Bracey, Solomon, Ainsworth, Ben, Alderman, Joseph, Banjeri, Chris, Chakraborti, Tapabrata, Cresswell, K, Davies, Alisha, Hellon, Vicky, Harbron, Chris, Kostopoulou, Olga, Karoune, Emma, Wyatt, Jeremy, MacArthur, Ben D. and Fuggle, Nicholas (2026) The ‘Hippocratic Oath’ for AI based clinical decision support systems. BMC Medical Informatics and Decision Making, 26 (1), [292]. (doi:10.1186/s12911-026-03474-5).
Abstract
Background: the implementation of Artificial Intelligence assisted Clinical Decision Support Systems (AI-CDSS) shows significant potential to improve healthcare. However, implementing AI-CDSS has many associated challenges. This article introduces the ‘Hippocratic Oath’ for AI which promotes safe and effective AI-CDSS development and implementation.
Methods: this paper summarises discussions which took place during the Turing-Roche Clinical AI Interest Group Joint Workshop. The workshop began with scoping lectures from AI experts, leading into focus group discussions of key themes surrounding AI-CDSS implementation. These include the ethics, trust, evaluation, regulation, human factors and challenges involved with implementing AI-CDSS into healthcare settings. Focus group outcomes, alongside insight from lectures, were used to formulate the arguments in this paper.
Results: this article presents a consensus definition of AI-CDSS and outlines a comprehensive table of implementation challenges alongside mitigation measures. It introduces the ‘Hippocratic Oath for AI’ and discusses its potential to promote safe and effective AI-CDSS implementation through addressing human factors and explainability.
Conclusions: the ‘Hippocratic Oath for AI’, can be used by AI-CDSS implementers and developers as a framework to mitigate challenges involved with implementing AI-CDSS into healthcare settings. This framework is likely to promote safe and effective implementation and maximise HCP uptake of the AI-CDSS. Through facilitating AI-CDSS use, this oath can transform health care practice via reducing medical errors, healthcare costs and improving patient outcomes.
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