Abstract

Automated face recognition has rapidly evolved, driven by deep learning advancements and widespread adoption in border security, transportation, authentication, and law enforcement. While independent evaluations by NIST and others have demonstrated significant improvements in accuracy, recent events highlight the critical risks of misconfigured or misapplied systems. Despite its potential, face recognition has now been linked to at least seven wrongful arrests, with the most recent case—acknowledged in January 2025—resulting in an individual being wrongfully incarcerated for 17 months.

This talk will examine key wrongful arrest cases, analyzing the specific technical and operational failures that led to these injustices. Issues such as poor image quality, improper system configurations, and overreliance on automated matches without human oversight have contributed to these errors. Additionally, broader concerns about bias, system transparency, and the legal implications of face recognition in law enforcement will be explored. By dissecting these cases, hopefully we can better understand how to mitigate risks and establish safeguards that ensure face recognition technology is used responsibly, minimizing the potential for harm while preserving its legitimate benefits.

About the Speaker

Michael C. King joined the Harris Institute for Assured Information at Florida Institute of Technology, Melbourne, FL, USA, as a Research Scientist in 2015 and holds a joint appointment as an Associate Professor in the Department of Computer Engineering and Sciences. Before joining academia, he served for more than ten years as a Scientific Research/Program Management Professional with the United States Intelligence Community. While in government, he created, directed, and managed research portfolios covering a broad range of topics related to biometrics and identity to include: advanced exploitation algorithm development, advanced sensors and acquisition systems, and computational imaging. He crafted and led the Intelligence Advanced Research Projects Activity's Biometric Exploitation Science and Technology Program to transition technology deliverables successfully to several Government organizations. His research interests include: machine learning, cybersecurity, and biometrics.