摘要
人工智能证据进入法庭需要满足合法性要求,但是由于其具有不同于传统证据的特点,以往基本的证据合法性要求过于笼统,不能完全与之相匹配,有必要从数据收集、数据分析和结果形成三阶段加以具体表述。人工智能证据数据过度收集可能侵犯个人信息保护权,算法黑箱下数据分析不透明可能违反程序正义和损害实体公正,表现形式欠缺合法要件导致证据适用随意。为此,可以从确立数据收集和处理的基本原则、逐步破除法定证据种类的藩篱、构建人工智能证据的合法性审查机制以及确保被追诉人充分参与和行使对质权等方面规范人工智能证据的使用。
AI evidence should meet legitimate requirements in the courts.Data collection,data analysis and result formation should match the legitimate requirements because of the unique features.Excessive collection of data for AI evidence may violate the right of personal information protection;the opacity of data analysis under the black box of algorithms may violate procedural justice and substantive justice;the lack of lawful elements in the form of manifestation leads to arbitrary application of evidence.Principles should be established for data collection and processing,legal types of evidence should be clarified,the mechanism for reviewing the legitimacy of AI evidence should be established,and the accused should participates in and exercises the confrontation right to formulate the use of AI evidence.
作者
王姝
Wang Shu(Law School,Beijing Normal University,Beijing 100875,China)
出处
《河北科技师范学院学报(社会科学版)》
2025年第1期64-70,共7页
Journal of Hebei Normal University of Science & Technology(Social Sciences)
基金
北京师范大学法学院2024年度学术型研究生专项科研基金课题“刑事诉讼中人工智能证据的可靠性风险及法律应对”(2024LAW043)。
关键词
人工智能证据
合法性
算法
个人信息保护
AI evidence
legitimacy
algorithms
personal information protection
