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Suspended responsibility: The trouble with integrating researchers into shared-responsibility models for machine learning-supported decisions

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Health:: An Interdisciplinary Journal for the Social Study of Health, Illness and Medicine

Published online on

Abstract

Health, Ahead of Print.
With the rise of machine learning-based decision support systems, the responsibility for potential errors is regularly questioned. Scholarly work regarding this issue has criticized a “responsibility gap,” that is, unattributable responsibility for the ...