The need for epistemic humility in AI-assisted pain assessment

It has been difficult historically for physicians, patients, and philosophers alike to quantify pain given that pain is commonly understood as an individual and subjective experience. The process of measuring and diagnosing pain is often a fraught and complicated process. New developments in diagnostic technologies assisted by artificial intelligence promise more accurate and efficient diagnosis for patients, but these tools are known to reproduce and further entrench existing issues within the healthcare system, such as poor patient treatment and the replication of systemic biases. In this paper we present the argument that there are several ethical-epistemic issues with the potential implementation of these technologies in pain management settings. We draw on literature about self-trust and epistemic and testimonial injustice to make these claims. We conclude with a proposal that the adoption of epistemic humility on the part of both AI tool developers and clinicians can contribute to a climate of trust in and beyond the pain management context and lead to a more just approach to the implementation of AI in pain diagnosis and management.

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Publication Details

Journal
Medicine Health Care and Philosophy
Published
2025-03-15
DOI
https://doi.org/10.1007/s11019-025-10264-9
Citations
4
Primary Topic
Pain Management and Placebo Effect
Type
article
Field-Weighted Citation Impact
5.72

Funders

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article

The need for epistemic humility in AI-assisted pain assessment

Daniel Z. Buchman, S. Scott Graham, Ruth Katz
4 citations
Medicine Health Care and Philosophy
Pain Management and Placebo Effect
5.72
article

The need for epistemic humility in AI-assisted pain assessment

Daniel Z. Buchman, S. Scott Graham, Ruth Katz
article en
4 citations

Abstract

It has been difficult historically for physicians, patients, and philosophers alike to quantify pain given that pain is commonly understood as an individual and subjective experience. The process of measuring and diagnosing pain is often a fraught and complicated process. New developments in diagnostic technologies assisted by artificial intelligence promise more accurate and efficient diagnosis for patients, but these tools are known to reproduce and further entrench existing issues within the healthcare system, such as poor patient treatment and the replication of systemic biases. In this paper we present the argument that there are several ethical-epistemic issues with the potential implementation of these technologies in pain management settings. We draw on literature about self-trust and epistemic and testimonial injustice to make these claims. We conclude with a proposal that the adoption of epistemic humility on the part of both AI tool developers and clinicians can contribute to a climate of trust in and beyond the pain management context and lead to a more just approach to the implementation of AI in pain diagnosis and management.

Medicine Health Care and PhilosophyVol. 28(2)
University Health Network (CA), Centre for Addiction and Mental Health (CA), University of Toronto (CA), Muscular Dystrophy Canada (CA), Public Health Ontario (CA), Krembil Research Institute, The University of Texas at Austin (US)
National Institutes of Health, Canadian Institutes of Health Research, Social Sciences and Humanities Research Council of Canada, National Institute of General Medical Sciences, Institute of Neurosciences, Mental Health and Addiction
Openalex Percentile: Top 5%
Pain Management and Placebo Effect
5.72
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