Digital Twin in Smart Judicial Systems: Reconstructing Legal Liability and Algorithmic Justice within the Framework of Digital Sovereignty

This research examines the transformative role of Digital Twin technology in the evolution of smart judicial systems, positioning it as a foundational tool for redefining legal liability in algorithm-driven environments. Moving beyond its traditional engineering applications, the study conceptualizes the Digital Twin as a predictive and analytical legal instrument capable of simulating judicial processes, modeling dispute scenarios, and anticipating legal outcomes. The paper critically explores how the integration of artificial intelligence, big data, and real-time system replication challenges classical doctrines of legal responsibility, particularly causation, fault, and accountability. It argues for a paradigm shift from linear legal reasoning to a multi-layered, dynamic model of algorithmic liability that accommodates autonomous decision-making systems. Furthermore, the study addresses the implications of Digital Twin deployment within the broader context of digital sovereignty, highlighting jurisdictional complexities, cross-border data governance, and regulatory fragmentation. Through a comparative analytical approach, the research evaluates emerging legal frameworks and proposes a hybrid regulatory model that balances innovation with judicial integrity. Ultimately, this paper contributes to the interdisciplinary discourse on Legal Tech by offering a forward-looking framework for integrating Digital Twin technologies into judicial infrastructures, aiming to enhance transparency, efficiency, and predictive justice while safeguarding fundamental legal principles.