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试论生成式人工智能的医疗应用能力与风险边界

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生成式人工智能医疗应用的伦理探讨需要对两个基本问题进行谨慎、清晰的划界.一方面,"能力"的划界旨在澄清生成式人工智能医疗应用的核心优势与技术局限,基于属种差异,明确生成式人工智能医疗应用相较于传统医疗人工智能的关键差异,避免陷入"ChatGPT全能论"或"ChatGPT无能论"的窠臼.另一方面,"风险"的划界旨在区分生成式人工智能医疗应用带来的问题类别及特征,厘清不同风险的独特性质与根源,包括传统人工智能的共有风险、生成式人工智能的特有风险以及生成式人工智能同医疗实践相结合的特性风险,推动风险的分类管理并推进伦理治理的不断完善.
Exploring the Capabilities and Risk Delineation of Generative AI in Medical Applications
Ethical discussions on the application of generative artificial intelligence(AI)in healthcare require careful and clear delineation of two fundamental issues.On one hand,the delineation of"capabilities"aims to clarify the core advantages and technical limitations of generative AI in medical applications.Based on species differences,it is essential to delineate the key differences between generative AI medical applications and traditional medical AI,avoiding falling into the trap of"ChatGPT omnipotence"or"ChatGPT impotence".On the other hand,the delineation of"risks"aims to distinguish the categories and characteristics of problems brought about by generative AI medical applications,clarifying the unique nature and roots of different risks.This includes common risks of traditional AI,unique risks of generative AI,and characteristic risks associated with the integration of generative AI with medical practice.This promotes the classification and management of risks and advances the continuous improvement of ethical governance.

generative artificial intelligencemedical applicationChatGPTcapability delineationrisk delineation

王硕、刘天语、汪琛、刘瑶瑶

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清华大学社会科学学院 北京 100084

东京大学卡维里宇宙物理学与数学研究所 日本千叶 277-8583

清华大学人文学院 北京 100084

生成式人工智能 医疗应用 ChatGPT 能力划界 风险划界

中国博士后科学基金面上项目(第七十四批)(2023)国家资助博士后研究人员计划(2023)

2023M741978GZC20231384

2024

医学与哲学
中国自然辩证法研究会

医学与哲学

CSTPCDCHSSCD北大核心
影响因子:1.314
ISSN:1002-0772
年,卷(期):2024.45(12)