Criminal Organizations, Drugs and the Youth

An emerging field applied in the legal domain is Artificial Intelligence, by which manual tasks are being automated. The main objective of this paper is an attempt to study, design, and evaluate a mechanism that is able to highlight legal documents in Criminal Justice Administration (CJA) with valuable information, and filter out the irrelevant data to make CJS more efficient and effective. AI applications are set to infiltrate the entirety of the legal services market and could dramatically expand the value and usefulness of this field, while helping it better use the mass data available to its practitioners. The legal system is quite specific with its own laws, constitution, and trial process and we have to take into consideration specifics in the structure of the documents: medical records, police records, affidavits, emergency call transcripts, etc. The judgments and other data for criminal cases are available at various legal databases (SCC Online, Manupatra, Westlaw, Lexix-nexis etc.). This data can be utilized regarding the rate of crimes and connect it with the rate of conviction, to establish a trend. Their main characteristic is an occurrence of a known entity, such as a victim, defendant, or location of an event that is part of the case. With the help of these machine learning process expected outcome may be to develop Legal Prediction tools to predict the outcomes of a criminal case by reference to earlier decisions.