Facial recognition technology refers to extensions of facial mapping or profiling. According to Mann and Smith (2017), the technology encompasses the automated comparison, digitization, and extraction of the geometric and spatial distribution of facial features. The utilization of facial recognition technology has been debated for years and remains a contentious topic. However, a wide range of organizations in automobiles, travel, retail, insurance, and energy companies already use the technology. The facial recognition technology worries individuals about safety, with organizations such as Microsoft and Civil Liberties Union, among others expressing concerns about consumer privacy, potential abuse, and regulations. This argumentative essay opposes the technology’s use to decrease the loss of inventory in retail businesses.
Facial recognition technology has a wide range of applications in retail businesses, especially to control loss of inventories. The enterprises use facial recognition to prevent organized retail crime and violence, provide tailored assistance in stores, and send meaningful text messages. The major advantages of facial recognition technology are security and privacy (Mann & Smith, 2017). The technology quickly captures the images of trespassers and alerts promptly, is highly accurate, and fully automated. However, the drawbacks of the technology outweigh the advantages.
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The major concerns of facial recognition technology in retail businesses are the threat to individuals' privacy. The concerns relate to the manner of storing, retaining, obtaining, and sharing of biometric data between agencies. Biometric technology invades privacy because of its potential to identify individuals and can be applied to connect or link information across datasets (Mann & Smith, 2017). The technology presents additional risks in privacy as they can be used to track or locate individuals through various implemented CCTV surveillance systems.
Facial recognition technology lacks efficiency in identifying women and individuals of color because its algorithms data sets are robust for men and whites. The technology risks ramifications for misidentifying people until the ramification of the issue. The technology's camera angle also requires resolutions because it strongly influences face processing, and obstructions such as hats or facial hair hinder efficiency. Storage of sensitive personal data, as well as the challenges associated with it, is another drawback of facial recognition technology. Databases containing facial scans used by defense firms, police forces, and banks encounter bleaching risks on a regular basis.
In conclusion, this essay opposes the application of facial recognition technology in retail businesses because the drawbacks outweigh the benefits. The only way to benefit from the technology's positive aspects is to address significant challenges to individuals' privacy and civil liberties. Retail organizations must consider the adequacy of existing oversight mechanisms and privacy protections before implementing the technology.
References
Mann, M., & Smith, M. (2017). Automated facial recognition technology: Recent developments and approaches to oversight. UNSWLJ , 40 , 121.
