Online Archive of University of Virginia Scholarship
Mobile Facial Recognition and ICE’s Racialized Expansion of State Power4 views
Author
Steele, Ryan, School of Engineering and Applied Science, University of Virginia
Advisors
Earle, Joshua, EN-Engineering and Society, University of Virginia
Abstract
This paper examines how mobile facial recognition technologies used by U.S. Immigration and Customs Enforcement, specifically Clearview AI and Mobile Fortify, perpetuate historical patterns of racialized surveillance in the United States. While facial recognition technology is often framed as a neutral tool for public safety, I argue that its deployment within law enforcement contexts extends state power while disproportionately exposing Black and Brown communities to hyper-surveillance, wrongful identification, and diminished privacy. Through an analysis of the history of facial recognition, U.S. government surveillance practices, documented racial biases in facial recognition systems, and ICE’s current biometric technologies, this paper explores how algorithmic policing reproduces existing systemic inequalities under the premise of technological efficiency. Ultimately, this paper questions whether the use of mobile facial recognition in everyday civilian life can coexist with democratic freedoms, privacy, and individual autonomy.
Degree
BS (Bachelor of Science)
Language
English
Rights
All rights reserved by the author (no additional license for public reuse)
Steele, Ryan. Mobile Facial Recognition and ICE’s Racialized Expansion of State Power. University of Virginia, School of Engineering and Applied Science, BS (Bachelor of Science), 2026-05-10, https://doi.org/10.18130/y45e-dj10.