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大语言模型数据隐私保护的难点与探索

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基于海量数据训练的大语言模型在带来通用人工智能可能性的同时,也给数据隐私保护带来了新的风险与挑战.在分析大语言模型全环节中涉及的数据隐私保护风险的基础上,对隐私保护中知情同意原则、数据收集"正当、必要"原则所面临的新伦理难点展开分析论证,并探索可能的解决框架和路径,以及实操中仍可能存在的伦理难点.
Difficulties and explorations in data privacy protection for large language models
Large language models based on massive data training bring the possibility of generalized artificial intelligence,but also bring new risks and challenges to data privacy protection.This paper analyzes the risks of data privacy protection in the whole process of large language model,argues the new ethical difficulties faced by the principle of informed consent and the principle of"justification and necessity"of data collection,and explores the possible solution frameworks and paths,as well as the ethical difficulties that may still exist in the practice.

large language modelgenerative artificial intelligencedata privacyinformed consentdata liability

施敏、杨海军

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上海市互联网信息办公室,上海 200032

大语言模型 生成式人工智能 数据隐私 知情同意 数据责任

2024

大数据
人民邮电出版社

大数据

CSTPCD
ISSN:2096-0271
年,卷(期):2024.10(5)