Artificial Intelligence and Criminal Justice Efficiency in Pakistan: A Critical Analysis of Machine Learning Applications for Case Backlog Reduction, Investigative Enhancement, and Fair Trial Safeguards

Abstract

The criminal justice system in Pakistan still suffers from delays, disjointed records, poor investigation capabilities, low conviction rates, and significant case backlog. This study analyzes the potential of AI and ML in the criminal justice system and their implications for constitutional safeguards and the efficiency of the system. It examines potential applications in the areas of police investigation, assessment of evidence, management of prosecutions, judicial scheduling, legal research and integrated case tracking using a doctrinal, comparative and policy approach. Lessons are learnt from India, the United Kingdom, Estonia, China and European governance structure. The research shows potential for low-risk use cases, such as intelligent case management, digital evidence review, witness coordination and automated administrative support, to help decrease delays and increase institutional coordination. Bias, privacy, transparency, accountability, judicial independence and the right to a fair trial, however, are of serious concern with regard to predictive policing, risk scoring, facial recognition and automated adjudication. The paper calls for "phased implementation, human oversight, explainability, data protection legislation, independent audits and statutory regulation prior to large-scale adoption.