Artificial Intelligence and Law最新文献_第7页

SM-BERT-CR: a deep learning approach for case law retrieval with supporting model SM-BERT-CR：一种具有支持模型的判例法检索深度学习方法

IF 4.1 2区社会学

Artificial Intelligence and Law Pub Date : 2022-08-10 DOI: 10.1007/s10506-022-09319-6

Yen Thi-Hai Vuong, Quan Minh Bui, Ha-Thanh Nguyen, Thi-Thu-Trang Nguyen, Vu Tran, Xuan-Hieu Phan, Ken Satoh, Le-Minh Nguyen

{"title":"SM-BERT-CR: a deep learning approach for case law retrieval with supporting model","authors":"Yen Thi-Hai Vuong, Quan Minh Bui, Ha-Thanh Nguyen, Thi-Thu-Trang Nguyen, Vu Tran, Xuan-Hieu Phan, Ken Satoh, Le-Minh Nguyen","doi":"10.1007/s10506-022-09319-6","DOIUrl":"10.1007/s10506-022-09319-6","url":null,"abstract":"<div><p>Case law retrieval is the task of locating truly relevant legal cases given an input query case. Unlike information retrieval for general texts, this task is more complex with two phases (<i>legal case retrieval</i> and <i>legal case entailment</i>) and much harder due to a number of reasons. First, both the query and candidate cases are long documents consisting of several paragraphs. This makes it difficult to model with representation learning that usually has restriction on input length. Second, the concept of <i>relevancy</i> in this domain is defined based on the legal relation that goes beyond the lexical or topical relevance. This is a real challenge because normal text matching will not work. Third, building a large and accurate legal case dataset requires a lot of effort and expertise. This is obviously an obstacle to creating enough data for training deep retrieval models. In this paper, we propose a novel approach called <i>supporting model</i> that can deal with both phases. The underlying idea is the case–case supporting relation and the paragraph–paragraph as well as the decision-paragraph matching strategy. In addition, we propose a method to automatically create a large weak-labeling dataset to overcome the lack of data. The experiments showed that our solution has achieved the state-of-the-art results for both case retrieval and case entailment phases.</p></div>","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":"31 3","pages":"601 - 628"},"PeriodicalIF":4.1,"publicationDate":"2022-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49470933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Thirty years of artificial intelligence and law: the third decade 人工智能与法律的三十年：第三个十年

IF 4.1 2区社会学

Artificial Intelligence and Law Pub Date : 2022-08-09 DOI: 10.1007/s10506-022-09327-6

Serena Villata, Michal Araszkiewicz, Kevin Ashley, Trevor Bench-Capon, L. Karl Branting, Jack G. Conrad, Adam Wyner

引用次数: 13

Thirty years of Artificial Intelligence and Law: Editor’s Introduction 人工智能与法律的三十年：编者简介

IF 4.1 2区社会学

Artificial Intelligence and Law Pub Date : 2022-08-08 DOI: 10.1007/s10506-022-09325-8

Trevor Bench-Capon

引用次数: 2

Thirty years of Artificial Intelligence and Law: the second decade 人工智能与法律三十年:第二个十年

IF 4.1 2区社会学

Artificial Intelligence and Law Pub Date : 2022-08-08 DOI: 10.1007/s10506-022-09326-7

Giovanni Sartor, Michał Araszkiewicz, Katie Atkinson, Floris Bex, Tom van Engers, Enrico Francesconi, Henry Prakken, Giovanni Sileno, Frank Schilder, Adam Wyner, Trevor Bench-Capon

引用次数: 4

Thirty years of Artificial Intelligence and Law: overviews 人工智能与法律三十年:综述

IF 4.1 2区社会学

Artificial Intelligence and Law Pub Date : 2022-08-06 DOI: 10.1007/s10506-022-09324-9

Michał Araszkiewicz, Trevor Bench-Capon, Enrico Francesconi, Marc Lauritsen, Antonino Rotolo

引用次数: 3

Mapping the Issues of Automated Legal Systems: Why Worry About Automatically Processable Regulation? 绘制自动化法律系统的问题:为什么要担心可自动处理的监管?

