Inteligência artificial na função judicial: revisão sistemática da literatura e suas implicações no caso do ChatBot CURIA
Barra lateral de artigos
Como Citar
Este trabalho está licenciado sob uma licença Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
##plugins.themes.bootstrap3.displayStats.downloads##
Societal impact
Conteúdo do artigo principal
Resumo
A presente pesquisa consiste em uma revisão sistemática da literatura acerca da aplicação de ferramentas de inteligência artificial (IA) no âmbito judicial, com o propósito de analisar sua influência na eficiência da administração da justiça, na gestão da informação jurídica e no apoio à tomada de decisões. Nesse contexto, são examinados diversos sistemas de assistência baseados em IA, entre eles o ChatBot CURIA, implementado pelo Poder Judiciário do Peru, concebido como uma ferramenta especializada em pesquisa jurídica inteligente, cujo propósito é auxiliar os operadores da justiça sem substituir a função jurisdicional nem a faculdade decisória dos juízes. A pesquisa adota uma abordagem qualitativa por meio de uma revisão sistemática de estudos científicos publicados em bases de dados internacionais de alta qualidade e prestígio entre 2020 e 2026. Os resultados indicam que as aplicações baseadas em processamento de linguagem natural (PLN), big data e modelos de IA contribuem para reduzir a carga de trabalho jurisdicional e melhorar o acesso à informação jurídica e à jurisprudência. No entanto, também são identificados riscos relacionados ao viés algorítmico, à transparência, à proteção de dados e à independência judicial. O estudo oferece uma avaliação crítica e sistemática da integração da IA na função judicial, propondo critérios para sua implementação.
Detalhes do artigo
Referências
Alikhademi, K., Drobina, E., Prioleau, D., Richardson, B., Purves, D., & Gilbert, J. E. (2021). A Review of Predictive Policing from the Perspective of Fairness. Artificial Intelligence And Law, 30(1), 1-17. https://doi.org/10.1007/s10506-021-09286-4
Arar, Ö. F., & Ayan, K. (2017). A Feature Dependent Naive Bayes Approach and Its Application to the Software Defect Prediction Problem. Applied Soft Computing, 59, 197-209. https://doi.org/10.1016/j.asoc.2017.05.043
Baclic, O., Tunis, M., Young, K., Doan, C., & Swerdfeger, H. (2020). Challenges and Opportunities for Public Health Made Possible by Advances in Natural Language Processing. Canada Communicable Disease Report, 46(6), 161-168. https://doi.org/10.14745/ccdr.v46i06a02
Battineni, G., Chougule, S. N., Kataria, A., & Goyal, L. M. (2025). Navigating Ethics and Legalities in Artificial Intelligence: Challenges, Frameworks, and Future Directions. In M. Mittal & B. Bhushan (Eds.). Generative AI in Healthcare: Concepts, Methodologies, Tools, and Applications. Studies in Computational Intelligence (Vo. 1234, pp. 293-315). Springer. https://doi.org/10.1007/978-981-95-2129-6_12
Benbouzid, B. (2019). To Predict and to Manage: Predictive Policing in the United States. Big Data & Society, 6(1). https://doi.org/10.1177/2053951719861703
Benedikter, R., & Cruz-Infante, C. (2026). AI in Latin America: Attempts of Regulating Artificial Intelligence within the Geopolitical Paradigm of Active Non-Alignment (ANA). A Critical Review. Journal Of Transatlantic Studies, 24(1). https://doi.org/10.1057/s42738-026-00156-y
Bhattacharya, B., Bhattacharjee, R., Bhattacharya, S., & Islam, M. B. (2025). The Impact of Artificial Intelligence on Legal and Jurisdictional Challenges. In M. Chakraborty, S. P. Chakrabarty, A. Penteado & V. E. Balas (Eds.). Proceedings of 5th International Ethical Hacking Conference. eHaCON 2024. Lecture Notes in Networks and Systems (Vol. 1148, pp. 351-363). Springer. https://doi.org/10.1007/978-981-97-8457-8_23
