Distribution, Recognition, and Just Medical AI

Abstract Medical artificial intelligence (AI) systems are value-laden technologies that can simultaneously encourage and discourage conflicting values that may all be relevant for the pursuit of justice. I argue that the predominant theory of healthcare justice, the Rawls-inspired approach of Norman Daniels, neither adequately acknowledges such conflicts nor explains if and how they can resolved. By juxtaposing Daniels’s theory of healthcare justice with Axel Honneth’s and Nancy Fraser’s respective theories of justice, I draw attention to one such conflict. Medical AI may improve the distribution of opportunity qua health while simultaneously mis-recognizing patients and thereby reducing their self-respect. I argue that justly resolving this conflict will at times require greater inclusion of those mis-recognized in deliberation about medical AI, and consider what such inclusion may entail.

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Publication Details

Journal
Philosophy & Technology
Published
2025-01-27
DOI
https://doi.org/10.1007/s13347-025-00842-3
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00

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article

Distribution, Recognition, and Just Medical AI

Zachary Daus
1 links
Philosophy & Technology
Artificial Intelligence in Healthcare and Education
article

Distribution, Recognition, and Just Medical AI

Zachary Daus
article en

Abstract

Abstract Medical artificial intelligence (AI) systems are value-laden technologies that can simultaneously encourage and discourage conflicting values that may all be relevant for the pursuit of justice. I argue that the predominant theory of healthcare justice, the Rawls-inspired approach of Norman Daniels, neither adequately acknowledges such conflicts nor explains if and how they can resolved. By juxtaposing Daniels’s theory of healthcare justice with Axel Honneth’s and Nancy Fraser’s respective theories of justice, I draw attention to one such conflict. Medical AI may improve the distribution of opportunity qua health while simultaneously mis-recognizing patients and thereby reducing their self-respect. I argue that justly resolving this conflict will at times require greater inclusion of those mis-recognized in deliberation about medical AI, and consider what such inclusion may entail.

Philosophy & TechnologyVol. 38(1)
Monash University (AU)
Monash University, Universität Wien
Openalex Percentile: Top 99%
Artificial Intelligence in Healthcare and Education
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