意大利司法系统中人工智能支持流程分析的挑战:数字化后会怎样?

Devis Bianchini, Carlo Bono, Alessandro Campi, Cinzia Cappiello, Stefano Ceri, Francesca De Luzi, Massimo Mecella, Barbara Pernici, Pierluigi Plebani
{"title":"意大利司法系统中人工智能支持流程分析的挑战:数字化后会怎样?","authors":"Devis Bianchini, Carlo Bono, Alessandro Campi, Cinzia Cappiello, Stefano Ceri, Francesca De Luzi, Massimo Mecella, Barbara Pernici, Pierluigi Plebani","doi":"10.1145/3630025","DOIUrl":null,"url":null,"abstract":"In this commentary paper, we outline research challenges and possible directions for the potential applications of AI in the judicial domain by specifically considering process analysis in the Italian context. Applying AI to process analysis poses several challenges, including information extraction from legacy information systems and analysis of legal documents, process modeling with a particular emphasis on temporal analysis, real-time process monitoring, conformance and compliance checking, predictive techniques for accurate predictions, and analysis of judges’ workload. Solutions to these challenges include methods and tools for data identification and collection, innovative approaches to process modeling, reactive techniques for real-time monitoring, conformance checking with explainability, language models adapted to specific domains, and the identification of suitable indicators for the analysis of case handling efficiency and case classification.","PeriodicalId":93488,"journal":{"name":"Proceedings of the ... International Conference on Digital Government Research. International Conference on Digital Government Research","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Challenges in AI-supported process analysis in the Italian judicial system: what after digitalization?\",\"authors\":\"Devis Bianchini, Carlo Bono, Alessandro Campi, Cinzia Cappiello, Stefano Ceri, Francesca De Luzi, Massimo Mecella, Barbara Pernici, Pierluigi Plebani\",\"doi\":\"10.1145/3630025\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this commentary paper, we outline research challenges and possible directions for the potential applications of AI in the judicial domain by specifically considering process analysis in the Italian context. Applying AI to process analysis poses several challenges, including information extraction from legacy information systems and analysis of legal documents, process modeling with a particular emphasis on temporal analysis, real-time process monitoring, conformance and compliance checking, predictive techniques for accurate predictions, and analysis of judges’ workload. Solutions to these challenges include methods and tools for data identification and collection, innovative approaches to process modeling, reactive techniques for real-time monitoring, conformance checking with explainability, language models adapted to specific domains, and the identification of suitable indicators for the analysis of case handling efficiency and case classification.\",\"PeriodicalId\":93488,\"journal\":{\"name\":\"Proceedings of the ... International Conference on Digital Government Research. International Conference on Digital Government Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ... International Conference on Digital Government Research. International Conference on Digital Government Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3630025\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... International Conference on Digital Government Research. International Conference on Digital Government Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3630025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在这篇评论文章中,我们通过具体考虑意大利背景下的过程分析,概述了人工智能在司法领域潜在应用的研究挑战和可能的方向。将人工智能应用于流程分析带来了一些挑战,包括从遗留信息系统中提取信息和分析法律文件,特别强调时间分析的流程建模,实时流程监控,一致性和合规检查,准确预测的预测技术以及法官工作量分析。这些挑战的解决方案包括数据识别和收集的方法和工具,流程建模的创新方法,实时监控的反应技术,可解释性的一致性检查,适应特定领域的语言模型,以及用于分析案例处理效率和案例分类的合适指标的识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Challenges in AI-supported process analysis in the Italian judicial system: what after digitalization?
In this commentary paper, we outline research challenges and possible directions for the potential applications of AI in the judicial domain by specifically considering process analysis in the Italian context. Applying AI to process analysis poses several challenges, including information extraction from legacy information systems and analysis of legal documents, process modeling with a particular emphasis on temporal analysis, real-time process monitoring, conformance and compliance checking, predictive techniques for accurate predictions, and analysis of judges’ workload. Solutions to these challenges include methods and tools for data identification and collection, innovative approaches to process modeling, reactive techniques for real-time monitoring, conformance checking with explainability, language models adapted to specific domains, and the identification of suitable indicators for the analysis of case handling efficiency and case classification.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信