［美］罗纳德·J·艾伦 著  汪诸豪 译

【摘 要】就实际法令的意义而言，法律规则与法院判决之间的冲突广为人知。这种冲突关系同样存在于事实认定之中。法律几乎贯穿了人类活动的所有方面；人与人之间的任何互动都可能会导致法律冲突。对这些纷争进行准确的事实认定是恰当贯彻实体法要求的必要前提保障。若事实认定缺乏准确性，法律就会变得不可测，继而人们便无法高效地按照法律规定行事。法律事实认定之于准确性和可预判性的需要促使人们去探寻适用于这项任务的形式化工具。众多形式化工具之中，贝叶斯定理和期望效用理论 ( 贝叶斯式或统计式决策理论 ) 已被检验。可惜二者并无法很好地与诉讼相契合，进而引发了对其它替代方案的探索与检验，其中以案情故事模式和相对可信论为典型。本文将依次探讨这些问题，展开论述美国传统法庭审理的基本架构；审视庭审与贝叶斯定理、期望效用理论等形式化工具之间的不和谐关系；并介绍相对可信论—一种阐释司法证明本质的理论。

【关键词】人工智能；形式主义；司法证明；相对可信论

【中图分类号】D915.13

【文献标识码】A

【文章编号】1674-1226（2020）05-0588-12

Artificial intelligence and the evidentiary process: the challenges of formalism and computation. Ronald J.Allen, John Henry Wigmore Professor of Law, Northwestern University; Translated by Wang Zhuhao, Institute of Evidence Law and Forensic Science, China University of Political Science and Law (CUPL), Beijing, 100088.

【Abstract】The tension between rule and judgment is well known with respect to the meaning of substantive legal commands. The same conflict is present in fact finding. The law penetrates to virtually all aspects of human affairs; virtually any interaction can generate a legal conflict. Accurate fact finding about such disputes is a necessary condition for the appropriate application of substantive legal commands. Without accuracy in fact finding, the law is unpredictable, and thus individuals cannot efficiently accommodate their affairs to its commands. The need for accuracy and predictability in legal fact finding has generated a search for formal tools to apply to the task. Among the tools that have been examined are Bayes’ Theorem and expected utility theory (Bayesian or statistical decision theory). These tools do not map well onto trials, which in turn has generated an examination of alternative approaches, in particular the story model and the relative plausibility theory. This paper discusses these issues in turn. It elaborates the basic structure of trials in the American tradition; examines the uneasy relationship between trials and such formalisms as Bayes’ Theorem and expected utility theory; and introduces the relative plausibility theory as an explanation of the nature of juridical proof.

【Key Words】Artificial intelligence; Formalism; Juridical proof; Relative plausibility theory