一个范式的转变? - - 关于医学大语言模型的伦理
Thomas Grote1, Philipp Berens2
1Cluster of Excellence: "Machine Learning: New Perspectives for Science", University of Tübingen, Tübingen, Germany.
Bioethics
|March 25, 2024
概括
大型语言模型 (LLM) 正在将医学机器学习 (ML) 从专业工具转变为通用AI. 这种转变加剧了ML现有的伦理挑战,需要仔细考虑医疗保健中的信任,公平和隐私.
科学领域:
- 医疗人工智能 医疗人工智能
- 临床伦理学 临床伦理学
- 自然语言处理自然语言处理.
背景情况:
- 机器学习 (ML) 已经在医学诊断和风险预测中建立.
- 大型语言模型 (LLM) 的最新进展表明,医疗AI的潜在范式转变.
研究的目的:
- 研究将医疗ML转向通用LLM驱动模型的伦理影响.
- 分析LLM如何加剧医疗AI中现有的伦理问题.
主要方法:
- 文献审查和当前医学ML实践的伦理分析.
- 检查LLM功能对已建立的伦理原则的影响.
主要成果:
- 转向一般的LLM加剧了诸如信任,透明度,患者自主,责任,公平和隐私等道德问题.
- 医学LLM研究的临床评估和可重复性面临着深刻的挑战,而企业利益则加剧了这一挑战.
结论:
- 法学士在医学中的整合提出了复杂的伦理挑战,这些挑战建立在现有辩论的基础上.
- 解决这些挑战对于在医疗保健中负责任地开发和部署人工智能至关重要.
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