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Paper short abstract

We report some results from a longitudinal, qualitative study of the adoption of AI-based diagnostic support tools in histopathology. We focus, in particular, on issues these tools raise in regard to their accountability, transparency and trustworthiness in everyday diagnostic work.

Paper long abstract

In this paper we present the findings of a two year qualitative study of the work of histopathologists and their experiences of trialling an AI-based clinical decision support tool, which works by drawing the attention of the histopathologist to the presence of suspicious lesions in digitised tissue biopsies, in their everyday work in the detection and diagnosis of prostate cancer. We document changing work practices; the experiences with different AI-based diagnostic tools; the strengths; weaknesses and anomalies observed in terms of productivity, measurement and reassurance; and the extent to which the AI systems meet histopathologists’ expectations. We use the findings of this study to further examine the recursive relationship between human action and the wider organisational and system context. We are especially interested in some key issues regarding the impact of AI tools on the nature of diagnostic work, and how these foreground emerging issues concerning the nature of accountability, transparency and trust – interpersonal, organisational and trust in technology – that appear crucial to the successful adoption of this type of technological innovation within clinical settings.