LegalAnalytics: bridging visual explanations and workload streamline in Brazilian Supreme Court appeals

IF 5.3 2区 社会学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Lucas Resck, Felipe Moreno-Vera, Tobias Veiga, Gerardo Paucar, Ezequiel Fajreldines, Guilherme Klafke, Luis G. Nonato, Jorge Poco
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引用次数: 0

Abstract

The Brazilian Supreme Court serves as the highest judicial authority in Brazil and is responsible for adjudicating constitutional matters presented as extraordinary appeals. These appeals undergo a rigorous screening process guided by established legal principles known as Topics of General Repercussion. Seeking to streamline this procedure, we developed LegalAnalytics to explore the research question: Can machine learning and explainable AI techniques enhance the classification of appeals in legal workflows? LegalAnalytics harnesses advanced natural language processing algorithms and classification models to categorize each appeal according to the most pertinent topics accurately. In addition, it incorporates LIME (Local Interpretable Model-agnostic Explanations) to highlight the key sections of an appeal and compare them with relevant precedents. This approach ensures a transparent justification for every classification. The system is thoughtfully designed with a user-friendly interface tailored for public servants, judges, and lawyers. Extensive testing with dozens of legal experts confirmed the effectiveness of LegalAnalytics, with consistently positive feedback underscoring its significant practical impact.

LegalAnalytics:在巴西最高法院上诉中衔接视觉解释和工作量简化
巴西最高法院是巴西的最高司法机构,负责裁决作为特别上诉提出的宪法问题。这些申诉要经过严格的筛选程序,并遵循被称为“普遍影响议题”的既定法律原则。为了简化这一程序,我们开发了LegalAnalytics来探索研究问题:机器学习和可解释的人工智能技术能否增强法律工作流程中的上诉分类?LegalAnalytics利用先进的自然语言处理算法和分类模型,根据最相关的主题准确地对每个上诉进行分类。此外,它还结合了LIME(本地可解释模型不可知论解释),以突出上诉的关键部分,并将其与相关判例进行比较。这种方法确保每个分类都有一个透明的理由。该系统为公务员、法官和律师精心设计了一个用户友好的界面。经过数十位法律专家的广泛测试,LegalAnalytics的有效性得到了证实,持续不断的积极反馈强调了其重大的实际影响。
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来源期刊
CiteScore
9.50
自引率
26.80%
发文量
33
期刊介绍: Artificial Intelligence and Law is an international forum for the dissemination of original interdisciplinary research in the following areas: Theoretical or empirical studies in artificial intelligence (AI), cognitive psychology, jurisprudence, linguistics, or philosophy which address the development of formal or computational models of legal knowledge, reasoning, and decision making. In-depth studies of innovative artificial intelligence systems that are being used in the legal domain. Studies which address the legal, ethical and social implications of the field of Artificial Intelligence and Law. Topics of interest include, but are not limited to, the following: Computational models of legal reasoning and decision making; judgmental reasoning, adversarial reasoning, case-based reasoning, deontic reasoning, and normative reasoning. Formal representation of legal knowledge: deontic notions, normative modalities, rights, factors, values, rules. Jurisprudential theories of legal reasoning. Specialized logics for law. Psychological and linguistic studies concerning legal reasoning. Legal expert systems; statutory systems, legal practice systems, predictive systems, and normative systems. AI and law support for legislative drafting, judicial decision-making, and public administration. Intelligent processing of legal documents; conceptual retrieval of cases and statutes, automatic text understanding, intelligent document assembly systems, hypertext, and semantic markup of legal documents. Intelligent processing of legal information on the World Wide Web, legal ontologies, automated intelligent legal agents, electronic legal institutions, computational models of legal texts. Ramifications for AI and Law in e-Commerce, automatic contracting and negotiation, digital rights management, and automated dispute resolution. Ramifications for AI and Law in e-governance, e-government, e-Democracy, and knowledge-based systems supporting public services, public dialogue and mediation. Intelligent computer-assisted instructional systems in law or ethics. Evaluation and auditing techniques for legal AI systems. Systemic problems in the construction and delivery of legal AI systems. Impact of AI on the law and legal institutions. Ethical issues concerning legal AI systems. In addition to original research contributions, the Journal will include a Book Review section, a series of Technology Reports describing existing and emerging products, applications and technologies, and a Research Notes section of occasional essays posing interesting and timely research challenges for the field of Artificial Intelligence and Law. Financial support for the Journal of Artificial Intelligence and Law is provided by the University of Pittsburgh School of Law.
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