Abstract

Recently, the rapid development of facial recognition technology, which is an important field of artificial intelligence, has attracted more and more attention worldwide due to the integration of big data and artificial intelligence technology. This technology has been widely applied in various fields and continues to develop with many advantages and convenience. However, the concerns and potential risks associated with the widespread use of facial recognition technology are also significant. Therefore, this study aims to comprehensively and critically review the development and risks of this technology, focusing on the current situation in China. It is intended to offer guidance and support for the ethical advancement of contemporary facial recognition technology as well as to promote responsible oversight and regulation. In this paper, first, the development process of facial recognition technology such as the technological origin and core technological innovation in the world and China is reviewed. Next, it also examines the application and convergence of big data and artificial intelligence algorithms in facial recognition technology. Furthermore, it analyzes the latest development of facial recognition technology in China, including the driving role of the government and companies and trends in major application fields. Simultaneously, this discourse delves into the extensive risks and challenges associated with facial recognition technology, such as privacy, data security, potential misuse, ethics, and legal regulations. To put it another way, the practical risks of facial recognition technology are focused on its specific applications in the fields of public safety, commerce, and social management, highlighting the resulting technical vulnerabilities, privacy threats, and abuse of social monitoring. Finally, this study summarizes the development status of facial recognition technology, points out the major problems and risks facing it once again, and presents appropriate countermeasures and policy recommendations.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call