Partial Data and Total Pain: Clinical and Ethical Hazards of AI Applications in Palliative Care

Medicine finds itself on the brink of an artificial intelligence (AI) revolution, promising to transform what it means to be human and thus what it means to encounter humans with serious illness. The character of such transformation in pain management remains yet to be determined, leaving open to what extent AI might exacerbate or resolve challenges confronting pain management. In this article, I aim to clarify what might be expected from AI in pain management on a conceptual level and proceed by problematizing the tension between, on the one hand, <i>partial data</i> representing the range of incipient AI applications relevant to pain and, on the other hand, <i>total pain</i> representing the core principles and concepts of pain management in palliative medicine. This helps to elucidate those aspects of pain most amenable to automation, generating a call to action within pain research and presenting an opportunity for palliative clinicians to steer AI implementation.

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Publication Details

Journal
Journal of Palliative Medicine
Published
2026-02-24
DOI
https://doi.org/10.1177/10966218261422909
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Partial Data and Total Pain: Clinical and Ethical Hazards of AI Applications in Palliative Care

Ethan M. Schimmoeller
Journal of Palliative Medicine
Artificial Intelligence in Healthcare and Education
article

Partial Data and Total Pain: Clinical and Ethical Hazards of AI Applications in Palliative Care

Ethan M. Schimmoeller
article en

Abstract

Medicine finds itself on the brink of an artificial intelligence (AI) revolution, promising to transform what it means to be human and thus what it means to encounter humans with serious illness. The character of such transformation in pain management remains yet to be determined, leaving open to what extent AI might exacerbate or resolve challenges confronting pain management. In this article, I aim to clarify what might be expected from AI in pain management on a conceptual level and proceed by problematizing the tension between, on the one hand, <i>partial data</i> representing the range of incipient AI applications relevant to pain and, on the other hand, <i>total pain</i> representing the core principles and concepts of pain management in palliative medicine. This helps to elucidate those aspects of pain most amenable to automation, generating a call to action within pain research and presenting an opportunity for palliative clinicians to steer AI implementation.

Journal of Palliative Medicine
OhioHealth (US)
Openalex Percentile: Top 47%
Artificial Intelligence in Healthcare and Education
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