Digital Criminal Investigations in the Era of Artificial Intelligence: A Comprehensive Overview

Abstract

Artificial Intelligence (AI) has been integrated within digital criminal investigations comprehensively with the help of associated methodologies, legal ramifications, and its overarching impact on the justice system. This study adopted a multifaceted approach encompassing qualitative, descriptive, and analytical methods, drawing its data primarily from an array of legal documents and scholarly literature. Through its investigation, this study elucidated the pivotal role that AI plays within law enforcement, encompassing aspects such as arrest procedures, release decisions, sentencing processes, prediction of recidivism, identification of criminal activities and patterns, as well as the apprehension of suspects through advanced audio analysis techniques. The findings underscore the transformative potential of machine learning techniques in enhancing the analysis and organization of case data. The study provides a series of recommendations aimed at optimizing the utilization of AI in digital criminal investigations. These recommendations advocate for the prioritization of high-risk cases through the incorporation of diverse data sources to facilitate well-informed decision-making. Additionally, the study advocates for the deployment of AI in crime prediction, suspect identification, and the reinforcement of security measures. Furthermore, it underscores the importance of implementing AI-powered biometric identification (Bio-ID) systems to fortify identity verification processes. Lastly, the study advocates for the implementation of intelligent surveillance solutions to proactively prevent criminal activities, utilizing advanced visual analysis techniques. Concurrently, it emphasizes the role of machine learning in streamlining case management processes, thereby providing precise recommendations and enhancing overall efficiency within the criminal justice system.