. As a work in progress, it is significant to bridge gaps in terms of the limited of empirical studies on risk perceptions of AI and insufficient theoretical grounding. This Research-In-Progress paper has provided a research framework, methodology and anticipated contributions while also seeking insightful critique to strengthen the research argument and its significance.
Description
Keywords
Artificial intelligence , Behaviour , Clinical decision making , Mitigation , Perception of risk , Radiologists , TEO Framework , [CUBS] , [Medicine]
Citation
Alshamrani, A, Treacy, S, Rowan, W, O’Flaherty, B & England, A 2026, 'Perceived risk and mitigation of AI-supported clinical decision-making among radiologists: an exploratory study', Journal of Decision Systems, vol. 35, no. 1, 2664010, pp. 1-5. https://doi.org/10.1080/12460125.2026.2664010