AI and Ethics: A Systematic Review of the Ethical Considerations of Large Language Model Use in Surgery Research

Author:

Pressman Sophia M.1,Borna Sahar1,Gomez-Cabello Cesar A.1ORCID,Haider Syed A.1ORCID,Haider Clifton2,Forte Antonio J.13ORCID

Affiliation:

1. Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA

2. Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, USA

3. Center for Digital Health, Mayo Clinic, Rochester, MN 55905, USA

Abstract

Introduction: As large language models receive greater attention in medical research, the investigation of ethical considerations is warranted. This review aims to explore surgery literature to identify ethical concerns surrounding these artificial intelligence models and evaluate how autonomy, beneficence, nonmaleficence, and justice are represented within these ethical discussions to provide insights in order to guide further research and practice. Methods: A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Five electronic databases were searched in October 2023. Eligible studies included surgery-related articles that focused on large language models and contained adequate ethical discussion. Study details, including specialty and ethical concerns, were collected. Results: The literature search yielded 1179 articles, with 53 meeting the inclusion criteria. Plastic surgery, orthopedic surgery, and neurosurgery were the most represented surgical specialties. Autonomy was the most explicitly cited ethical principle. The most frequently discussed ethical concern was accuracy (n = 45, 84.9%), followed by bias, patient confidentiality, and responsibility. Conclusion: The ethical implications of using large language models in surgery are complex and evolving. The integration of these models into surgery necessitates continuous ethical discourse to ensure responsible and ethical use, balancing technological advancement with human dignity and safety.

Funder

Noaber Foundation

Publisher

MDPI AG

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