[1]闫 立 吴何奇.重大疫情治理中人工智能的价值属性与隐私风险——兼谈隐私保护的刑法路径[J].南京师大学报(社会科学版),2020,(02):032-41.
 YAN Li,WU Heqi.The Value and Privacy Risks of Deploying AI in Handling a PublicHealth Emergency:Also on a Criminal Law-basedApproach to Privacy Protection[J].Journal of Nanjing Normal University (Social Science Edition),2020,(02):032-41.
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重大疫情治理中人工智能的价值属性与隐私风险——兼谈隐私保护的刑法路径
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《南京师大学报》(社会科学版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2020年02期
页码:
032-41
栏目:
特别专题:重大疫情治理研究
出版日期:
2020-03-15

文章信息/Info

Title:
The Value and Privacy Risks of Deploying AI in Handling a PublicHealth Emergency:Also on a Criminal Law-basedApproach to Privacy Protection
作者:
闫 立 吴何奇
闫立,上海政法学院、(上海201701); 吴何奇,上海财经大学法学院博(上海200433)
Author(s):
YAN Li WU Heqi
关键词:
重大疫情治理 大数据 人工智能 隐私风险
Keywords:
public health emergency big data AI privacy risks
摘要:
相关国家政策文件的出台为我国医疗人工智能的迅速发展夯实了政策基础,在重大疫情的治理过程中,以医疗大数据为基础的人工智能不仅能够提升诊断的准确率、缓解医务人员不足的困境,更能减少医务工作者感染疾病的风险。但由于人工智能的运作存在着对个人隐私侵犯的天然性,反思人工智能时代个人隐私保护的刑法路径也应同步于重大疫情的治理。我国刑法中并没有以隐私权为独立客体的法律条文,现有对隐私权的保护附属于刑法对市场经济秩序、公民人身权利与民主权利、社会管理秩序的保护,但这一体系下的个人隐私保护存在着制度设计上的缺陷。针对弊端,个人隐私保护刑法路径的建构首先应以对大数据背景下个人隐私的合理界定为逻辑前提,站在风险防范与利益平衡的立场,不以静态的视角界定隐私的边界,再以此展开个人隐私保护刑法路径的具体设计。
Abstract:
The introduction of relevant state policies has laid a solid foundation for the rapid development of AI for medical purposes in China. In dealing with a public health emergency, AI technology based on medical big data can not only improve the accuracy of diagnosis, alleviate the shortage of medical personnel, but also reduce the medical workers’ risk of infection. However, because the operation of AI will inevitably result in the invasion of personal privacy, the criminal law path to the protection of personal privacy in the era of AI should also be aligned with the governance of a public health emergency. In China’s criminal law, there is no legal provision regarding privacy as an independent object, and the protection of privacy is attached to the protection of market order, citizens’ personal and democratic rights, and social order. In view of the disadvantages, the construction of the criminal law path to personal privacy protection should first take as the logical premise a reasonable definition of personal privacy in the context of big data, and stick to the standpoint of risk prevention and interest balance, rather than defining the boundary of privacy from a static perspective. Only in this way can we carry out the specific design of a criminal law-based path to personal privacy protection.

备注/Memo

备注/Memo:
闫立,法学博士,上海政法学院教授、博士生导师(上海201701); 吴何奇,上海财经大学法学院博士研究生(上海200433)。本文系中央高校基本科研业务费专项资金资助(2018110301)的研究成果。YAN Li, PhD in Law, is Professor in Shanghai University of Political Science and Law(Shanghai 201701); WU Heqi is PhD Candidate at School of Law, Shanghai University of Finance and Economics(Shanghai 200433).
更新日期/Last Update: 2020-03-15