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Artificial Intelligence in Healthcare and Education

Ethical and regulatory challenges of large language models in medicine

Jasmine Chiat Ling Ong, Yin‐Hsi Chang, William Wasswa, Atul J. Butte, Nigam H. Shah, Lita Chew, Nan Liu, Finale Doshi‐Velez, Wei Lü, Julian Savulescu, Daniel Shu Wei Ting

Artificial Intelligence in Healthcare and EducationMachine Learning in HealthcareExplainable Artificial Intelligence (XAI)
Published April 23, 2024Read PDF ↗View on arXiv ↗

Abstract

With the rapid growth of interest in and use of large language models (LLMs) across various industries, we are facing some crucial and profound ethical concerns, especially in the medical field. The unique technical architecture and purported emergent abilities of LLMs differentiate them substantially from other artificial intelligence (AI) models and natural language processing techniques used, necessitating a nuanced understanding of LLM ethics. In this Viewpoint, we highlight ethical concerns stemming from the perspectives of users, developers, and regulators, notably focusing on data privacy and rights of use, data provenance, intellectual property contamination, and broad applications and plasticity of LLMs. A comprehensive framework and mitigating strategies will be imperative for the responsible integration of LLMs into medical practice, ensuring alignment with ethical principles and safeguarding against potential societal risks.

Sourced from arXiv · Updated September 2, 2026

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Common questions

What is "Ethical and regulatory challenges of large language models in medicine" about?

With the rapid growth of interest in and use of large language models (LLMs) across various industries, we are facing some crucial and profound ethical concerns, especially in the medical field. The unique technical architecture and purported emergent abilities of LLMs differenti

Who wrote this paper?

Jasmine Chiat Ling Ong, Yin‐Hsi Chang, William Wasswa, Atul J. Butte, Nigam H. Shah, Lita Chew, Nan Liu, Finale Doshi‐Velez, Wei Lü, Julian Savulescu, Daniel Shu Wei Ting

Where can I read the full paper?

The full text is available as a PDF on arXiv (linked above), published April 23, 2024.

Does this paper have a DOI?

Yes: https://doi.org/10.1016/s2589-7500(24)00061-x.