The DOI matches its Crossref record; 32 of the 33 references it cites were found in a registry or an index.
In principle obstacles for empathic AI: why we can’t replace human empathy in healthcare
Open accessAbstract
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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“Empathy requires experiencing what someone is going through and deeply caring [96, 108].”
From Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providers. (2025) · cites this paper as [96]
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Afroogh, S., Akbari, A., Malone, E., Kargar, M., & Alambeigi, H. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-04044-8 · Cited by 718
Will generative AI replace teachers in higher education? A study of teacher and student perceptions
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Metadata
- Authors
- Montemayor, C., Halpern, J., & Fairweather, A.
- Affiliations
- San Francisco State University (US)
- University of California, Berkeley (US)
- Corresponding author
- Montemayor, Carlos
- Venue
- AI & SOCIETY
- Published
- 2021-05-26
- Volume
- 37
- Issue
- 4
- Pages
- 1353-1359
- ISSN
- 0951-5666 (ISSN-L)
- 1435-5655
- PMC
- PMC8149918
- OpenAlex
- W3165373184
- Cited by
- 293
- References
- 33
- Citations by year
- 2026: 91 · 2025: 94 · 2024: 74 · 2023: 23 · 2022: 5 · 2021: 5
- FWCI
- 7.80
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- AI & Society (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Health Sciences › Medicine › Psychiatry and Mental health › Empathy and Medical Education
- Keywords
- artificial intelligence in healthcare, empathy, nursing care, relational care, AI limitations, human monitoring, emotional intervention, moral responsibility, legal responsibility, patient care
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