Pub Date : 2023-04-04DOI: 10.1007/s10506-023-09356-9
B. Brożek, Michael Furman, Marek Jakubiec, Bartłomiej Kucharzyk
{"title":"The black box problem revisited. Real and imaginary challenges for automated legal decision making","authors":"B. Brożek, Michael Furman, Marek Jakubiec, Bartłomiej Kucharzyk","doi":"10.1007/s10506-023-09356-9","DOIUrl":"https://doi.org/10.1007/s10506-023-09356-9","url":null,"abstract":"","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46797808","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}
Pub Date : 2023-03-30DOI: 10.1007/s10506-023-09353-y
Maxime C Cohen, Samuel Dahan, Warut Khern-Am-Nuai, Hajime Shimao, Jonathan Touboul
The use of artificial intelligence (AI) to aid legal decision making has become prominent. This paper investigates the use of AI in a critical issue in employment law, the determination of a worker's status-employee vs. independent contractor-in two common law countries (the U.S. and Canada). This legal question has been a contentious labor issue insofar as independent contractors are not eligible for the same benefits as employees. It has become an important societal issue due to the ubiquity of the gig economy and the recent disruptions in employment arrangements. To address this problem, we collected, annotated, and structured the data for all Canadian and Californian court cases related to this legal question between 2002 and 2021, resulting in 538 Canadian cases and 217 U.S. cases. In contrast to legal literature focusing on complex and correlated characteristics of the employment relationship, our statistical analyses of the data show very strong correlations between the worker's status and a small subset of quantifiable characteristics of the employment relationship. In fact, despite the variety of situations in the case law, we show that simple, off-the-shelf AI models classify the cases with an out-of-sample accuracy of more than 90%. Interestingly, the analysis of misclassified cases reveals consistent misclassification patterns by most algorithms. Legal analyses of these cases led us to identify how equity is ensured by judges in ambiguous situations. Finally, our findings have practical implications for access to legal advice and justice. We deployed our AI model via the open-access platform, https://MyOpenCourt.org/, to help users answer employment legal questions. This platform has already assisted many Canadian users, and we hope it will help democratize access to legal advice to large crowds.
{"title":"The use of AI in legal systems: determining independent contractor vs. employee status.","authors":"Maxime C Cohen, Samuel Dahan, Warut Khern-Am-Nuai, Hajime Shimao, Jonathan Touboul","doi":"10.1007/s10506-023-09353-y","DOIUrl":"10.1007/s10506-023-09353-y","url":null,"abstract":"<p><p>The use of artificial intelligence (AI) to aid legal decision making has become prominent. This paper investigates the use of AI in a critical issue in employment law, the determination of a worker's status-employee vs. independent contractor-in two common law countries (the U.S. and Canada). This legal question has been a contentious labor issue insofar as independent contractors are not eligible for the same benefits as employees. It has become an important societal issue due to the ubiquity of the gig economy and the recent disruptions in employment arrangements. To address this problem, we collected, annotated, and structured the data for all Canadian and Californian court cases related to this legal question between 2002 and 2021, resulting in 538 Canadian cases and 217 U.S. cases. In contrast to legal literature focusing on complex and correlated characteristics of the employment relationship, our statistical analyses of the data show very strong correlations between the worker's status and a small subset of quantifiable characteristics of the employment relationship. In fact, despite the variety of situations in the case law, we show that simple, off-the-shelf AI models classify the cases with an out-of-sample accuracy of more than 90%. Interestingly, the analysis of misclassified cases reveals consistent misclassification patterns by most algorithms. Legal analyses of these cases led us to identify how equity is ensured by judges in ambiguous situations. Finally, our findings have practical implications for access to legal advice and justice. We deployed our AI model via the open-access platform, https://MyOpenCourt.org/, to help users answer employment legal questions. This platform has already assisted many Canadian users, and we hope it will help democratize access to legal advice to large crowds.</p>","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10061388/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9742579","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}
Pub Date : 2023-03-16DOI: 10.1007/s10506-023-09351-0
Meghdad Ghari
{"title":"A formalization of the Protagoras court paradox in a temporal logic of epistemic and normative reasons","authors":"Meghdad Ghari","doi":"10.1007/s10506-023-09351-0","DOIUrl":"https://doi.org/10.1007/s10506-023-09351-0","url":null,"abstract":"","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44602578","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}
Pub Date : 2023-03-15DOI: 10.1007/s10506-023-09352-z
Fábio M. Oliveira, M. Balbino, Luis E. Zárate, Fawn T. Ngo, R. Govindu, Anurag Agarwal, C. Nobre
{"title":"Predicting inmates misconduct using the SHAP approach","authors":"Fábio M. Oliveira, M. Balbino, Luis E. Zárate, Fawn T. Ngo, R. Govindu, Anurag Agarwal, C. Nobre","doi":"10.1007/s10506-023-09352-z","DOIUrl":"https://doi.org/10.1007/s10506-023-09352-z","url":null,"abstract":"","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43644754","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}
Pub Date : 2023-03-14DOI: 10.1007/s10506-023-09354-x
Junlin Zhu, Jiaye Wu, Xudong Luo, Jie Liu
Recently, the pandemic caused by COVID-19 is severe in the entire world. The prevention and control of crimes associated with COVID-19 are critical for controlling the pandemic. Therefore, to provide efficient and convenient intelligent legal knowledge services during the pandemic, we develop an intelligent system for legal information retrieval on the WeChat platform in this paper. The data source we used for training our system is "The typical cases of national procuratorial authorities handling crimes against the prevention and control of the new coronary pneumonia pandemic following the law", which is published online by the Supreme People's Procuratorate of the People's Republic of China. We base our system on convolutional neural network and use the semantic matching mechanism to capture inter-sentence relationship information and make a prediction. Moreover, we introduce an auxiliary learning process to help the network better distinguish the relation between two sentences. Finally, the system uses the trained model to identify the information entered by a user and responds to the user with a reference case similar to the query case and gives the reference legal gist applicable to the query case.