Broeders, D., Schrijvers, E., van der Sloot, B., van Brakel, R., de Hoog, J., & Ballin, E. H. (2017). Big Data and Security Policies: Toward a Framework for Regulating the Phases of Analytics and Use of Big Data. Computer Law & Security Review, 33(3), 309-323. https://doi.org/10.1016/j.clsr.2017.03.002
Chalkidis, I., & Kampas, D. (2018). Deep Learning in Law: Early Adaptation and Legal Word Embeddings Trained on Large Corpora. Artificial Intelligence and Law, 27(2), 171-198. https://doi.org/10.1007/s10506-018-9238-9
Chen, Q. (2025). Improving the Trial Efficiency of Criminal Cases with the Assistance of Artificial Intelligence. Discover Artificial Intelligence, 5(1). https://doi.org/10.1007/s44163-025-00353-2
Chotcomwongse, P., Srisawat, C., & Theeramunkong, T. (2024). Automated Legal Article Classification Using Natural Language Processing and Deep Learning. Engineering Journal, 28(3), 1-13. https://doi.org/10.4186/ej.2024.28.3.1
Chowdhary, K. R. (2020). Natural Language Processing. In Fundamentals of Artificial Intelligence (pp. 603-649). Springer. https://doi.org/10.1007/978-81-322-3972-7_19
da Silva, S. S. F., & Pereira, J. D. (2025). A ética da inteligência artificial no direito: reflexões à luz da filosofia do direito e dos fundamentos da justiça. Revista Foco, 18(12), e10887. https://doi.org/10.54751/revistafoco.v18n12-061
Douilhet, E., & Karanasiou, A. P. (2018). Legal Responses to the Commodification of Personal Data in the Era of Big Data: The Paradigm Shift from Data Protection towards Data Ownership. In I. Management Association (Ed.). Web Services: Concepts, Methodologies, Tools, and Applications (pp. 2076-2085). IGI Global Scientific Publishing. https://doi.org/10.4018/978-1-5225-7501-6.ch106
Freire, D. L., De Almeida, A. M. G., De S Dias, M., Rivolli, A., Pereira, F. S. F., De Godoi, G. A., & De Carvalho, A. C. P. L. F. (2024). Towards Automated Classification of Repetitive Themes in Brazilian Courts with Legal Class. In Á. Rocha, C. Ferrás, J. Hochstetter Diez & M. Diéguez Rebolledo (Eds.). Information Technology and Systems. ICITS 2024. Lecture Notes in Networks and Systems (Vol. 933, pp. 247-257). Springer. https://doi.org/10.1007/978-3-031-54256-5_23
Gromova, E. A., Ferreira, D. B., & Begishev, I. R. (2023). ChatGPT and Other Intelligent Chatbots: Legal, Ethical and Dipute Resolution Concerns. Revista Brasileira de Alternative Dispute Resolution, 5(10), 153-175. https://doi.org/10.52028/rbadr.v5i10.art07.ru
Halaburda, N., Radchenia, N., & Pahlevanzade, A. (2025). State Regulation of the Use of Artificial Intelligence: Civil Law and Economic and Legal Aspects. Baltic Journal of Economic Studies, 11(4), 294-303. https://doi.org/10.30525/2256-0742/2025-11-4-294-303
Han, Q., Kou, Y., & Snaidauf, D. (2019). Experimental Evaluation of CNN Parameters for Text Categorization in Legal Document Review. 2019 IEEE International Conference on Big Data (Big Data) (pp. 4320-4324). Wiley-IEEE Press. https://doi.org/10.1109/bigdata47090.2019.9006182
Han, Q., & Snaidauf, D. (2021). Comparison of Deep Learning Technologies in Legal Document Classification. In 2021 IEEE International Conference on Big Data (Big Data) (pp. 2701-2704). Wiley-IEEE Press. https://doi.org/10.1109/bigdata52589.2021.9671486
He, M., & Chen, Y. (2025). Personal Data Protection in China: Progress, Challenges and Prospects in the Age of Big Data and AI. Telecommunications Policy, 49(10), 103076. https://doi.org/10.1016/j.telpol.2025.103076
Hellman, D. (2023). Big Data and Compounding Injustice. Journal Of Moral Philosophy, 21(1-2), 62-83. https://doi.org/10.1163/17455243-20234373
Huanca, R. (2023). El principio de celeridad procesal y el acceso a la justicia en el sistema judicial peruano. Revista Jurídica del Perú, 43(2), 17-35.
