Due process, cognitive bias and artificial intelligence in judicial decision-making

Abstract

This study analyzes the legal and psychological implications of artificial intelligence in judicial decision-making, with particular emphasis on its effects on due process guarantees. The research adopts a qualitative, doctrinal, and comparative approach based on a systematic review of academic literature and international regulatory frameworks related to AI governance and digital justice. From a legal perspective, the findings identify risks associated with algorithmic opacity, automated bias, and the weakening of reasoned judicial decisions, potentially affecting equality before the law, judicial impartiality, and the right to defense. From a psychological perspective, the study highlights the influence of cognitive biases, particularly automation bias and anchoring effects, on judicial actors interacting with AI systems, which may reduce autonomy and critical reasoning. The results also indicate that procedural fairness and public trust in judicial institutions may be undermined when algorithmic processes lack transparency and explainability. In response to these challenges, the study proposes a hybrid model of adjudication in which artificial intelligence functions as a decision-support tool under strict human supervision, ensuring the protection of fundamental rights and the preservation of cognitive integrity in judicial decision-making processes.