{"title":"Semantic matching based legal information retrieval system for COVID-19 pandemic.","authors":"Junlin Zhu, Jiaye Wu, Xudong Luo, Jie Liu","doi":"10.1007/s10506-023-09354-x","DOIUrl":"10.1007/s10506-023-09354-x","url":null,"abstract":"<p><p>Recently, the pandemic caused by COVID-19 is severe in the entire world. The prevention and control of crimes associated with COVID-19 are critical for controlling the pandemic. Therefore, to provide efficient and convenient intelligent legal knowledge services during the pandemic, we develop an intelligent system for legal information retrieval on the WeChat platform in this paper. The data source we used for training our system is \"The typical cases of national procuratorial authorities handling crimes against the prevention and control of the new coronary pneumonia pandemic following the law\", which is published online by the Supreme People's Procuratorate of the People's Republic of China. We base our system on convolutional neural network and use the semantic matching mechanism to capture inter-sentence relationship information and make a prediction. Moreover, we introduce an auxiliary learning process to help the network better distinguish the relation between two sentences. Finally, the system uses the trained model to identify the information entered by a user and responds to the user with a reference case similar to the query case and gives the reference legal gist applicable to the query case.</p>","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10012305/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10074769","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}
Pub Date : 2023-03-04DOI: 10.1007/s10506-023-09349-8
Aniket Deroy, Kripabandhu Ghosh, Saptarshi Ghosh
{"title":"Ensemble methods for improving extractive summarization of legal case judgements","authors":"Aniket Deroy, Kripabandhu Ghosh, Saptarshi Ghosh","doi":"10.1007/s10506-023-09349-8","DOIUrl":"https://doi.org/10.1007/s10506-023-09349-8","url":null,"abstract":"","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46658483","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}
Pub Date : 2023-02-22DOI: 10.1007/s10506-023-09347-w
Athina Sachoulidou
{"title":"Going beyond the “common suspects”: to be presumed innocent in the era of algorithms, big data and artificial intelligence","authors":"Athina Sachoulidou","doi":"10.1007/s10506-023-09347-w","DOIUrl":"https://doi.org/10.1007/s10506-023-09347-w","url":null,"abstract":"","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48818700","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}
Pub Date : 2023-02-18DOI: 10.1007/s10506-023-09348-9
Hugo Mentzingen, N. António, Victor Lobo
{"title":"Joining metadata and textual features to advise administrative courts decisions: a cascading classifier approach","authors":"Hugo Mentzingen, N. António, Victor Lobo","doi":"10.1007/s10506-023-09348-9","DOIUrl":"https://doi.org/10.1007/s10506-023-09348-9","url":null,"abstract":"","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45108787","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}
Pub Date : 2023-02-09DOI: 10.1007/s10506-023-09346-x
V. G. Bertalan, E. Ruiz
{"title":"Correction: Using attention methods to predict judicial outcomes","authors":"V. G. Bertalan, E. Ruiz","doi":"10.1007/s10506-023-09346-x","DOIUrl":"https://doi.org/10.1007/s10506-023-09346-x","url":null,"abstract":"","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49128770","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}
Pub Date : 2023-02-01DOI: 10.1007/s10506-023-09345-y
Deepali Jain, M. Borah, Anupam Biswas
{"title":"A sentence is known by the company it keeps: Improving Legal Document Summarization Using Deep Clustering","authors":"Deepali Jain, M. Borah, Anupam Biswas","doi":"10.1007/s10506-023-09345-y","DOIUrl":"https://doi.org/10.1007/s10506-023-09345-y","url":null,"abstract":"","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43077802","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}
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