The increasing volume and complexity of statements collected during investigations pose significant challenges for law enforcement and legal professionals. Traditional methods of statement analysis are time-consuming, prone to inconsistencies, and heavily reliant on human expertise. This paper proposes the AI-Enhanced Statement Synthesizer (AISS)—a generative AI-powered solution that leverages natural language processing (NLP), machine learning, and multimodal AI to automate the analysis, verification, and synthesis of investigative statements. AISS is designed to cross-check inconsistencies across multiple testimonies, extract critical insights, and generate coherent, context-aware narratives to assist investigators in making informed decisions. By integrating real-time AI-driven insights, AISS enhances the efficiency, accuracy, and reliability of statement analysis while reducing cognitive load on investigators. This research explores the technical architecture, potential applications, ethical considerations, and limitations of AISS, highlighting its transformative potential in modern policing and criminal investigations. The proposed solution represents a significant step toward AI-assisted forensic analysis, ensuring faster, data-driven decision-making in investigative workflows.
The paper examines the trajectory of crime, tracing its evolution from traditional forms to digital manifestations in cybercrime, and proposes "Hypercrime" as the latest frontier. Leveraging insights from Michael McGuire's "Hypercrime: The New Geometry of Harm," the study calls for a paradigm shift in law enforcement strategies to meet the challenges posed by AI-driven hypercrime. Emphasis is placed on understanding hypercrime's complexity, developing proactive policies, and embracing technological tools tomitigate risks associated with AI misuse.