Artificial Intelligence and Law最新文献

{"title":"Resolving counterintuitive consequences in law using legal debugging","authors":"Wachara Fungwacharakorn,&nbsp;Kanae Tsushima,&nbsp;Ken Satoh","doi":"10.1007/s10506-021-09283-7","DOIUrl":"10.1007/s10506-021-09283-7","url":null,"abstract":"<div><p>There are cases in which the literal interpretation of statutes may lead to counterintuitive consequences. When such cases go to high courts, judges may handle these counterintuitive consequences by identifying problematic rule conditions. Given that the law consists of a large number of rule conditions, it is demanding and exhaustive to figure out which condition is problematic. For solving this problem, our work aims to assist judges in civil law systems to resolve counterintuitive consequences using logic program representation of statutes and Legal Debugging. The core principle of Legal Debugging is to cooperate with a user to find a <i>culprit</i>, a root cause of counterintuitive consequences. This article proposes an algorithm to resolve a culprit. Since the statutes are represented by logic rules but changes in law are initiated by cases, we adopt a <i>prototypical case with judgement</i> specified by a set of rules. Then, to resolve a culprit, we reconstruct a program so that it provides reasons as if we applied case-based reasoning to a new set of prototypical cases with judgement, which include a new set of facts relevant to a considering case.</p></div>","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":"29 4","pages":"541 - 557"},"PeriodicalIF":4.1,"publicationDate":"2021-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10506-021-09283-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46978136","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}

{"title":"Compliance-aware engineering process plans: the case of space software engineering processes","authors":"Julieth Patricia Castellanos-Ardila,&nbsp;Barbara Gallina,&nbsp;Guido Governatori","doi":"10.1007/s10506-021-09285-5","DOIUrl":"10.1007/s10506-021-09285-5","url":null,"abstract":"<div><p>Safety-critical systems manufacturers have the duty of care, i.e., they should take correct steps while performing acts that could foreseeably harm others. Commonly, industry standards prescribe reasonable steps in their process requirements, which regulatory bodies trust. Manufacturers perform careful documentation of compliance with each requirement to show that they act under acceptable criteria. To facilitate this task, a safety-centered planning-time framework, called ACCEPT, has been proposed. Based on compliance-by-design, ACCEPT capabilities (i.e., processes and standards modeling, and automatic compliance checking) permit to design Compliance-aware Engineering Process Plans (CaEPP), which are able to show the planning-time allocation of standard demands, i.e., if the elements set down by the standard requirements are present at given points in the engineering process plan. In this paper, we perform a case study to understand if the ACCEPT produced models could support the planning of space software engineering processes. Space software is safety and mission-critical, and it is often the result of industrial cooperation. Such cooperation is coordinated through compliance with relevant standards. In the European context, ECSS-E-ST-40C is the de-facto standard for space software production. The planning of processes in compliance with project-specific ECSS-E-ST-40C applicable requirements is mandatory during contractual agreements. Our analysis is based on qualitative criteria targeting the effort dictated by task demands required to create a CaEPP for software development with ACCEPT. Initial observations show that the effort required to model compliance and processes artifacts is significant. However, such an effort pays off in the long term since models are, to some extend, reusable and flexible. The coverage level of the models is also analyzed based on design decisions. In our opinion, such a level is adequate since it responds to the information needs required by the ECSS-E-ST-40C framework.</p></div>","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":"29 4","pages":"587 - 627"},"PeriodicalIF":4.1,"publicationDate":"2021-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10506-021-09285-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47711941","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}

{"title":"Return on Investment on AI: The Case of Capital Requirement","authors":"H. Fraisse, Matthias Laporte","doi":"10.2139/ssrn.3803150","DOIUrl":"https://doi.org/10.2139/ssrn.3803150","url":null,"abstract":"Taking advantage of granular data we measure the change in bank capital requirement resulting from the implementation of AI techniques to predict corporate defaults. For each of the largest banks operating in France we design an algorithm to build pseudo-internal models of credit risk management for a range of methodologies extensively used in AI (random forest, gradient boosting, ridge regression, deep learning). We compare these models to the traditional model usually in place that basically relies on a combination of logistic regression and expert judgement. The comparison is made along two sets of criterias capturing : the ability to pass compliance tests used by the regulators during onsite missions of model validation (i), and the induced changes in capital requirement (ii). The different models show noticeable differences in their ability to pass the regulatory tests and to lead to a reduction in capital requirement. While displaying a similar ability than the traditional model to pass compliance tests, neural networks provide the strongest incentive for banks to apply AI models for their internal model of credit risk of corporate businesses as they lead in some cases to sizeable reduction in capital requirement.","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":"286 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80288101","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}

{"title":"Different Models of Innovation and Their Relation to Law","authors":"C. Delmotte","doi":"10.1017/9781839701047.003","DOIUrl":"https://doi.org/10.1017/9781839701047.003","url":null,"abstract":"","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":"1 1","pages":"23-48"},"PeriodicalIF":4.1,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1017/9781839701047.003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43856937","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}

{"title":"Basic Concepts of AI for Legal Scholars","authors":"Rembrandt Devillé, Nico Sergeyssels, C. Middag","doi":"10.1017/9781839701047.002","DOIUrl":"https://doi.org/10.1017/9781839701047.002","url":null,"abstract":"","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":"1 1","pages":"1-22"},"PeriodicalIF":4.1,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1017/9781839701047.002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47645921","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}

{"title":"AI in Belgian Contract Law: Disruptive Challenge or Business as Usual?","authors":"A. Appelmans, Maarten Herbosch, Benjamin Verheye","doi":"10.1017/9781839701047.014","DOIUrl":"https://doi.org/10.1017/9781839701047.014","url":null,"abstract":"","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":"1 1","pages":"335-358"},"PeriodicalIF":4.1,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1017/9781839701047.014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41338507","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}

{"title":"Robotisation and Labour Law. The Dark Factory: the Dark Side of Work?","authors":"Simon Taes","doi":"10.1017/9781839701047.012","DOIUrl":"https://doi.org/10.1017/9781839701047.012","url":null,"abstract":"","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":"1 1","pages":"285-316"},"PeriodicalIF":4.1,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1017/9781839701047.012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46837080","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}

{"title":"AI and Creditworthiness Assessments: the Tale of Credit Scoring and Consumer Protection. A Story with a Happy Ending?","authors":"Julie Goetghebuer","doi":"10.1017/9781839701047.017","DOIUrl":"https://doi.org/10.1017/9781839701047.017","url":null,"abstract":"","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":"1 1","pages":"429-460"},"PeriodicalIF":4.1,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1017/9781839701047.017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48232898","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}

{"title":"Setting the Scene: On AI Ethics and Regulation","authors":"Michiel Fierens, Stephanie Rossello, Ellen Wauters","doi":"10.1017/9781839701047.004","DOIUrl":"https://doi.org/10.1017/9781839701047.004","url":null,"abstract":"","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":"1 1","pages":"49-72"},"PeriodicalIF":4.1,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1017/9781839701047.004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48838243","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}

{"title":"AI and the Consumer","authors":"Skander Bennis","doi":"10.1017/9781839701047.018","DOIUrl":"https://doi.org/10.1017/9781839701047.018","url":null,"abstract":"","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":"1 1","pages":"461-486"},"PeriodicalIF":4.1,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1017/9781839701047.018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48086415","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}