An Artificial-Intelligence-Based Semantic Assist Framework for Judicial Trials

被引:3
作者
Jin, Yaohui [1 ,3 ]
He, Hao [2 ]
机构
[1] Shanghai Jiao Tong Univ, Artificial Intelligence Inst, 800 Dongchuan Rd, Shanghai, Peoples R China
[2] Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai, Peoples R China
[3] Shanghai Jiao Tong Univ, AI Inst, MoE Key Lab Artificial Intelligence, Shanghai, Peoples R China
关键词
artificial intelligence; legal reason; fact extraction and verification; semantic similarity; sentencing prediction;
D O I
10.1017/als.2020.33
中图分类号
D9 [法律]; DF [法律];
学科分类号
0301 ;
摘要
Due to their success in routine tasks such as voice recognition, image classification, and text processing, extensive attention has been aroused on how to use artificial intelligence (AD -based automation tools in the judicial-trial process to improve efficiency. Meanwhile, judicial trial is a complex task that requires accurate insight and subtle analysis of the cases, law, and common knowledge. Applying the results provided by AI-based automation tools directly to the judicialtrial process is controversial due to their irregular logic and low accuracy. Based on this observation, this article investigates the logic underlined in judicial trials and the technical characteristics of AI, and proposes an AI-based semantic assist approach for judicial trials that is logical and transparent to the judges.
引用
收藏
页码:531 / 540
页数:10
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