大数据证据质证形式化的问题检视与制度矫正  

Examination and Institutional Correction of the Formalization of Big Data Evidence Verification

作　　者：陈在上[1] 任逸飞 CHEN Zaishang;REN Yifei(Henan University of Economics and Law,Zhengzhou Henan 450046,China)

机构地区：[1]河南财经政法大学,河南郑州450046

出　　处：《河南警察学院学报》2024年第6期52-61,共10页Journal of Henan Police College

基　　金：2021年度河南省哲学社会科学规划项目“审判中心主义视阈下律师辩护权实质化研究”(2021BFX004)。

摘　　要：随着大数据证据的司法运用逐渐增多,其质证阶段的证据偏在现象严重、质证流程不够规范、专业技术论证缺失等形式化问题凸显,原因在于控辩能力的差异性、质证规则的局限性及算法运行的黑箱性。基于此,应从强化控方义务、保障辩方权利、改善裁判规则等方面优化主体权责结构;从更新专家辅助人制度、细化非法证据排除规则、明晰交叉询问规则等方面完善庭审质证规则;从推进算法有限公开、加强算法可理解性、增设数据访问权利等方面克服算法黑箱流弊,以矫正大数据证据质证制度。With the increasing use of big data evidence in judicial practice,formal problems such as serious bias in evidence during the cross-examination stage,nonstandard process,and lack of professional technical argumentation have become prominent.The reasons lie in the differences in prosecution and defense abilities,limitations in cross examination rules,and the black box nature of algorithm operation.Based on this,in order to correct the big data evidence verification system,the structure of subject rights and responsibilities can be optimized by strengthening the obligations of the prosecution,safeguarding the rights of the defense,and improving the rules of adjudication;the rules for cross examination in court can be improved by updating the expert assistance system,refining the rules for excluding illegal evidence,and clarifying the rules for cross examination;and the drawbacks of algorithm black box can be overcome by promoting limited algorithm disclosure,strengthening algorithm comprehensibility and adding data access rights.

关 键 词：大数据证据 质证规则 算法黑箱 控辩失衡 证据偏在 

分 类 号：D925.2[政治法律—诉讼法学]