AI-BASED CRIMINAL JUSTICE DECISION-MAKING: ACCOUNTABILITY, TRANSPARENCY, AND HUMAN RIGHTS

Abstract

Policing, criminal investigations, evidence appraisal, and judicial decision-making are all being transformed by the growing integration of artificial intelligence (AI) into criminal justice systems. With a focus on predictive policing, algorithmic risk assessment, facial recognition technology, and AI-supported evidence analysis, this article critically investigates the legal and human rights implications of AI-assisted criminal justice. The study assesses how well these technologies align with basic criminal justice principles, such as the presumption of innocence, the right to a fair trial, due process, equality before the law, and the principle of legality, using a doctrinal and comparative legal research methodology. The analysis highlights significant issues that could compromise judicial discretion and procedural fairness, including algorithmic opacity, prejudice, accountability deficiencies, data privacy concerns, and the increasing dependence on automated decision-making. Even though AI has the ability to increase productivity, uniformity, and investigative accuracy, its use without sufficient legal protections runs the risk of escalating already-existing disparities and eroding public trust in the legal system. The paper makes the case that AI should support human judgment rather than replace it. It concludes that in order to guaranty that AI-driven criminal justice systems continue to be compliant with international human rights standards, constitutional guaranties, and the rule of law, effective regulatory frameworks, transparency, independent oversight, explainability, and meaningful human review are crucial.