IF 4.1 2区社会学

Artificial Intelligence and Law Pub Date : 2022-08-04 DOI: 10.1007/s10506-022-09323-w

Clement Guitton, Aurelia Tamò-Larrieux, Simon Mayer

{"title":"Mapping the Issues of Automated Legal Systems: Why Worry About Automatically Processable Regulation?","authors":"Clement Guitton, Aurelia Tamò-Larrieux, Simon Mayer","doi":"10.1007/s10506-022-09323-w","DOIUrl":"10.1007/s10506-022-09323-w","url":null,"abstract":"<div><p>The field of computational law has increasingly moved into the focus of the scientific community, with recent research analysing its issues and risks. In this article, we seek to draw a structured and comprehensive list of societal issues that the deployment of automatically processable regulation could entail. We do this by systematically exploring attributes of the law that are being challenged through its encoding and by taking stock of what issues current projects in this field raise. This article adds to the current literature not only by providing a needed framework to structure arising issues of computational law but also by bridging the gap between theoretical literature and practical implementation. Key findings of this article are: (1) The primary benefit (efficiency vs. accessibility) sought after when encoding law matters with respect to the issues such an endeavor triggers; (2) Specific characteristics of a project—project type, degree of mediation by computers, and potential for divergence of interests—each impact the overall number of societal issues arising from the implementation of automatically processable regulation.</p></div>","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":"31 3","pages":"571 - 599"},"PeriodicalIF":4.1,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10506-022-09323-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43740456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A user-centered approach to developing an AI system analyzing U.S. federal court data 以用户为中心开发分析美国联邦法院数据的人工智能系统

IF 4.1 2区社会学

Artificial Intelligence and Law Pub Date : 2022-08-01 DOI: 10.1007/s10506-022-09320-z

Rachel F. Adler, Andrew Paley, Andong L. Li Zhao, Harper Pack, Sergio Servantez, Adam R. Pah, Kristian Hammond, SCALES OKN Consortium

{"title":"A user-centered approach to developing an AI system analyzing U.S. federal court data","authors":"Rachel F. Adler, Andrew Paley, Andong L. Li Zhao, Harper Pack, Sergio Servantez, Adam R. Pah, Kristian Hammond, SCALES OKN Consortium","doi":"10.1007/s10506-022-09320-z","DOIUrl":"10.1007/s10506-022-09320-z","url":null,"abstract":"<div><p>We implemented a user-centered approach to the design of an artificial intelligence (AI) system that provides users with access to information about the workings of the United States federal court system regardless of their technical background. Presently, most of the records associated with the federal judiciary are provided through a federal system that does not support exploration aimed at discovering systematic patterns about court activities. In addition, many users lack the data analytical skills necessary to conduct their own analyses and convert data into information. We conducted interviews, observations, and surveys to uncover the needs of our users and discuss the development of an intuitive platform informed from these needs that makes it possible for legal scholars, lawyers, and journalists to discover answers to more advanced questions about the federal court system. We report on results from usability testing and discuss design implications for AI and law practitioners and researchers.</p></div>","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":"31 3","pages":"547 - 570"},"PeriodicalIF":4.1,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10506-022-09320-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42775697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Definitions of intent suitable for algorithms 适用于算法的意图定义

IF 4.1 2区社会学

Artificial Intelligence and Law Pub Date : 2022-07-25 DOI: 10.1007/s10506-022-09322-x

Hal Ashton

{"title":"Definitions of intent suitable for algorithms","authors":"Hal Ashton","doi":"10.1007/s10506-022-09322-x","DOIUrl":"10.1007/s10506-022-09322-x","url":null,"abstract":"<div><p>This article introduces definitions for direct, means-end, oblique (or indirect) and ulterior intent which can be used to test for intent in an algorithmic actor. These definitions of intent are informed by legal theory from common law jurisdictions. Certain crimes exist where the harm caused is dependent on the reason it was done so. Here the actus reus or performative element of the crime is dependent on the mental state or mens rea of the actor. The ability to prosecute these crimes is dependent on the ability to identify and diagnose intentional states in the accused. A certain class of auto didactic algorithmic actor can be given broad objectives without being told how to meet them. Without a definition of intent, they cannot be told not to engage in certain law breaking behaviour nor can they ever be identified as having done it. This ambiguity is neither positive for the owner of the algorithm or for society. The problem exists over and above more familiar debates concerning the eligibility of algorithms for culpability judgements that mens rea is usually associated with. Aside from inchoate offences, many economic crimes with elements of fraud or deceit fall into this category of crime. Algorithms operate in areas where these crimes could be plausibly undertaken depending on whether the intent existed in the algorithm or not.\u0000</p></div>","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":"31 3","pages":"515 - 546"},"PeriodicalIF":4.1,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10506-022-09322-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42138451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

