| Texto completo | |
| Autor(es): |
Resck, Lucas
;
Moreno-Vera, Felipe
;
Veiga, Tobias
;
Paucar, Gerardo
;
Fajreldines, Ezequiel
;
Klafke, Guilherme
;
Nonato, Luis G.
;
Poco, Jorge
Número total de Autores: 8
|
| Tipo de documento: | Artigo Científico |
| Fonte: | ARTIFICIAL INTELLIGENCE AND LAW; v. N/A, p. 59-pg., 2025-07-11. |
| Resumo | |
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. (AU) | |
| Processo FAPESP: | 22/09091-8 - Criminalidade, insegurança e legitimidade: uma abordagem transdisciplinar |
| Beneficiário: | Luis Gustavo Nonato |
| Modalidade de apoio: | Auxílio à Pesquisa - Programa eScience e Data Science - Temático |
| Processo FAPESP: | 21/07012-0 - Inteligência orientada a dados para análise e percepção de crimes urbanos |
| Beneficiário: | Jorge Luis Poco Medina |
| Modalidade de apoio: | Auxílio à Pesquisa - Jovens Pesquisadores |