COMPLIANCE TO LEGAL PRECEDENTS AND REPETITIVE LEGAL CASES MANAGEMENT WITH MACHINE LEARNING

• Autor(a) principal: Sabo, Isabela Cristina
• Data de Publicação: 2020
• Outros Autores: Rover, Aires José
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Revista Opinião Jurídica (Fortaleza)
• Texto Completo: https://periodicos.unichristus.edu.br/opiniaojuridica/article/view/2553
• topic: E-Judiciary; Civil jurisdiction; Machine learning; Electronic process; Legal precedents system; E-justicia; Jurisdicción civil; Aprendizaje automático; Proceso judicial electrónico; Precedentes judiciales; Direito, Direito Processual Civil; Inteligência Artificial; E-Judiciário; Jurisdição civil; Aprendizado de máquina; Processo eletrônico; Precedentes

Brazilian Judiciary is presented as one of the focus of discussion on the implementation of technologies related to Artificial Intelligence (AI), from which comes the machine learning (ML). In this context, the research problem is presented: is it possible that machine learning contributes to the functioning of the legal precedents system? Starting from an initial positive hypothesis, and using the inductive method, the article presents a study of two cases, with data collection about two procedural institutes: one about the non-compliance to legal precedents,the “Reclamação” [sic]; and another about the techniques for management of repetitive cases, the “Incidente de Resolução de Demandas Repetitivas (IRDR)” [sic]. In order to contextualize the theme and objectives of the study, the research presents the evolution of the concept of jurisdiction, referring to the changes brought by the Brazilian Code of Civil Procedure (2015), and still the notions of E-Judiciary and e-jurisdiction combined with the functionalities of AI, as well as related work using ML. Thus, the proposed ML applications are based on theidentification of these two procedural institutes, related to the operation of the legal precedence system, which can be improved with the implementation of the technology to achieve a model of intelligent civil jurisdiction.