Ethical issues of artificial intelligence in plastic surgery: a narrative review

Abstract

The integration of artificial intelligence (AI) into plastic surgery is transforming the field by enhancing precision in preoperative planning, diagnostic accuracy, intraoperative assistance, and postoperative care. AI encompasses machine learning, natural language processing, computer vision, and artificial neural networks, each offering unique advancements to surgical practice. This narrative review explores the ethical challenges of AI in plastic surgery, addressing concerns such as data protection, algorithmic bias, transparency, accountability, and informed consent. A comprehensive search adhering to PRISMA guidelines identified 63 studies, with 15 selected for in-depth analysis. Findings indicate significant ethical issues: data privacy needs stringent cybersecurity, biases in AI models must be mitigated, and transparency in AI decision making is essential. The review emphasizes the necessity for updated Health Insurance Portability and Accountability Act (HIPAA) regulations, robust validation mechanisms, and the development of explainable AI models. It also highlights the need for an independent regulatory body to oversee AI integration, ensuring ethical standards and protecting patient welfare. Although AI presents promising benefits, its successful application in plastic surgery hinges on addressing these ethical challenges comprehensively.

Keywords

AI / machine learning / plastic surgery / bias / large language models

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