大数据技术背景下司法证明的认知结构与限度

长久以来，司法证明的认知结构这一论题并未获得证据法学界的重视，司法证明的研究场域被局限在法律形式主义的司法三段论中，但事实上，传统的司法证明具备 “经验—逻辑—结论”的三重认知结构。大数据技术介入司法证明领域后，司法数据库的建立、算法模型及其生成规律的适用为司法证明的认知结构带来了要素性的转变，同时也在证明逻辑层面揭示了法官作为 ＂逻辑黑箱” 与 “算法黑箱“ 存在一定程度的同质性。大数据司法证明具有 “数据库—逻辑—结论” 的认知结构，其以法官的有限理性为限，并以消解认知上的不透明性为目的。在当前大数据证明的认知结构下，大数据技术的信息收集与处理 能力决定了司法证明的技术限度；大数据用于智能增强的技术定位决定了司法收集与处理 能力决定了司法证明的技术限度；大数据用于智能增强的技术定位决定了司法证明的伦理限度；大数据技术原理下司法证明的工作方式决定了司法证明的事实限度。

Abstract: For a long time, the cognitive structure of judicial proof has not received due at­tention from the field of evidence law. The research domain of judicial proof has been confined within the framework of the legal formalism's judicial syllogism. However, in reality, traditional judicial proof possesses a three-tier cognitive structure of”experience - logic - conclusion“. With the advent of big data technology in the field of judicial proof, the establishment of judicial dat­abases, the application of algorithm models and their generation rules have brought about funda­mental changes to the cognitive structure of judicial proof. At the same time, it has also revealed a certain degree of homogeneity between judges as ”logical black boxes“ and ”algorithmic black boxes“ at the level of prooflogic. Big data judicial proof features a cognitive structure of ”data­base - logic - conclusion“, which is limited by the bounded rationality of judges and aims to elim­inate the opacity