The legal universe has been witnessing a fast-paced technological revolution in its processes, which have equally affected private and public institutions. This phenomenon has been discussed by several law schools worldwide. On July 27, the UCL – Law, Economics & Society, the Institute for Studies in Competition Law and Policy (IMEDIPA), and the European Public Law Organization (EPLO) hosted the Artificial Cosmoi and the Law conference in Athens, Greece, featuring professors and researchers from FGV’s São Paulo Law School (Direito SP), Marina Feferbaum and Alexandre Pacheco, coordinators of Direito SP’s Nucleus for Teaching Methodology and Law and Innovation Research Group (GEPI), respectively.

The professors made the presentation ‘Impact of Machine Learning Technologies on the Legal Practice of Repetitive Litigation,’ describing how private and public players have been used to optimize repetitive resources, analyzing the transformations caused by the use of technology, and discussing how these technologies can potentially cut costs in the Brazilian judicial system and restructure legal activities.

According to the researchers, the expansion of the Brazilian judicial dispute settlement system – which costs approximately BRL 68.4 billion (1.2% of the GDP) per year – was achieved at the expense of small causes. “This scenario raises costs and human resources, and also generates a large volume of cases, involving multiple parties,” said Alexandre Pacheco.

According to Marina Feferbaum, many institutions started to invest in new technologies to streamline administration activities. “An example is the Brazilian Superior Labor Court, which has been experimenting to replace its case sorting and distribution systems with automated tools, reassigning part of its personnel in charge of these activities to more relevant tasks,” she said.

In private law practice, several firms are also investing in new technologies, mainly in the so-called repetitive disputes, increasing the financial return on each case filed. An example is JBM, which created a company called Finch Solutions to use of neural networks and other teaching tools to extract information from documents and cases, and create other low-complexity pieces.