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In principle obstacles for empathic AI: why we can’t replace human empathy in healthcare

What are the limits of the use of artificial intelligence (AI) in the relational aspects of medical and nursing care? There has been a lot of recent work and applications showing the promise and efficiency of AI in clinical medicine, both at the research and treatment levels. Many of the obstacles d...

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Detalles Bibliográficos
Autores principales: Montemayor, Carlos, Halpern, Jodi, Fairweather, Abrol
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer London 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8149918/
https://www.ncbi.nlm.nih.gov/pubmed/34054228
http://dx.doi.org/10.1007/s00146-021-01230-z
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author Montemayor, Carlos
Halpern, Jodi
Fairweather, Abrol
author_facet Montemayor, Carlos
Halpern, Jodi
Fairweather, Abrol
author_sort Montemayor, Carlos
collection PubMed
description What are the limits of the use of artificial intelligence (AI) in the relational aspects of medical and nursing care? There has been a lot of recent work and applications showing the promise and efficiency of AI in clinical medicine, both at the research and treatment levels. Many of the obstacles discussed in the literature are technical in character, regarding how to improve and optimize current practices in clinical medicine and also how to develop better data bases for optimal parameter adjustments and predictive algorithms. This paper argues that there are also in principle obstacles to the application of AI in clinical medicine and care where empathy is important, and that these problems cannot be solved with any of the technical and theoretical approaches that shape the current application of AI in specific areas of clinical medicine in which care for patients is fundamental. This is important, because it generates specific risks that may be overlooked otherwise, and it justifies the necessity of human monitoring and emotional intervention in clinical medicine. Consequently, difficult issues concerning moral and legal responsibility may ensue if these in principle problems are ignored.
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spelling pubmed-81499182021-05-26 In principle obstacles for empathic AI: why we can’t replace human empathy in healthcare Montemayor, Carlos Halpern, Jodi Fairweather, Abrol AI Soc Original Article What are the limits of the use of artificial intelligence (AI) in the relational aspects of medical and nursing care? There has been a lot of recent work and applications showing the promise and efficiency of AI in clinical medicine, both at the research and treatment levels. Many of the obstacles discussed in the literature are technical in character, regarding how to improve and optimize current practices in clinical medicine and also how to develop better data bases for optimal parameter adjustments and predictive algorithms. This paper argues that there are also in principle obstacles to the application of AI in clinical medicine and care where empathy is important, and that these problems cannot be solved with any of the technical and theoretical approaches that shape the current application of AI in specific areas of clinical medicine in which care for patients is fundamental. This is important, because it generates specific risks that may be overlooked otherwise, and it justifies the necessity of human monitoring and emotional intervention in clinical medicine. Consequently, difficult issues concerning moral and legal responsibility may ensue if these in principle problems are ignored. Springer London 2021-05-26 2022 /pmc/articles/PMC8149918/ /pubmed/34054228 http://dx.doi.org/10.1007/s00146-021-01230-z Text en © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Article
Montemayor, Carlos
Halpern, Jodi
Fairweather, Abrol
In principle obstacles for empathic AI: why we can’t replace human empathy in healthcare
title In principle obstacles for empathic AI: why we can’t replace human empathy in healthcare
title_full In principle obstacles for empathic AI: why we can’t replace human empathy in healthcare
title_fullStr In principle obstacles for empathic AI: why we can’t replace human empathy in healthcare
title_full_unstemmed In principle obstacles for empathic AI: why we can’t replace human empathy in healthcare
title_short In principle obstacles for empathic AI: why we can’t replace human empathy in healthcare
title_sort in principle obstacles for empathic ai: why we can’t replace human empathy in healthcare
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8149918/
https://www.ncbi.nlm.nih.gov/pubmed/34054228
http://dx.doi.org/10.1007/s00146-021-01230-z
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