暨南学报(哲学社会科学版)

作者：孙道萃

单位：中国政法大学国家法律援助研究院副教授,法学博士。

关键词：认罪认罚案件,人工智能辅助量刑,精准预测,理论供需,知识原理,实施体系

基金：国家社会科学基金青年项目“人工智能时代的刑法前瞻与应对研究”(批准号:18CFX041);中国政法大学青年教师资助计划“检察机关贯彻落实认罪认罚从宽制度的实证研究”(批准号:1000-10820706)。

在认罪认罚案件中,控辩量刑从宽协商机制的司法供给不足、量刑建议协商的效率诉求攀升、量刑建议的正当性与精准化要求等问题交互叠加,亟待从理论本源上疏解供需矛盾,人工智能辅助预测量刑也应运而生。认罪认罚案件具备智能办案的规模化、类型化优势条件,与“预测”量刑的本质特征、量刑规范化理论、司法大数据蕴含的量刑规律与经验等,共同生成人工智能辅助精准预测量刑的知识体系。理论预测与数据预测作为体系双核相互验证,与必要的人工介入,齐力实现更精准预测量刑,提高量刑协商效率与量刑建议质量。人工智能辅助精准预测量刑系统宜定位为司法辅助角色,发挥量刑规范化层面的参考作用。"/>template{display:none;}.mag-rich-xref-fn { cursor: pointer;}//长视频$(document).ready(function(){if($("#showLongArticleVideo") && $("#showLongArticleVideo").length && $("#showLongArticleVideo").length>0){mag_ajax_update({ele_id:'showLongArticleVideo',url:mag_currentQikanUrl() + "/CN/article/showLongArticleVideo.do?id="+$("#articleId").val()});}});$(document).ready(function(){window.metaData = {"journal":{"issn":"1000-5072","qiKanMingCheng_CN":"暨南学报（哲学社会科学版）","id":2,"qiKanMingCheng_EN":"Jinan Journal"},"fundList_cn":["国家社会科学基金青年项目“人工智能时代的刑法前瞻与应对研究”(批准号:18CFX041);中国政法大学青年教师资助计划“检察机关贯彻落实认罪认罚从宽制度的实证研究”(批准号:1000-10820706)。"],"article":{"keywordList_cn":["精准预测","理论供需","人工智能辅助量刑","认罪认罚案件","实施体系","知识原理"],"juan":"42","zhaiyao_cn":"在认罪认罚案件中,控辩量刑从宽协商机制的司法供给不足、量刑建议协商的效率诉求攀升、量刑建议的正当性与精准化要求等问题交互叠加,亟待从理论本源上疏解供需矛盾,人工智能辅助预测量刑也应运而生。认罪认罚案件具备智能办案的规模化、类型化优势条件,与“预测”量刑的本质特征、量刑规范化理论、司法大数据蕴含的量刑规律与经验等,共同生成人工智能辅助精准预测量刑的知识体系。理论预测与数据预测作为体系双核相互验证,与必要的人工介入,齐力实现更精准预测量刑,提高量刑协商效率与量刑建议质量。人工智能辅助精准预测量刑系统宜定位为司法辅助角色,发挥量刑规范化层面的参考作用。","endNoteUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/article/getTxtFile.do?fileType=EndNote&id=6521","reference":"","bibtexUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/article/getTxtFile.do?fileType=BibTeX&id=6521","abstractUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/Y2020/V42/I12/64","qi":"12","id":6521,"nian":2020,"bianHao":"2020-12-64","zuoZheEn_L":"SUN Daocui","juanUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/Y2020","shouCiFaBuRiQi":"2020-12-23","qiShiYe":"64","qiUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/Y2020/V42/I12","lanMu_cn":"认罪认罚从宽制度实施问题研究","pdfSize":"1511","zuoZhe_CN":"孙道萃","risUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/article/getTxtFile.do?fileType=Ris&id=6521","title_cn":"人工智能辅助精准预测量刑的中国境遇——以认罪认罚案件为适用场域","jieShuYe":"78","keywordList_en":["cases of admission of guilt and acceptance of punishment","knowledge principles","operation system","precise prediction","sentencing assisted by AI","theoretical demand"],"endNoteUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/article/getTxtFile.do?fileType=EndNote&id=6521","zhaiyao_en":"Judicial authorities are now facing the major task of negotiating sentencing for cases involving admission of guilt and acceptance of punishment. The contradiction between the number of people and the judicial efficiency is getting more and more prominent. The mechanism and ability of sentencing negotiation are relatively insufficient. However, cases involving admission of guilt and acceptance of punishment have favourable conditions for intelligent handling, which determines the advent of the intelligent sentencing. The functional orientation of accurate prediction, the theory of sentencing standardization and the results of reform, the sentencing rules and experience of judicial big data support the exploration basis of intelligent and accurate prediction of sentencing. Theoretical prediction and data prediction are dual theoretical cores, which mutually verify each other. In addition, with necessary manual intervention, they can not only facilitate the accuracy of intelligent predictive sentencing, but also can promote the efficiency and quality of sentencing negotiation. 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来源：2020年第12期

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