Kaczmarczyk, A., Libal, T., & Smywiński-Pohl, A. (2024). A Legal Assistant for Accountable Decision-Making. In J. Savelka, J. Harasta, T. Novotna & J. Misek (Eds.). Legal Knowledge and Information Systems (Vol. 395, pp. 378-380). IOS Press. https://doi.org/10.3233/faia241275
Keeling, R., Chhatwal, R., Huber-Fliflet, N., Zhang, J., Wei, F., Zhao, H., Shi, Y., & Qin, H. (2019). Empirical Comparisons of CNN with Other Learning Algorithms for Text Classification in Legal Document Review. In 2019 IEEE International Conference on Big Data (Big Data) (pp. 2038-2042). Wiley-IEEE Press. https://doi.org/10.1109/bigdata47090.2019.9006248
Kelly, E. P., & Tastle, W. J. (2004). E-Government and the Judicial System: Online Access to Case Information. Electronic Government: An International Journal, 1(2), 166-178. https://doi.org/10.1504/eg.2004.005176
Kerdvibulvech, C. (2024). Big Data and AI-Driven Evidence Analysis: A Global Perspective on Citation Trends, Accessibility, and Future Research in Legal Applications. Journal of Big Data, 11(1). https://doi.org/10.1186/s40537-024-01046-w
Krasadakis, P., Sakkopoulos, E., & Verykios, V. S. (2024). A Survey on Challenges and Advances in Natural Language Processing with a Focus on Legal Informatics and Low-Resource Languages. Electronics, 13(3), 648. https://doi.org/10.3390/electronics13030648
La Torre, M., Dumay, J., & Rea, M. A. (2018). Breaching Intellectual Capital: Critical Reflections on Big Data Security. Meditari Accountancy Research, 26(3), 463-482. https://doi.org/10.1108/medar-06-2017-0154
Lebre de Freitas, J. (2020). Introdução ao processo civil: Conceito e princípios gerais (4.ª ed.). Gestlegal.
Licari, D., & Comandè, G. (2023). ITALIAN-LEGAL-BERT Models for Improving Natural Language Processing Tasks in the Italian Legal Domain. Computer Law & Security Review, 52, 105908. https://doi.org/10.1016/j.clsr.2023.105908
Laukyte, M. (2025). Fernando H. Llano Alonso, Homo Ex Machina. Ética de la inteligencia artificial y Derecho digital ante el horizonte de la singularidad tecnológica. Derechos y Libertades: Revista de Filosofía del Derecho y Derechos Humanos, 53, 345-357. https://doi.org/10.20318/dyl.2025.9468Luban, D. J. (2008). Fairness to Rightness: Jurisdiction, Legality, and the Legitimacy of International Criminal Law (Georgetown Public Law Research Paper No. 1154117). Georgetown University Law Center. https://doi.org/10.2139/ssrn.1154177
Luo, S., & Pan, L. (2026). Big Data Analysis. Springer. https://doi.org/10.1007/978-981-95-5725-7
Mahesh, B. (2020). Machine Learning Algorithms - a review. International Journal Of Science And Research (IJSR), 9(1), 381-386. https://doi.org/10.21275/art20203995
Medina Romero, M. Á., Torres Chávez, T. H. y Ochoa Figueroa, R. (2023). Aplicación de las herramientas de inteligencia artificial en la enseñanza del Derecho: consideraciones sobre su eficacia, limitaciones y desafíos. LATAM Revista Latinoamericana de Ciencias Sociales y Humanidades, 4(3), 673-678. https://doi.org/10.56712/latam.v4i3.1105
Medvedeva, M., Vols, M., & Wieling, M. (2019). Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law, 28(2), 237-266. https://doi.org/10.1007/s10506-019-09255-y
Mercader Uguina, J. R. (2022). Algoritmos e inteligencia artificial en el derecho digital del trabajo. Tirant lo Blanch.
