Gobernanza algorítmica y legitimidad judicial en un Tribunal Peruano
Palabras clave:
inteligencia artificial en los tribunales, debido proceso, gobernanza algorítmica, supervisión humana, legitimidad judicial
Resumen
La incorporación de herramientas de inteligencia artificial (IA) en el ámbito judicial ha intensificado el debate sobre su compatibilidad con las garantías estructurales del debido proceso. Este estudio buscó describir la percepción de los profesionales del derecho del uso de la IA en procedimientos del sistema de justicia peruano. La metodología consistió en una investigación cualitativa de alcance exploratorio desarrollada en el Distrito Judicial de Ica (Perú), basada en entrevistas semiestructuradas a operadores jurídicos del sistema judicial con experiencia activa en procedimientos civiles, penales y administrativos. Los hallazgos evidencian una aceptación condicionada del uso de inteligencia artificial en el sistema judicial peruano. Los participantes reconocen su utilidad para actividades de apoyo, como búsqueda jurisprudencial, organización documental y análisis preliminar de información; sin embargo, rechazan su utilización como mecanismo sustitutivo de la decisión judicial humana. Se concluye que la legitimidad del uso de algoritmos en la justicia depende de la supervisión humana significativa, la trazabilidad de los resultados, la explicabilidad de los sistemas y el registro formal de su utilización dentro del expediente judicial.
Citas
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Sourdin, T. (2018). Judge v robot? Artificial intelligence and judicial decision-making. The University of New South Wales Law Journal, 41(4). https://doi.org/10.53637/zgux2213
Strauss, A., & Corbin, J. (2002). Bases de la investigación cualitativa: Técnicas y procedimientos para desarrollar la teoría fundamentada. Editorial Universidad de Antioquia.
Susskind, R. (2019). Online courts and the future of justice. Oxford University Press. https://doi.org/10.1093/oso/9780198838364.001.0001
Tripathi, P., Malik, A., & Aggarwal, A. (2025). Artificial intelligence in judicial decision-making: Opportunities, risks and ethical implications. En Artificial intelligence-driven research in modern legal education in India (pp. 5–31). Integrity Education.
Veale, M., & Zuiderveen Borgesius, F. J. (2021). Demystifying the draft EU Artificial Intelligence Act. Computer Law & Security Review, 42, 105589. https://doi.org/10.1016/j.clsr.2021.105589
Wachter, S., Mittelstadt, B., & Russell, C. (2017). Counterfactual explanations without opening the black box: Automated decisions and the GDPR. En arXiv [cs.AI]. https://doi.org/10.48550/arXiv.1711.00399
Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2019). Artificial intelligence and the public sector—applications and challenges. International Journal of Public Administration, 42(7), 596–615. https://doi.org/10.1080/01900692.2018.1498103
Casey, A. J., & Niblett, A. (2016). Self-driving laws. The University of Toronto Law Journal, 66(4), 429–442. https://doi.org/10.3138/utlj.4006
Chouldechova, A. (2017). Fair prediction with disparate impact: A study of bias in recidivism prediction instruments. Big Data, 5(2), 153–163. https://doi.org/10.1089/big.2016.0047
Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). Sage Publications.
Denzin, N. K., & Lincoln, Y. S. (2018). The Sage handbook of qualitative research (5th ed.). Sage Publications.
Dressel, J., & Farid, H. (2018). The accuracy, fairness, and limits of predicting recidivism. Science Advances, 4(1), eaao5580. https://doi.org/10.1126/sciadv.aao5580
Engels, C., Linhardt, L., & Schubert, M. (2025). Code is law: how COMPAS affects the way the judiciary handles the risk of recidivism. Artificial Intelligence and Law, 33(2), 383–404. https://doi.org/10.1007/s10506-024-09389-8
European Commission for the Efficiency of Justice. (2018). European ethical charter on the use of artificial intelligence in judicial systems and their environment. Council of Europe. https://rm.coe.int/ethical-charter-en-for-publication-4-december-2018/16808f699c
European Parliament & Council of the European Union. (2024). Regulation (EU) 2024/1689 laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). Official Journal of the European Union. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32024R1689
Flick, U. (2015). Introducción a la investigación cualitativa (3.ª ed.). Ediciones Morata.
