Exploring the Ethical Challenges of Large Language Models in Emergency Medicine: A Comparative International Review

Abstract

Large Language Models (LLMs) hold promise for advancing Emergency Medicine by enhancing operational efficiency and supporting decision-making. This scoping review explores the ethical, legal, and global considerations influencing LLM deployment in emergency care. Key ethical concerns, including patient safety, data privacy, and transparency, emphasise the need for explainable AI (XAI) to build trust and prevent biased outputs. Legal challenges highlight the importance of regulatory compliance, especially regarding data protection laws like the GDPR. Significant international variability in LLM adoption further underscores the need for harmonised guidelines to ensure safe and equitable AI integration across diverse healthcare systems. To advance the responsible use of LLMs, future research should prioritise model transparency, consider resource-limited settings, and focus on establishing robust regulatory frameworks.

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