大数据法律监督的发展隐忧及优化路径  

Development Concerns and Optimization Paths of Big Data Legal Supervision

作　　者：董玉庭[1] 张闳诏 DONG Yuting;ZHANG Hongzhao(School of Law,Heilongjiang University,Harbin 150080,China)

机构地区：[1]黑龙江大学法学院,哈尔滨黑龙江150080

出　　处：《湖南科技大学学报（社会科学版）》2023年第5期135-142,共8页Journal of Hunan University of Science and Technology(Social Science Edition)

摘　　要：新时代大数据应用的蓬勃发展推动着法律监督的变革,尤其在检察机关工作中,案件监督向数据监督转变、事后监督向全程监督转变、人力监督向算法监督转变。大数据法律监督通过对数据进行挖掘分析,揭示司法程序中的规律和不足,从而提升工作效率与效果,促进司法公正和法治建设。与此同时,大数据法律监督也存在着发展隐忧,需要完善监督模式、整合数据来源、规范数据模型进而推进司法大数据的深度应用,以实现大数据法律监督的优化。The vigorous development of big data applications in the new era is driving a transformation in legal supervision,especially in the work of prosecuting agencies.Case supervision is shifting towards data supervision,post-event supervision is turning into continuous supervision,and human supervision is transitioning to algorithmic supervision.Big data legal supervision involves mining and analyzing data to reveal patterns and shortcomings in the judicial process,thereby improving work efficiency and effectiveness,promoting judicial fairness,and advancing the rule of law.At the same time,big data legal supervision also faces development concerns and requires the refinement of supervision models,the integration of data sources,and the standardization of data models to further advance the deep application of judicial big data,in order to optimize the supervision of big data legal practices.

关 键 词：大数据法律监督 检察监督 法律监督模式 

分 类 号：D92[政治法律—法学]