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On the Justified Use of AI Decision Support in Evidence-Based Medicine: Validity, Explainability, and Responsibility.
Holm, Sune.
Afiliación
  • Holm S; Department of Food and Resource Economics, University of Copenhagen, 1958Frederiksberg C, Denmark.
Camb Q Healthc Ethics ; : 1-7, 2023 Jun 09.
Article en En | MEDLINE | ID: mdl-37293823
When is it justified to use opaque artificial intelligence (AI) output in medical decision-making? Consideration of this question is of central importance for the responsible use of opaque machine learning (ML) models, which have been shown to produce accurate and reliable diagnoses, prognoses, and treatment suggestions in medicine. In this article, I discuss the merits of two answers to the question. According to the Explanation View, clinicians must have access to an explanation of why an output was produced. According to the Validation View, it is sufficient that the AI system has been validated using established standards for safety and reliability. I defend the Explanation View against two lines of criticism, and I argue that within the framework of evidence-based medicine mere validation seems insufficient for the use of AI output. I end by characterizing the epistemic responsibility of clinicians and point out how a mere AI output cannot in itself ground a practical conclusion about what to do.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Guideline / Prognostic_studies Idioma: En Revista: Camb Q Healthc Ethics Asunto de la revista: ETICA Año: 2023 Tipo del documento: Article País de afiliación: Dinamarca Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Guideline / Prognostic_studies Idioma: En Revista: Camb Q Healthc Ethics Asunto de la revista: ETICA Año: 2023 Tipo del documento: Article País de afiliación: Dinamarca Pais de publicación: Estados Unidos