From Gunpowder to Code: Reimagining Firearm Evidence Through Artificial Intelligence

The incorporation of “Artificial Intelligence (AI) and Machine Learning (ML)” into forensic science represents a new era towards the processing of firearm evidence. Previously, firearm forensics was predominantly based on expert opinion, visual comparisons, and other subjective methods that were further marred by questions of reliability and admissibility. AI and ML provide a data-driven and objective methods that can be used to speed up and to increase the accuracy and consistency of ballistic and tool-marks analyses. This paper explores the scientific basis, practical applications and legal frameworks within which AI and ML technologies are being increasingly-weaved throughout firearm evidence analysis. The main focus is to determine the ways in which these technologies are changing the course of forensic investigations, court decisions, and ways that traditional standards of evidence are being challenged. Technologically as it reviews, in a multi-disciplinary manner both, landmark judicial decisions, and current ethical debates. The complementary examination of Indian and international legal context enables a deeper understanding. The results highlight potential improvements in forensic accuracy from the use of AI and ML while discussing issues of explain ability, bias, and the legal admissibility of such tools. While they are cautiously optimistic, courts require more clearness and rigorous validation of ai assisted exhibits. The paper ends with recommendations for necessary technology policy—regulatory standards that legally enforce commitments to equity, an interdisciplinary approach between the social and engineering sciences to study what happens with new technologies, and ethical theory development and application to guide the use of technologies to elevate policing and justice rather than degrade.