大型语言模型在医学伦理推理中的缺陷

IF 15.1 1区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Shelly Soffer, Vera Sorin, Girish N. Nadkarni, Eyal Klang
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引用次数: 0

摘要

大型语言模型(llm),如chatgpt - 01,在复杂的推理任务中显示出微妙的盲点。我们用横向思维难题和医学伦理场景来说明这些陷阱。我们的观察表明,训练数据中的模式可能会导致认知偏差,限制了模型在微妙的道德情况下导航的能力。认识到这些趋势对于在临床环境中负责任地部署人工智能至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pitfalls of large language models in medical ethics reasoning
Large language models (LLMs), such as ChatGPT-o1, display subtle blind spots in complex reasoning tasks. We illustrate these pitfalls with lateral thinking puzzles and medical ethics scenarios. Our observations indicate that patterns in training data may contribute to cognitive biases, limiting the models’ ability to navigate nuanced ethical situations. Recognizing these tendencies is crucial for responsible AI deployment in clinical contexts.
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来源期刊
CiteScore
25.10
自引率
3.30%
发文量
170
审稿时长
15 weeks
期刊介绍: npj Digital Medicine is an online open-access journal that focuses on publishing peer-reviewed research in the field of digital medicine. The journal covers various aspects of digital medicine, including the application and implementation of digital and mobile technologies in clinical settings, virtual healthcare, and the use of artificial intelligence and informatics. The primary goal of the journal is to support innovation and the advancement of healthcare through the integration of new digital and mobile technologies. When determining if a manuscript is suitable for publication, the journal considers four important criteria: novelty, clinical relevance, scientific rigor, and digital innovation.
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