Artificial intelligence in justice: A theoretical analysis of methodologies and accessibility
Keywords:
artificial intelligence, judicial systems, natural language processing, accessibility to justice, predictive methodsAbstract
The implementation of artificial intelligence (AI) in judicial systems is presented as an innovative solution to improve efficiency and accessibility to justice. The objective of the article was to evaluate current methodologies used for the implementation of AI in judicial systems and their effectiveness in enhancing accessibility to justice. Through an exhaustive theoretical review, techniques such as natural language processing (NLP), predictive analysis, and decision-support systems were analyzed. The results indicated that these methodologies not only improve efficiency and speed in case resolution but also promote greater consistency and fairness in judicial decisions. However, limitations were identified, including lack of transparency in algorithms and resistance to change among legal professionals. It is concluded that, although AI has the potential to positively transform the administration of justice, developing robust ethical frameworks and fostering ongoing training for legal professionals is crucial for effective implementation. This study highlights the need for further research and refinement of these methodologies to maximize the benefits of AI in the judicial system.
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Copyright (c) 2024 Edgardo Cristiam Iván López De La Cruz
This work is licensed under a Creative Commons Attribution 4.0 International License.
