What is diagnosis in the age of artificial intelligence

The integration of artificial intelligence into clinical practice demands fundamental reconsideration of how we conceptualize diagnosis. Clinical and popular discourse often frames diagnosis as a "virtuoso model" emphasizing individual physician expertise, which inadequately addresses the complexities of human-AI collaboration and overlooks work on its distributed and social dimensions. We propose a pluralistic framework moving beyond this paradigm toward a model better suited for AI integration. Drawing from medical and cultural history, sociological analysis, and cognitive science, we identify four key shifts necessary to reconceptualize diagnosis for the AI context: recognizing diagnosis as distributed cognition rather than simply individual virtuosity; embracing metacognitive awareness for human-AI collaboration; acknowledging patients as diagnostic co-creators rather than passive subjects; and understanding diagnosis as contextual and culturally situated. Successful AI integration requires moving beyond viewing AI as threat or efficiency tool toward reconceptualizing diagnosis as a collaborative, technologically-mediated activity where clinicians function as interpreters, patients as co-creators, and AI as specialized partners with transparent limitations. This framework demands new approaches to medical education and human-computer interaction research to realize AI's potential while preserving essential human judgment.

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Publication Details

Journal
Diagnosis
Published
2026-04-16
DOI
https://doi.org/10.1515/dx-2025-0166
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

What is diagnosis in the age of artificial intelligence

Christine Cassel, Lakshmi Krishnan
Diagnosis
Artificial Intelligence in Healthcare and Education
article

What is diagnosis in the age of artificial intelligence

Christine Cassel, Lakshmi Krishnan
article en

Abstract

The integration of artificial intelligence into clinical practice demands fundamental reconsideration of how we conceptualize diagnosis. Clinical and popular discourse often frames diagnosis as a "virtuoso model" emphasizing individual physician expertise, which inadequately addresses the complexities of human-AI collaboration and overlooks work on its distributed and social dimensions. We propose a pluralistic framework moving beyond this paradigm toward a model better suited for AI integration. Drawing from medical and cultural history, sociological analysis, and cognitive science, we identify four key shifts necessary to reconceptualize diagnosis for the AI context: recognizing diagnosis as distributed cognition rather than simply individual virtuosity; embracing metacognitive awareness for human-AI collaboration; acknowledging patients as diagnostic co-creators rather than passive subjects; and understanding diagnosis as contextual and culturally situated. Successful AI integration requires moving beyond viewing AI as threat or efficiency tool toward reconceptualizing diagnosis as a collaborative, technologically-mediated activity where clinicians function as interpreters, patients as co-creators, and AI as specialized partners with transparent limitations. This framework demands new approaches to medical education and human-computer interaction research to realize AI's potential while preserving essential human judgment.

Diagnosis
University of California, San Francisco (US), Georgetown University (US), Georgetown University Medical Center (US)
Openalex Percentile: Top 8%
Artificial Intelligence in Healthcare and Education
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What is diagnosis in the age of artificial intelligence — Christine Cassel, Lakshmi Krishnan · Diagnosis (2026) | TGRS Research Map | TGRS