Miller, V. (2025). Students under Surveillance: Big Data Policing and Privacy Rights. Educational Researcher, 54(4), 234-237. https://doi.org/10.3102/0013189x251318346
Muldoon, J., & Wu, B. A. (2023). Artificial Intelligence in the Colonial Matrix of Power. Philosophy & Technology, 36(4), 1-24. https://doi.org/10.1007/s13347-023-00687-8
Murugan, S. K., Sundaram, P. S., Govindaraj, T., & Veeramani, S. (2025). Know Your Law (KYL): A Lawbot for Empowering Citizens. AIP Conference Proceedings, 3175(1), 020056. https://doi.org/10.1063/5.0255500
Ngige, O., Ayankoya, F., Balogun, J., Onuiri, E., Agbonkhese, C., & Sanusi, F. (2023). A Dataset for Predicting Supreme Court Judgments in Nigeria. Data in Brief, 50, 109483. https://doi.org/10.1016/j.dib.2023.109483
Oliveira, R. S. d, & Nascimento, E. G. S. (2025). Analysing Similarities between Legal Court Documents Using Natural Language Processing Approaches Based on Transformers. PLoS ONE, 20(4), e0320244. https://doi.org/10.1371/journal.pone.0320244
Oneto, L., Navarin, N., & Schleif, F. (2022). Advances in Artificial Neural Networks, Machine Learning and Computational Intelligence. Neurocomputing, 507, 311-314. https://doi.org/10.1016/j.neucom.2022.08.001
Peer, E., Brandimarte, L., Samat, S., & Acquisti, A. (2017). Beyond the Turk: Alternative Platforms for Crowdsourcing Behavioral Research. Journal of Experimental Social Psychology, 70, 153-163. https://doi.org/10.1016/j.jesp.2017.01.006
Perkins, M., & Roe, J. (2024). The Use of Generative AI in Qualitative Analysis: Inductive Thematic Analysis with ChatGPT. Journal of Applied Learning & Teaching, 7(1), 390-395. https://doi.org/10.37074/jalt.2024.7.1.22
Peykani, P., Ramezanlou, F., Tanasescu, C., & Ghanidel, S. (2025). Large Language Models: A Structured Taxonomy and Review of Challenges, Limitations, Solutions, and Future Directions. Applied Sciences, 15(14), 8103. https://doi.org/10.3390/app15148103
Pineda, J. E. (2021). Garantías procesales en la aplicación de la inteligencia artificial y el Big Data en el estándar de la prueba penal. CES Derecho, 12(1), 108-125. https://doi.org/10.21615/cesder.12.1.6
Prince-Tritto, P., & Ponce, H. (2023). Exploring the Challenges and Limitations of Unsupervised Machine Learning Approaches in Legal Concepts Discovery. In H. Calvo, L. Martínez-Villaseñor & H. Ponce (Eds.). Advances in Soft Computing (pp. 52-67). Springer. https://doi.org/10.1007/978-3-031-47640-2_5
Rahman, M. M., Gony, N., Rahman, M. M., Rahman, M. M., & Sd, M. K. S. (2025). Natural Language Processing in Legal Document Analysis Software: A Systematic Review of Current Approaches, Challenges, and Opportunities. International Journal of Innovative Research and Scientific Studies, 8(3), 5026-5042. https://doi.org/10.53894/ijirss.v8i3.7702
Rinaldin, G. (2026). From the Asilomar Principles to the AI Act: Five Years of AI Regulation and Applications in a Critical and Comparative Perspective. Physica Medica: European Journal of Medical Physics, 142, 105327. https://doi.org/10.1016/j.ejmp.2025.105327
Rolf, R. E. (2025). Using Generative Artificial Intelligence in a Contract Simulation to Promote Student Learning in Business Law. Journal of Legal Studies Education, 42(1), 7-22. https://doi.org/10.1111/jlse.12154
