Intelligent decision support systems in legal decision making: Selected issues from a theoretical and legal perspective

Abstract

The growing complexity of social relations and the rapid development of artificial intelligence prompt renewed reflection on the role of Intelligent Decision Support Systems (IDSS) in legal decision-making. The study aims to determine the extent to which, and the conditions under which, IDSS can, acting as complementary tools, enhance the efficiency and accuracy of judgments without undermining the constitutive role of humans in the interpretation of law. The research methods used include: decision analysis, which was employed to captured the dynamics of legal phenomena; the logico-linguistic method, which was applied to assess the soundness of arguments; and comparative analysis, which focused on regulations (notably the AI Act) and practical solutions implemented in Estonia and China. IDSS are already capable of handling simple, repetitive cases, thereby relieving courts and reducing lengthy proceedings. In complex cases that require the weighing of evidence, the systems should remain purely advisory, with mandatory judicial verification. Owing to algorithmic opacity, rigorous monitoring of data quality and the introduction of accountability mechanisms are imperative. For straightforward matters, a hybrid model – ‘machine at first instance, human at second instance’ – appears optimal. It should be noted that the effective use of IDSS also demands the parallel development of lawyers’ digital competencies and the introduction of detailed sector-specific regulations.