TRANSFORMING THE LEGAL LANDSCAPE: AN AI-DRIVEN FRAMEWORK FOR JUDICIAL TEXT PROCESSING
DOI:
https://doi.org/10.47820/recima21.v6i5.6426Palavras-chave:
Inteligência Artificial e Direito, Processamento de Linguagem Natural, Metodologia para Desenvolvimento de Inteligência ArtificialResumo
Artificial Intelligence can revolutionize the legal field by addressing the complexities of managing extensive textual data inherent to judicial processes. Nevertheless, the literature highlights the difficulties in managing different contexts regarding distinct application scenarios. This paper presents a novel methodology tailored for developing applications in the legal domain, leveraging cutting-edge natural language processing techniques, including transformer-based architectures, pre-trained models, and transfer learning. Unlike traditional software development, this approach embraces the inherent uncertainties of Artificial Intelligence solutions by employing an iterative framework that integrates strong collaboration with legal professionals, domain-specific datasets, and comprehensive evaluation strategies. The methodology was validated through real-world applications at the Court of Justice of Rio Grande do Sul, including the development of a Judgment Report Generator, which automates judgment report creation using Generative Artificial Intelligence, and additional experiments showcased state-of-the-art performance in legal Named Entity Recognition using fine-tuned BERT models and context-adapted text generation with GPT-2-based models, demonstrating adaptability to diverse legal scenarios. This work bridges advanced natural language processing techniques with the practical demands of the judiciary, establishing a foundation for scalable, reliable, and domain-aware AI applications. The proposed methodology addresses practical challenges, regulatory alignment, and dataset specificity, enabling effective AI integration in the legal sector for enhanced efficiency and impact in real-world judicial systems.
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