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Ong JCL, Chang SYH, William W, Butte AJ, Shah NH, Chew LST, Liu N, Doshi-Velez F, Lu W, Savulescu J, Ting DSW. Ethical and regulatory challenges of large language models in medicine. Lancet Digit Health 2024:S2589-7500(24)00061-X. [PMID: 38658283 DOI: 10.1016/s2589-7500(24)00061-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 03/08/2024] [Accepted: 03/12/2024] [Indexed: 04/26/2024]
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.
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Affiliation(s)
- Jasmine Chiat Ling Ong
- Division of Pharmacy, Singapore General Hospital, Singapore; Duke-NUS Medical School, National University of Singapore, Singapore
| | - Shelley Yin-Hsi Chang
- Department of Ophthalmology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan; College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Wasswa William
- Department of Biomedical Sciences and Engineering, Mbarara University of Science and Technology, Mbarara, Uganda
| | - Atul J Butte
- Bakar Computational Health Sciences Institute, and Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA; Center for Data-Driven Insights and Innovation, University of California Health, Oakland, CA, USA
| | - Nigam H Shah
- Stanford Health Care, Palo Alto, CA, USA; Department of Medicine, and Clinical Excellence Research Center, School of Medicine, Stanford University, Stanford, CA, USA
| | - Lita Sui Tjien Chew
- Department of Pharmacy, National University of Singapore, Singapore; Singapore Health Services, Pharmacy and Therapeutics Council Office, Singapore; Department of Pharmacy, National Cancer Centre Singapore, Singapore
| | - Nan Liu
- Duke-NUS Medical School, National University of Singapore, Singapore
| | - Finale Doshi-Velez
- Harvard Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Wei Lu
- StatNLP Research Group, Singapore University of Technology and Design, Singpore
| | - Julian Savulescu
- Murdoch Children's Research Institute, Melbourne, VIC, Australia; Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Oxford Uehiro Centre for Practical Ethics, Faculty of Philosophy, University of Oxford, Oxford, UK
| | - Daniel Shu Wei Ting
- Duke-NUS Medical School, National University of Singapore, Singapore; Artificial Intelligence and Digital Innovation, Singapore Eye Research Institute, Singapore National Eye Center, Singapore Health Service, Singapore; Byers Eye Institute, Stanford University, Palo Alto, CA, USA.
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