The potential of an artificial intelligence (AI) application for the tax administration system’s modernization: the case of Indonesia 人工智能应用于税务管理系统现代化的潜力：以印度尼西亚为例

IF 4.1 2区社会学

Artificial Intelligence and Law Pub Date : 2022-07-20 DOI: 10.1007/s10506-022-09321-y

Arfah Habib Saragih, Qaumy Reyhani, Milla Sepliana Setyowati, Adang Hendrawan

{"title":"The potential of an artificial intelligence (AI) application for the tax administration system’s modernization: the case of Indonesia","authors":"Arfah Habib Saragih, Qaumy Reyhani, Milla Sepliana Setyowati, Adang Hendrawan","doi":"10.1007/s10506-022-09321-y","DOIUrl":"10.1007/s10506-022-09321-y","url":null,"abstract":"<div><p>From 2010 to 2020, Indonesia’s tax-to-gross domestic product (GDP) ratio has been declining. A tax-to-GDP ratio trend of this magnitude indicates that the tax authority lacks the capacity to collect taxes. The tax administration system’s modernization utilizing information technology is thus deemed necessary. Artificial intelligence (AI) technology may serve as a solution to this issue. Using the theoretical frameworks of innovations in tax compliance, the cost of taxation, success factors for information technology governance (SFITG), and AI readiness, this study aims to analyze the costs and benefits, the enablers and inhibitors, and the readiness of the government and related parties to apply AI to modernize the tax administration system in Indonesia. This study used qualitative approaches for the data’s collection and analysis. The data were obtained through a literature study and in-depth interviews. The findings show that AI application in the field of taxation can assist tax authorities in enforcing the law, provide taxpayers with convenience in fulfilling their tax obligations, improve justice for all taxpayers, and reduce tax compliance costs. The openness of Indonesia to technological developments, as evidenced by the AI National Strategy, is a supporting factor in the application of AI in Indonesia, particularly for the modernization of the tax administration system. The absence of specific regulations governing AI adoption, as well as a lack of human resources that can help the tax administration process, data, and infrastructure already support, are the impediments to implementing AI for the modernization of the tax administration system in Indonesia.</p></div>","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":"31 3","pages":"491 - 514"},"PeriodicalIF":4.1,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44388272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

A computational model of facilitation in online dispute resolution 网络纠纷解决便利化的计算模型

IF 4.1 2区社会学

Artificial Intelligence and Law Pub Date : 2022-07-13 DOI: 10.1007/s10506-022-09318-7

Karl Branting, Sarah McLeod, Sarah Howell, Brandy Weiss, Brett Profitt, James Tanner, Ian Gross, David Shin

{"title":"A computational model of facilitation in online dispute resolution","authors":"Karl Branting, Sarah McLeod, Sarah Howell, Brandy Weiss, Brett Profitt, James Tanner, Ian Gross, David Shin","doi":"10.1007/s10506-022-09318-7","DOIUrl":"10.1007/s10506-022-09318-7","url":null,"abstract":"<div><p>Online dispute resolution (ODR) is an alternative to traditional litigation that can both significantly reduce the disadvantages suffered by litigants unable to afford an attorney and greatly improve court efficiency and economy. An important aspect of many ODR systems is a facilitator, a neutral party who guides the disputants through the steps of reaching an agreement. However, insufficient availability of facilitators impedes broad adoption of ODR systems. This paper describes a novel model of facilitation that integrates two distinct but complementary knowledge sources: cognitive task analysis of facilitator behavior and corpus analysis of ODR session transcripts. This model is implemented in a decision-support system that (1) monitors cases to detect situations requiring immediate attention and (2) automates selection of standard text messages appropriate to the current state of the negotiations. This facilitation model has the potential to compensate for shortages of facilitators by improving the efficiency of experienced facilitators, assisting novice facilitators, and providing autonomous facilitation.</p></div>","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":"31 3","pages":"465 - 490"},"PeriodicalIF":4.1,"publicationDate":"2022-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10506-022-09318-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48168582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1