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Limits of trust in medical AI.
Hatherley, Joshua James.
Afiliación
  • Hatherley JJ; School of Historical, Philosophical, and International Studies, Monash University, Clayton, VIC 3194, Australia joshua.hatherley@monash.edu.
J Med Ethics ; 46(7): 478-481, 2020 07.
Article en En | MEDLINE | ID: mdl-32220870
Artificial intelligence (AI) is expected to revolutionise the practice of medicine. Recent advancements in the field of deep learning have demonstrated success in variety of clinical tasks: detecting diabetic retinopathy from images, predicting hospital readmissions, aiding in the discovery of new drugs, etc. AI's progress in medicine, however, has led to concerns regarding the potential effects of this technology on relationships of trust in clinical practice. In this paper, I will argue that there is merit to these concerns, since AI systems can be relied on, and are capable of reliability, but cannot be trusted, and are not capable of trustworthiness. Insofar as patients are required to rely on AI systems for their medical decision-making, there is potential for this to produce a deficit of trust in relationships in clinical practice.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Confianza Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: J Med Ethics Año: 2020 Tipo del documento: Article País de afiliación: Australia Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Confianza Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: J Med Ethics Año: 2020 Tipo del documento: Article País de afiliación: Australia Pais de publicación: Reino Unido