Work

Predicting Brazilian Court Decisions

Year: 2022

Type: article

Abstract: Predicting case outcomes is useful for legal professionals to understand case law, file a lawsuit, raise a defense, or lodge appeals, for instance. However, it is very hard to predict legal decisions since this requires extracting valuable information from myriads of cases and other documents. Moreover, legal system complexity along with a huge volume of litigation make this problem even harder. This paper introduces an approach to predicting Brazilian court decisions, including whether they will be unanimous. Our methodology uses various machine learning algorithms, including classifiers and state-of-the-art Deep Learning models. We developed a working prototype whose F1-score performance is ~80.2% by using 4,043 cases from a Brazilian court. To our knowledge, this is the first study to present methods for predicting Brazilian court decision outcomes.

Source: PeerJ Computer Science

DOI: 10.7717/peerj-cs.904

Authors: André Lage-Freitas, Héctor Allende-Cid, Orivaldo Santana, Lívia Oliveira-Lage

Institutions: Universidade Federal de Alagoas, Pontificia Universidad Católica de Valparaíso, Universidade Federal do Rio Grande do Norte, Governo do Estado de Alagoas

Language: English

Topic: Artificial Intelligence in Law

Subfield: Political Science and International Relations

Field: Social Sciences

Domain: Social Sciences

SDG: Peace, justice, and strong institutions

Open Access status: gold

Estimated APC paid: $1,395