University of Cambridge > > Departmental Seminars in History and Philosophy of Science > Algorithmic diagnosis and the problem of statistical evidence

Algorithmic diagnosis and the problem of statistical evidence

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Disease detecting algorithms with superior accuracy are becoming available. From a societal point of view, higher diagnostic accuracy could enable more efficient use of healthcare resources. From a patient point of view, higher accuracy could improve health outcomes for patients. If we can reasonably expect that an algorithmic diagnostic procedure will be more accurate than one involving human diagnosticians, it is pertinent to ask whether we should sometimes substitute algorithms for human diagnosticians? In this talk I discuss whether there is a principled epistemological argument against a diagnostic procedure that relies wholly on a disease detection algorithm shown to have superior accuracy. My discussion focuses on the purely statistical nature of algorithmic diagnosis and connects algorithmic diagnosis to the extensive literature on the epistemology of statistical evidence and its use in court.

This talk is part of the Departmental Seminars in History and Philosophy of Science series.

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