Face recognition refers to a method used to confirm or identify an individual’s identity using their face. The technology authenticates and identifies an individual based on sets of verifiable and recognizable data unique and specific to that individual. Facebook launched its DeepFace program in 2014, which can be used to identify two photographed faces belonging to one individual (Scherhag et al., 2019). While face recognition technology is gaining increasing application, especially by digital corporations, critics believe that storage and identity management have various ethical issues, including privacy and confidentiality. The use of face recognition technology is associated with various ethical concerns, such as lack of transparency and informed consent, racial discrimination, misinformation and bias, data breaches and mass surveillance.
Data privacy is undoubtedly the biggest ethical concern regarding the adoption and use of face recognition technology. Privacy is a key concern for people using the internet, especially social media. According to a study by Scherhag and colleagues, face recognition programs infringe on individuals’ inherent rights to remain under constant surveillance and have their images kept without their consent (Scherhag et al., 2019). For instance, in 2019, the European Commission banned the use of facial recognition technology in public spaces because of the ethical and privacy abuse associated with the technology (Scherhag et al., 2019). Privacy concerns associated with facial recognition revolve around unsafe data storage practices capable of exposing facial recognition information. Many corporations continue to host their facial recognition information on local servers with high-security vulnerabilities.
Facebook is among the digital corporations that announced to shut down its facial recognition software used to identify faces in videos and photographs. The corporation decided to delete over one billion facial recognition templates that the company has collected since its inception. There has been increasing concern about the ethics of facial recognition programs, and many questions have been raised over their accuracy, racial bias and privacy. Facebook has been facing severe criticism over the impact of this technology on users. The company was forced to bring down the program in 2019; however, users can turn the feature back on.
The decision made by Meta to shut down its facial recognition program was a right and ethical decision. Face recognition technology compromises privacy, making intrusive surveillance normal and often targeting marginalized people. The use of face recognition technology has gotten the company into various ethical issues. In 2019, Facebook was fined $6.5 billion by the US Federal Trade Commission to settle privacy complaints (Scherhag et al., 2019). The decision to shut down facial recognition software came after the corporation faced severe regulatory and legislative scrutiny over leaked user information.
The decision to bring down facial recognition technology positively impacts the company and its users. Not only will the company’s reputation grow strong, but also it will gain more users because the users will be assured of their privacy. Moreover, Facebook will not be involved in privacy complaints associated with face recognition technology. The company is now looking for a new form of identifying individuals with minimal privacy concerns—a narrower form of individual authentication.
The government and corporations should control facial recognition technology and be allowed to use it for narrower purposes. The technology is more effective and valuable when operated privately on an individual’s devices (Scherhag et al., 2019). Face recognition technology is not private, leading to severe security concerns. People have the right over their privacy, and their data can only be used with their consent. Therefore, the government must regulate the use of facial recognition technologies by organizations and businesses.
Reference
Scherhag, U., Rathgeb, C., Merkle, J., Breithaupt, R., & Busch, C. (2019). Face recognition systems under morphing attacks: A survey. IEEE Access, 7, 23012-23026.