Trends Of Machine Learning Techniques for Enhancing Court Decision Making

Artificial intelligence (AI) techniques have increased in different fields and lately it supports several Decision Support Systems (DSS). It can assist the judicial decision-making process. Prediction is possible in various cases, such as predicting the outcome of construction litigation, crime-cases, parental rights, divorces, and tax law. Machine learning (ML) methods can function as support decision tools in the legal system. Aimed to impart a systematic literature review (SLR) of studies concerning the prediction of court decisions via ML. It analyzed the ML methods and techniques used in predicting court decisions. It used Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Data were chosen from three databases: IEEE Digital Library, Scopus, and Science Direct. Outcomes found: types of judicial decisions using the ML techniques for law text interpretation, transit, crime, human right, legal assistance and electoral field; on the other hand, scholars agree on the most used ML method have been supervised, unsupervised, and deep learning. The ML has been applied in developed countries such as China, India, US, Russia, and, in recent years, in undeveloped countries: Thailand, Morocco, and Colombia. A few of society agree on the application to legal tasks of the empirical and quantitative methods on which the algorithmic models of ML. The AI is working as (DSS) in the first time, but the final decision is the judge; therefore, judges and artificial intelligence practitioner’s need work together to improve the second stage and improve the court decision.