ETHICS-2025 Plenary 1: When Innovation Meets Injustice: Navigating the Ethical Frontiers of Face Recognition Technology

Automated face recognition (AFR) technology stands at the crossroads of innovation and injustice. While it offers extraordinary capabilities for security and investigative work, its deployment raises urgent ethical questions about privacy, fairness, and accountability. Real-world cases—such as wrongful arrests resulting from misidentification—reveal the high stakes when technological decisions intersect with human judgment. This talk explores the ethical frontiers of AFR, drawing on current research, practical experience, and emerging threats like generative and adversarial AI. Attendees will better understand where “biases” truly originate, how vulnerabilities can be exploited, and what principles should guide the responsible development and use of AFR systems. Balancing the promise of innovation against the risk of injustice, we will chart a path toward ethical governance, transparency, and accountability in face recognition technologies.

Publication Details

Published
2025-06-06
DOI
https://doi.org/10.1109/ethics65148.2025.11098412
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

ETHICS-2025 Plenary 1: When Innovation Meets Injustice: Navigating the Ethical Frontiers of Face Recognition Technology

Ethics and Social Impacts of AI
article

ETHICS-2025 Plenary 1: When Innovation Meets Injustice: Navigating the Ethical Frontiers of Face Recognition Technology

article en

Abstract

Automated face recognition (AFR) technology stands at the crossroads of innovation and injustice. While it offers extraordinary capabilities for security and investigative work, its deployment raises urgent ethical questions about privacy, fairness, and accountability. Real-world cases—such as wrongful arrests resulting from misidentification—reveal the high stakes when technological decisions intersect with human judgment. This talk explores the ethical frontiers of AFR, drawing on current research, practical experience, and emerging threats like generative and adversarial AI. Attendees will better understand where “biases” truly originate, how vulnerabilities can be exploited, and what principles should guide the responsible development and use of AFR systems. Balancing the promise of innovation against the risk of injustice, we will chart a path toward ethical governance, transparency, and accountability in face recognition technologies.

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