Salem, N., Al-Tarawneh, K., Hudaib, A., Salem, H., Tareef, A., Salloum, H., & Mazzara, M. (2024). Generating database schema from requirement specification based on natural language processing and large language model. Computer Research And Modeling, 16(7), 1703-1713. https://doi.org/10.20537/2076-7633-2024-16-7-1703-1713
Singh, D., Tomer, A., Kaushik, T. K., Singh, R., & Kumar, S. (2024). The Potential Applications of Artificial Intelligence and Machine Learning in India’s Legal System. In 2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE) (pp. 820-826). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ic3se62002.2024.10592961
Socol de la Osa, D. U., & Remolina, N. (2024). Artificial Intelligence at the Bench: Legal and Ethical Challenges of Informing—or Misinforming—Judicial Decision-Making through Generative AI. Data & Policy, (6), e59. https://doi.org/10.1017/dap.2024.53
Solar Cayón, J. I. (2021). La inteligencia artificial en la práctica jurídica: Automatización y aprendizaje automático en el derecho. Aranzadi.
Hon, W. K., Millard, C., Singh, J., Walden, I., & Crowcroft, J. (2016). Policy, legal and regulatory implications of a Europe-only cloud. International Journal Of Law And Information Technology, 24(3), 251-278. https://doi.org/10.1093/ijlit/eaw006
Stępień-Załucka, B. (2025). Algorithms and Artificial Intelligence as a Threat to Fundamental Rights. En Algoritmos e inteligencia artificial como amenaza a los derechos fundamentales (pp. 1-12). https://doi.org/10.1007/978-3-319-31739-7_233-1
Su, J. (2023). The Use of Big Data in Criminal Justice and Its Challenges. Peking University Law Journal, 11(1), 105-125. https://doi.org/10.1080/20517483.2023.2223851
Талапина, Э. (2025). Прозрачность алгоритмов искусственного интеллекта. Law Journal of the Higher School of Economics, 18(3), 4-27. https://doi.org/10.17323/2072-8166.2025.3.4.27
Tong, A., Liu, Y., & Zhang, W. (2026). Generative AI in Judicial Processes: Efficiency, Accuracy, and Consistency Analysis. Journal of Artificial Intelligence and Law, 34(2), 1-19. https://doi.org/10.1007/s44196-025-00789-3
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., . . . Alonso-Fernández, S. (2021). Declaración PRISMA 2020: una guía actualizada para la publicación de revisiones sistemáticas. Revista Española de Cardiología, 74(9), 790-799. https://doi.org/10.1016/j.recesp.2021.06.016
Urueña, R. (2019). Autoridad algorítmica: ¿cómo empezar a pensar la protección de los derechos humanos en la era del “big data”? Latin American Law Review, (2), 99-124. https://doi.org/10.29263/lar02.2019.05
Van Der Aa, H., Di Ciccio, C., Leopold, H., & Reijers, H. A. (2019). Extracting Declarative Process Models from Natural Language. En Lecture notes in computer science (pp. 365-382). https://doi.org/10.1007/978-3-030-21290-2_23
Venkadapathi, V., Murugan, S., Shanmugavel, S. B., Veeriaya, D., & Balaganapathy, R. (2026). Machine Learning in Law: Unveiling the AHKPSV Algorithm for Improved Legal Case Outcome Forecasts. International Journal of Machine Learning and Cybernetics, 17(2), 81. https://doi.org/10.1007/s13042-025-02959-5
Wan, X., & Jin, P. (2020). Judicial Statistics Based on Big Data Context. In M. Atiquzzaman, N. Yen & Z. Xu (Eds.). Big Data Analytics for Cyber-Physical System in Smart City. BDCPS 2019. Advances in Intelligent Systems and Computing (Vol. 1117, pp. 877-884). Springer. https://doi.org/10.1007/978-981-15-2568-1_119
