The integration of Artificial Intelligence (AI) into criminal justice systems presents a complex landscape of opportunities and challenges. This paper examines the legal implications of AI applications in various facets of criminal justice, from predictive policing to sentencing algorithms that can analyse large datasets, identify patterns, and provide insights for quick and quality decision-making by stakeholders. While AI promises enhanced efficiency and data-driven decision-making, it simultaneously raises significant concerns about fairness, transparency, and the preservation of due process rights. This paper analyzes case studies from multiple jurisdictions, highlighting both successful implementations and controversial failures of AI systems in law enforcement and judicial processes. This paper also identifies several key legal and ethical challenges, including algorithmic bias, lack of transparency in decision-making processes, and the potential erosion of human judgment in critical legal determinations. This study emphasizes the need for continuous human oversight, regular audits of AI systems, and the establishment of clear accountability mechanisms. This study employs a multidisciplinary approach, combining legal analysis and ethical philosophy to evaluate the current state of AI in criminal justice and project future trajectories. The article concludes by outlining policy recommendations and best practices for lawmakers, judiciary, and law enforcement agencies to develop strategies to meet the realities of Artificial Intelligence-enabled crime
Bamidele et al. (Tue,) studied this question.