Digital Pathology Scanners and Contextual Integrity

Abstract

Abstract We aim to bring both digital pathology in general and computational pathology in particular within the scope of Helen Nissenbaum’s theory of appropriate information transfer as contextual integrity. In Section 1, the main lines of the theory of contextual integrity are introduced, and reasons are given why it is not properly speaking a theory of privacy, but rather a theory of morally permissible information transfer in general. Then the theory is applied to uses of digitised pathology images for (a) patient-by-patient analysis (Section 2); and (b) computational pathology (Sections 3 and 4). Although big data exercises involving personal data are sometimes seen by Nissenbaum and colleagues as particular threats to existing data-sharing norms and other social norms, we claim that patient-by-patient digital pathology is riskier, at least in forms it has taken during the pandemic. At the end, we consider some risks in computational pathology that are due to the interaction between health institutions, particularly in the public sector, and commercial algorithm developers.

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