Medicolegal Implications and Current Landscape of Artificial Intelligence in Plastic Surgery

Artificial intelligence (AI) is increasingly integrated into plastic and reconstructive surgery. It supports preoperative prediction and imaging analysis, intraoperative visualization, and postoperative monitoring. While these advancements demonstrate AI's growing potential across the surgical continuum, their adoption also presents ethical, legal, and regulatory challenges. Concerns surrounding algorithmic bias, data privacy, and informed consent are particularly relevant in fields shaped by individualized anatomy, aesthetic nuance, and patient-specific goals. This analysis reviews the current landscape of AI in plastic surgery and medicolegal frameworks shaping its use. Existing legal doctrines, ranging from antidiscrimination and privacy protections to common-law informed consent, offer partial guidance for AI use in plastic surgery. Traditional liability models struggle to accommodate adaptive algorithms. Early litigation has focused largely on insurance decision-making rather than procedural use of AI. In the absence of clear precedent, regulatory efforts remain fragmented. The EU imposes strict oversight for high-risk medical AI, and US federal and state policies emphasize transparency and human oversight. However, there remains limited direction on liability or intraoperative use. These gaps highlight the need for more comprehensive, procedure-specific regulation as AI integrates into surgical care and plastic surgery more broadly. This analysis proposes a decision-making framework. We emphasize transparent informed consent, patient privacy protections, and clinician awareness of algorithmic bias, to guide safe integration of AI tools into active clinical practice. While AI may meaningfully enhance plastic surgery, its limited generalizability and susceptibility to bias reinforce its current role as an adjunct to, rather than a substitute for, a surgeon's expertise.

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Publication Details

Journal
Journal of Craniofacial Surgery
Published
2026-01-29
DOI
https://doi.org/10.1097/scs.0000000000012419
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
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article

Medicolegal Implications and Current Landscape of Artificial Intelligence in Plastic Surgery

Rohan K. Mangal, Nicholas A. Mirsky, Seth Ray Thaller, Stephanie Riveron et al.
Journal of Craniofacial Surgery
Artificial Intelligence in Healthcare and Education
article

Medicolegal Implications and Current Landscape of Artificial Intelligence in Plastic Surgery

Rohan K. Mangal, Nicholas A. Mirsky, Seth Ray Thaller, Stephanie Riveron, Hannah Quan
article en

Abstract

Artificial intelligence (AI) is increasingly integrated into plastic and reconstructive surgery. It supports preoperative prediction and imaging analysis, intraoperative visualization, and postoperative monitoring. While these advancements demonstrate AI's growing potential across the surgical continuum, their adoption also presents ethical, legal, and regulatory challenges. Concerns surrounding algorithmic bias, data privacy, and informed consent are particularly relevant in fields shaped by individualized anatomy, aesthetic nuance, and patient-specific goals. This analysis reviews the current landscape of AI in plastic surgery and medicolegal frameworks shaping its use. Existing legal doctrines, ranging from antidiscrimination and privacy protections to common-law informed consent, offer partial guidance for AI use in plastic surgery. Traditional liability models struggle to accommodate adaptive algorithms. Early litigation has focused largely on insurance decision-making rather than procedural use of AI. In the absence of clear precedent, regulatory efforts remain fragmented. The EU imposes strict oversight for high-risk medical AI, and US federal and state policies emphasize transparency and human oversight. However, there remains limited direction on liability or intraoperative use. These gaps highlight the need for more comprehensive, procedure-specific regulation as AI integrates into surgical care and plastic surgery more broadly. This analysis proposes a decision-making framework. We emphasize transparent informed consent, patient privacy protections, and clinician awareness of algorithmic bias, to guide safe integration of AI tools into active clinical practice. While AI may meaningfully enhance plastic surgery, its limited generalizability and susceptibility to bias reinforce its current role as an adjunct to, rather than a substitute for, a surgeon's expertise.

Journal of Craniofacial SurgeryVol. 37(3/4)
University of Miami (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 76%
Artificial Intelligence in Healthcare and Education
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