Impact of Artificial Intelligence on the Sphere of the Judiciary and the Perspectives for Future Research

Abstract

Artificial intelligence tools are increasingly common in the judiciary. While robot judges have not been invented yet, introducing new AI technologies is spreading and contributing to the transformation of court activities. This article discusses AI's impact on the judiciary and its potential influence on future research, aiming to improve current legislation. The author outlines two key areas of influence: the implementation of AI in professional tasks and the increasing awareness about AI. Artificial intelligence in the judiciary is expected to lead to more effective legal proceedings and ensure non-bias by excluding biases caused by inappropriate training data. Interest in this topic is driven by the desire to find potential areas for improving judges' activities, although artificial intelligence is not anticipated to replace them. The author describes different ways in which AI can impact the judiciary. These include using AI as a support tool for making legally binding decisions, taking on secondary tasks in place of judges, strengthening reliability and enhancing security in adopting modern technologies for legal proceedings, and increasing awareness of artificial intelligence. Further development and implementation of AI technologies may result in biased outcomes, external interference, and errors, highlighting the need for future research. This article explains why artificial intelligence in the judiciary requires more attention. Many questions still remain open, such as the legal support of innovative technologies for secondary tasks and guarantees for following generally accepted ethical principles of AI when used by judges. Certainly, scientists and researchers should promote new possibilities for the judiciary by developing and enhancing special software for this field. Key words: artificial intelligence, AI tools, artificial intelligence in the judiciary, transformation of the judiciary, generative artificial intelligence technologies, biased outcomes, human judges, awareness of AI, reliable AI.