Grimmelikhuijsen, V., & Meijer, A. (2022). Legitimacy of algorithmic decision-making: Six threats and the need for a calibrated institutional response. Perspectives on Public Management and Governance, 5(3), 232–242. https://doi.org/10.1093/ppmgov/gvac008
Hernández-Sampieri, R., & Mendoza Torres, C. P. (2018). Metodología de la investigación: Las rutas cuantitativa, cualitativa y mixta. McGraw-Hill Education.
Hildebrandt, M. (2018). Law as computation in the era of artificial legal intelligence: Speaking law to the power of statistics. The University of Toronto Law Journal, 68(supplement 1), 12–35. https://doi.org/10.3138/utlj.2017-0044
Malgieri, G. (2023). Risk-based approaches to AI governance under the EU AI Act. European Journal of Risk Regulation, 14(3), 482–497. https://doi.org/10.1017/err.2023.34
Malgieri, G. (2024). Artificial intelligence, automated decision-making, and accountability under the EU AI Act. Computer Law & Security Review, 52, 105907. https://doi.org/10.1016/j.clsr.2024.105907
McGinnis, J. O., & Pearce, R. G. (2014). The great disruption: How machine intelligence will transform the role of lawyers in the delivery of legal services. Fordham Law Review, 82(6), 3041–3066. https://ir.lawnet.fordham.edu/flr/vol82/iss6/11
Merriam, S. B., & Tisdell, E. J. (2016). Qualitative research: A guide to design and implementation (4th ed.). Jossey-Bass.
Mittelstadt, B. (2019). Principles alone cannot guarantee ethical AI. Nature Machine Intelligence, 1(11), 501–507. https://doi.org/10.1038/s42256-019-0114-4
Münch, L. A. C., & Ferraz, T. S. (2024). Exploring defuturing to design artificial-intelligence artifacts: A systemic-design approach to tackle litigiousness in the Brazilian Judiciary. Laws, 13(1), 4. https://doi.org/10.3390/laws13010004
Neuwirth, R. J. (2022). The EU artificial intelligence act: Regulating subliminal AI systems. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4135848
Pasquale, F. (2015). The black box society and algorithmic accountability. Law and Contemporary Problems, 78(1–2), 1–18.
Rudin, C. (2019). Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nature Machine Intelligence, 1(5), 206–215. https://doi.org/10.1038/s42256-019-0048-x
Saldaña, J. (2021). The coding manual for qualitative researchers (4th ed.). Sage Publications.
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
Sourdin, T. (2018). Judge v robot? Artificial intelligence and judicial decision-making. The University of New South Wales Law Journal, 41(4). https://doi.org/10.53637/zgux2213
Strauss, A., & Corbin, J. (2002). Bases de la investigación cualitativa: Técnicas y procedimientos para desarrollar la teoría fundamentada. Editorial Universidad de Antioquia.
Susskind, R. (2019). Online courts and the future of justice. Oxford University Press. https://doi.org/10.1093/oso/9780198838364.001.0001
Tripathi, P., Malik, A., & Aggarwal, A. (2025). Artificial intelligence in judicial decision-making: Opportunities, risks and ethical implications. En Artificial intelligence-driven research in modern legal education in India (pp. 5–31). Integrity Education.
Veale, M., & Zuiderveen Borgesius, F. J. (2021). Demystifying the draft EU Artificial Intelligence Act. Computer Law & Security Review, 42, 105589. https://doi.org/10.1016/j.clsr.2021.105589
Wachter, S., Mittelstadt, B., & Russell, C. (2017). Counterfactual explanations without opening the black box: Automated decisions and the GDPR. En arXiv [cs.AI]. https://doi.org/10.48550/arXiv.1711.00399
Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2019). Artificial intelligence and the public sector—applications and challenges. International Journal of Public Administration, 42(7), 596–615. https://doi.org/10.1080/01900692.2018.1498103
Publicado
2026-08-17
Cómo citar
Fernández Pacheco, Y., Vera Poma, R. G., & Ronceros Morales, C. (2026). Gobernanza algorítmica y legitimidad judicial en un Tribunal Peruano. Revista Venezolana De Gerencia, 31(115), e3111513. https://doi.org/10.52080/rvgluz.31.115.13
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