AI Accountability in Judicial Proceedings: An Actor–Network Approach

This paper analyzes the impact of AI systems in the judicial domain, adopting an actor–network theory (ANT) framework and focusing on accountability issues emerging when such technologies are introduced. Considering three different types of AI applications used by judges, this paper explores how introducing non-accountable artifacts into justice systems influences the actor–network configuration and the distribution of accountability between humans and technology. The analysis discusses the actor–network reconfiguration emerging when speech-to-text, legal analytics, and predictive justice technologies are introduced in pre-existing settings and maps out the changes in agency and accountability between judges and AI applications. The EU legal framework and the EU AI Act provide the juridical framework against which the findings are assessed to check the fit of new technological systems with justice system requirements. The findings show the paradox that non-accountable AI can be used without endangering fundamental judicial values when judges can control the system’s outputs, evaluating its correspondence with the inputs. When this requirement is not met, the remedies provided by the EU AI Act fall short in costs or in organizational and technical complexity. The judge becomes the unique subject accountable for the use and outcome of a non-accountable system. This paper suggests that this occurs regardless of whether the technology is AI-based or not. The concrete risks emerging from these findings are that these technological innovations can lead to undue influence on judicial decision making and endanger the fair trial principle.