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The need for AI systems to provide explanations for their behaviour is nowwidely recognised as key to their adoption. In this paper, we examine theproblem of trustworthy AI and explore what delivering this means in practice,with a focus on healthcare applications. Work in this area typically treatstrustworthy AI as a problem of Human-Computer Interaction involving theindividual user and an AI system. However, we argue here that this overlooksthe important part played by organisational accountability in how people reasonabout and trust AI in socio-technical settings. To illustrate the importance oforganisational accountability, we present findings from ethnographic studies ofbreast cancer screening and cancer treatment planning in multidisciplinary teammeetings to show how participants made themselves accountable both to eachother and to the organisations of which they are members. We use these findingsto enrich existing understandings of the requirements for trustworthy AI and tooutline some candidate solutions to the problems of making AI accountable bothto individual users and organisationally. We conclude by outlining theimplications of this for future work on the development of trustworthy AI,including ways in which our proposed solutions may be re-used in differentapplication settings.

Holding AI to Account: Challenges for the Delivery of Trustworthy AI in Healthcare