Wang, Y., Gao, J., & Chen, J. (2020). Deep Learning Algorithm for Judicial Judgment Prediction Based on BERT. In 2020 5th International Conference on Computing, Communication and Security (ICCCS) (pp. 1-6). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/icccs49678.2020.9277068
Wang, Z. (2023). Law Case Teaching Combining Big Data Environment with SPSS Statistics. International Journal of Web-Based Learning and Teaching Technologies, 19(1), 1-15. https://doi.org/10.4018/ijwltt.334848
Wei, L. (2022). Construction of the Interactive Relationship between Law Enforcement and Legislation Based on the Background of Big Data. Mathematical Problems in Engineering, 2022, 1-6. https://doi.org/10.1155/2022/6888268
Wen, L. (2022). Development Analysis of Cross-Border E-Commerce Logistics Based on Big Data Technology Under Safety Law Protection. International Journal of Information Systems in the Service Sector, 14(2), 1-14. https://doi.org/10.4018/ijisss.290547
Wickramasinghe, I., & Kalutarage, H. (2020). Naive Bayes: Applications, Variations and Vulnerabilities. Soft Computing, 25(3), 2277-2293. https://doi.org/10.1007/s00500-020-05297-6
Wu, W., & Zhao, Y. (2025). Big Data Grace: Implementations of Feature Engineering and Data Science Algorithms for Environmental Protection Law. Alexandria Engineering Journal, 125, 256-264. https://doi.org/10.1016/j.aej.2025.03.121
Alakbarova, I., & Alizada, D. (2024b). A New Approach to Improving Search Efficiency in Digital Libraries. International Journal Of Intelligent Systems And Applications, 16(2), 13-23. https://doi.org/10.5815/ijisa.2024.02.02
Xu, J. (2021). Research on Judicial Big Data Text Mining and Sentencing Prediction Model. Journal of Physics: Conference Series, 1883(1), 012158. https://doi.org/10.1088/1742-6596/1883/1/012158
Yadav, U., & Kumar, R. (2025). Comprehensive Analysis of Artificial Intelligence in Context of Judicial System in India. AIP Conference Proceedings, 3335(1), 030036. https://doi.org/10.1063/5.0295077
Yuan, X., Chen, Y., & Zou, B. (2025). Research on Prediction of Legal Decisions Based on Graph Neural Network with Attention Mechanism. In 2025 3rd International Conference on Data Science and Network Security (ICDSNS) (pp. 1-5). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/icdsns65743.2025.11168770
Zhang, C., & Xu, Y. (2023). Institutional Innovation Essence and Knowledge Innovation Goal of Intellectual Property Law in the Big Data Era. Journal of Innovation & Knowledge, 8(4), 100417. https://doi.org/10.1016/j.jik.2023.100417
Zhang, Y., Jiang, J., & Li, Y. (2023). Intelligent Analysis and Application of Judicial Big Data Sharing Based on Blockchain. In Proceedings of the International Conference on Artificial Intelligence and Big Data (ICAIBD) (pp. 592-596). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/icaibd57115.2023.10206326
Zheng, L. (2025). Fairness Verification Algorithms and Bias Mitigation Mechanisms for AI Criminal Justice Decision Systems. Journal of Computational Methods in Sciences and Engineering. https://doi.org/10.1177/14727978251385141
Ződi, Z. (2017). Law and Legal Science in the Age of Big Data. Intersections. East European Journal of Society and Politics, 3(2). https://doi.org/10.17356/ieejsp.v3i2.324