ARTIFICIAL INTELLIGENCE: FROM THE ANALYSIS OF DISCRIMINATORY BIAS TO THE SUPREMACY OF HUMAN EFFICIENCY OVER NUMERICAL EFFICIENCY IN THE JUDICIARY

Abstract

The integration of artificial intelligence (AI) into legal systems is growing globally, promising greater efficiency and cost reduction. However, this evolution faces ethical and legal challenges, especially in ensuring that the use of AI does not perpetuate discriminatory biases in legal proceedings. Although algorithms can process large volumes of data quickly, ethical and sensitive interpretation of complex cases is still a human skill. The focus of the research is to investigate how AI can amplify biases present in training data, and whether this processing generates unfair judicial decisions, especially for minority groups. The objective is to contribute to the development of guidelines that promote the ethical use of AI in the judiciary, ensuring impartiality and justice for all citizens, with respect for fundamental rights. To this end, the exploratory deductive method was used, through doctrines, scientific articles, theses, dissertations, laws, jurisprudence, and scientific document platforms, such as: Google Scholar, Scopus and Web of Science.