Robot Judges, two practical approaches to their concept

Authors

DOI:

https://doi.org/10.51302/rtss.2024.20111

Keywords:

robot judge, artificial intelligence, Justice administration, rule-based resolution, self-adaptive approach, codification, predictability, natural language processing, impact, GPT-4

Abstract

In today's digital era, the possibility of integrating artificial intelligence systems into the legal field has sparked a profound debate about automated justice administration. This article explores two paradigmatic approaches in conceptualizing a "robot judge": the rule-based and the adaptive. While the former focuses on an explicit encoding of the law, ensuring predictability and transparency, inspired by AlphaZero, the latter, inspired by AlphaGo, continuously adapts to jurisprudence, offering flexibility and evolutionary capacity. Through a detailed analysis, the advantages, limitations, and potential applications of both models are discussed. Likewise, two specific examples of a Robot Judge based on each of the models are shown, all based on Python and Tkinter, for AI resolution of lawsuits related to the termination of employment contracts due to delays in salary payments and on the review of permanent disabilities due to improvement.

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Author Biography

Javier Ercilla García, Magistrado del Juzgado de lo Social n.º 10 – Las Palmas de Gran Canaria (España)

Magistrado especialista en jurisdicción social. Cuenta con una sólida formación jurídica y técnica. Destaca por sus publicaciones y ponencias sobre la incidencia de las nuevas tecnologías, especialmente la inteligencia artificial y la robótica en el ámbito laboral y la Administración de justicia. Ha sido galardonado con el Premio a la Calidad de la Justicia 2020 en la modalidad «Justicia más eficaz» y es autor de diversos proyectos de automatización y gestión de sentencias utilizando lenguajes de programación como Python. https://orcid.org/0009-0006-5930-2574

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Published

2024-06-14

How to Cite

Ercilla García, J. (2024). Robot Judges, two practical approaches to their concept. Revista De Trabajo Y Seguridad Social. CEF, (481). https://doi.org/10.51302/rtss.2024.20111