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Black box problem and African views of trust

Medicine and Health

Black box problem and African views of trust

C. Ewuoso

Explore how African scholarship on trust sheds light on the opaque nature of clinical artificial intelligence in healthcare. This research by Cornelius Ewuoso unveils the relational and normative challenges that black box AI presents in health professional-patient relationships, raising critical questions about accountability and transparency.

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~3 min • Beginner • English
Abstract
This article draws on the thinking about trust in African scholarship to describe the problems black box clinical artificial intelligence (AI) generates in health professional-patient relationships. Notably, under the assumption of a black box problem, the view of trust as inherently relational implies that health professionals cannot explain whether and how a clinical AI incorporates a patient's values or leverages the same (in its outputs) to honour fiduciary relations. Additionally, the African view of trust as experience-based and accepting responsibility implies that health professionals can neither be held accountable for black box clinical AI outputs that they can hardly understand nor provide material information (concerning what the clinical AI does and why). Finally, given the understanding of trust as a normative concept, health professionals cannot accept patients' vulnerabilities, and patients cannot give the same. Given that trust will play a vital role in the global acceptance of clinical AI, future studies should research—from other positionalities—how the black box problem will challenge the relationship of trust in the medical context.
Publisher
Humanities and Social Sciences Communications
Published On
Oct 14, 2023
Authors
Cornelius Ewuoso
Tags
trust
artificial intelligence
healthcare
patient relationships
opacity
accountability
transparency
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