Classifying Judicial Decisions with Artificial Intelligence: Part One
Legal professionals consume several types of legal information, two of which are the main ones: law and jurisprudence. The law is an abstract norm, that is, it has not been applied to a concrete case. Jurisprudence, on the other hand, is a concrete rule, made to solve a case submitted to the Judiciary.
Although it is relatively easy to know the laws, as they are published in official repositories, it is much more complex to know the jurisprudence. The most widely used legislative repository is that of the Plateau and it illustrates well how the various forms of federal legislation are organized and consumed in Brazil. In contrast, There are several courts and each one is responsible for publishing its own jurisprudence .
In general, courts treat such data as natural language documents, with a relatively limited additional layer of metadata.
Thus, there are few filters to access this information, for example: the date of the judgment, the name of the judge, the body to which this judge belongs, the name and position of each party in the process, etc. We did not, however, find any public repository organized around the dimension of the result of the judgment, whether favorable or unfavorable its outcome.
Let's consider the following use case:
It is possible to imagine that a lawyer from a bank does a research on case law in a certain court to assess the chance of success of a new lawsuit.
As the STF's judgment base is indexed, it can, with some ease, find concrete cases that dealt with a certain topic. However, the lawyer has a lot of difficulty in finding, within this topic, which were the cases won by banks and in which the same banks were defeated.
The usefulness of developing a solution that understands which are the favorable and unfavorable cases lies in enabling an aggregate consultation also by this dimension, referring to the result of the judgment. After all, the professional consultation almost always has an interested side, in such a way that knowing the outcome of the case is very important information for the practical life of legal professionals.
In the coming weeks, we will publish here the journey of several of DireitoTec's researchers, dedicated to mapping tens of thousands of STF judgments. This will make it possible to create a foundation for artificial intelligence training in such a way that it is possible to automatically classify the outcome of a judgment. What about? Sounds promising?
This post is part of a series. See the Next post .