Book Title: Computational Criminology: AI Applications in Forensic Science and Criminal Justice
Editors: Dr. Xavier Louis, Dr. Surbhi Girdhar, Ms. Aswathi Chandran Nair, Mr. Ravi Kumar, and Ms. Nandini Katare
Chapter: 16
DOI: https://doi.org/10.59646/704/16
Author: Rakesh Nair
Abstract
Facial recognition technology (FRT) has emerged as one of the most consequential and most contested AI applications in contemporary law enforcement. Drawing upon deep convolutional neural networks trained on hundreds of millions of images, modern FRT systems can match faces across large databases with extraordinary speed and, under optimal conditions, high accuracy. Yet the technology’s deployment in policing contexts has generated profound controversies regarding algorithmic bias, disproportionate misidentification of individuals from racially marginalized communities, Fourth Amendment implications, and the threat of mass surveillance in democratic societies. This chapter provides a technically grounded overview of how FRT systems function from face detection through feature embedding to gallery matching and then critically examines the empirical evidence on accuracy disparities across demographic groups, surveys landmark legal challenges and regulatory responses, and evaluates frameworks for the ethical governance of FRT in law enforcement contexts. The chapter argues that technically competent use of FRT in policing demands not only accurate algorithms but robust procedural safeguards, transparency obligations, and meaningful democratic accountability.