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Artificial intelligence and clinical decision support: clinicians’ perspectives on trust, trustworthiness, and liability
Medical Law Review
Swansea University Author: Caroline Jones
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Artificial intelligence (AI) could transform healthcare provision, possibly improving patient safety and clinician decision-making, and mitigating the effects of staff shortages. However, there are concerns - voiced by regulators and policy-makers - over whether AI and clinical decision support syst...
|Published in:||Medical Law Review|
Oxford University Press (OUP)
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Artificial intelligence (AI) could transform healthcare provision, possibly improving patient safety and clinician decision-making, and mitigating the effects of staff shortages. However, there are concerns - voiced by regulators and policy-makers - over whether AI and clinical decision support systems (CDSSs) are trusted by relevant stakeholders, and more importantly whether such tools are worthy of trust. Yet, the meaning ascribed to trust and trustworthiness is often implicit, and it may be unclear what or who is being trusted. We address these issues, focusing for the most part on the perspective(s) of clinicians. Empirical studies suggest clinicians’ concerns about the use of AI/CDSSs include the accuracy of advice given and potential legal liability if a patient is harmed. Onora O’Neill’s conceptualisation of trust and trustworthiness provides the framework for our analysis. Through unpacking and reflecting upon these two concepts we gain greater clarity over the meaning given to them by a range of stakeholders; minimise the extent to/ways in which stakeholders are talking at cross purposes; and maintain the value of trust and trustworthiness as useful concepts in debates around the use of AI and CDSSs.
Artificial intelligence, Clinical decision support, Clinicians’ perspectives, Liability, Trust, Trustworthiness
Faculty of Humanities and Social Sciences