Artificial Intelligence and Law最新文献_第8页

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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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

Patterns for legal compliance checking in a decidable framework of linked open data 链接开放数据的可决策框架中的法律合规性检查模式

IF 4.1 2区社会学

Artificial Intelligence and Law Pub Date : 2022-07-04 DOI: 10.1007/s10506-022-09317-8

Enrico Francesconi, Guido Governatori

引用次数: 5

Measuring coherence with Bayesian networks 用贝叶斯网络测量一致性

IF 4.1 2区社会学

Artificial Intelligence and Law Pub Date : 2022-06-19 DOI: 10.1007/s10506-022-09316-9

Alicja Kowalewska, Rafal Urbaniak

引用次数: 0

Law Smells 法律气味

IF 4.1 2区社会学

Artificial Intelligence and Law Pub Date : 2022-06-06 DOI: 10.1007/s10506-022-09315-w

Corinna Coupette, Dirk Hartung, Janis Beckedorf, Maximilian Böther, Daniel Martin Katz

引用次数: 1

A collaboration between judge and machine to reduce legal uncertainty in disputes concerning ex aequo et bono compensations 法官和机器之间的合作，以减少有关公平和无偿赔偿的争端中的法律不确定性

IF 4.1 2区社会学

Artificial Intelligence and Law Pub Date : 2022-05-10 DOI: 10.1007/s10506-022-09314-x

Wim De Mulder, Peggy Valcke, Joke Baeck

{"title":"A collaboration between judge and machine to reduce legal uncertainty in disputes concerning ex aequo et bono compensations","authors":"Wim De Mulder, Peggy Valcke, Joke Baeck","doi":"10.1007/s10506-022-09314-x","DOIUrl":"10.1007/s10506-022-09314-x","url":null,"abstract":"<div><p>Ex aequo et bono compensations refer to tribunal’s compensations that cannot be determined exactly according to the rule of law, in which case the judge relies on an estimate that seems fair for the case at hand. Such cases are prone to legal uncertainty, given the subjectivity that is inherent to the concept of fairness. We show how basic principles from statistics and machine learning may be used to reduce legal uncertainty in ex aequo et bono judicial decisions. For a given type of ex aequo et bono dispute, we consider two general stages in estimating the compensation. First, the stage where there is significant disagreement among judges as to which compensation is fair. In that case, we let judges rule on such disputes, while a machine tracks a certain measure of the relative differences of the granted compensations. In the second stage that measure, which expresses the degree of legal uncertainty, has dropped below a predefined threshold. From then on legal decisions on the quantity of the ex aequo et bono compensation for the considered type of dispute may be replaced by the average of previous compensations. The main consequence is that this type of dispute is, from this stage on, free of legal uncertainty.</p></div>","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43519525","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: 2

Using machine learning to create a repository of judgments concerning a new practice area: a case study in animal protection law 使用机器学习创建一个关于新实践领域的判决库：动物保护法的案例研究

IF 4.1 2区社会学

Artificial Intelligence and Law Pub Date : 2022-05-08 DOI: 10.1007/s10506-022-09313-y

Joe Watson, Guy Aglionby, Samuel March

{"title":"Using machine learning to create a repository of judgments concerning a new practice area: a case study in animal protection law","authors":"Joe Watson, Guy Aglionby, Samuel March","doi":"10.1007/s10506-022-09313-y","DOIUrl":"10.1007/s10506-022-09313-y","url":null,"abstract":"<div><p>Judgments concerning animals have arisen across a variety of established practice areas. There is, however, no publicly available repository of judgments concerning the emerging practice area of animal protection law. This has hindered the identification of individual animal protection law judgments and comprehension of the scale of animal protection law made by courts. Thus, we detail the creation of an initial animal protection law repository using natural language processing and machine learning techniques. This involved domain expert classification of 500 judgments according to whether or not they were concerned with animal protection law. 400 of these judgments were used to train various models, each of which was used to predict the classification of the remaining 100 judgments. The predictions of each model were superior to a baseline measure intended to mimic current searching practice, with the best performing model being a support vector machine (SVM) approach that classified judgments according to term frequency—inverse document frequency (TF-IDF) values. Investigation of this model consisted of considering its most influential features and conducting an error analysis of all incorrectly predicted judgments. This showed the features indicative of animal protection law judgments to include terms such as ‘welfare’, ‘hunt’ and ‘cull’, and that incorrectly predicted judgments were often deemed marginal decisions by the domain expert. The TF-IDF SVM was then used to classify non-labelled judgments, resulting in an initial animal protection law repository. Inspection of this repository suggested that there were 175 animal protection judgments between January 2000 and December 2020 from the Privy Council, House of Lords, Supreme Court and upper England and Wales courts.</p></div>","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10506-022-09313-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41755920","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

Perceptions of Justice By Algorithms 算法对正义的感知

IF 4.1 2区社会学

Artificial Intelligence and Law Pub Date : 2022-04-05 DOI: 10.1007/s10506-022-09312-z

Gizem Yalcin, Erlis Themeli, Evert Stamhuis, Stefan Philipsen, Stefano Puntoni

引用次数: 12