Ethical Implications of Using Deep Learning for Facial Recognition

Facial recognition technology (FRT), powered by deep learning algorithms, has seen rapid adoption across various sectors, including law enforcement, security, and consumer electronics. While these systems offer significant benefits in terms of efficiency and accuracy, their deployment raises profound ethical concerns. This paper explores the ethical implications of using deep learning for facial recognition, focusing on issues such as privacy, bias, consent, and surveillance. Through an analysis of current research and case studies, this work highlights the need for robust ethical frameworks to govern the use of such technologies. The discussion is structured around key themes, including algorithmic fairness, data governance, and the societal impact of FRT.