Abstract
With the development of big data technology, the privacy concerns of face recognition have become the most critical social issue in the era of information sharing. Based on the perceived ease of use, perceived usefulness, social cognition, and cross-cultural aspects, this study analyses the privacy of face recognition and influencing factors. The study collected 518 questionnaires through the Internet, SPSS 25.0 was used to analyze the questionnaire data as well as evaluate the reliability of the data, and Cronbach’s alpha (α coefficient) was used to measure the data in this study. Our findings demonstrate that when users perceive the risk of their private information being disclosed through face recognition, they have greater privacy concerns. However, most users will still choose to provide personal information in exchange for the services and applications they need. Trust in technology and platforms can reduce users’ intention to put up guards against them. Users believe that face recognition platforms can create secure conditions for the use of face recognition technology, thus exhibiting a higher tendency to use such technology. Although perceived ease of use has no significant positive impact on the actual use of face recognition due to other external factors, such as accuracy and technology maturity, perceived usefulness still has a significant positive impact on the actual use of face recognition. These results enrich the literature on the application behavior of face recognition and play an important role in making better use of face recognition by social individuals, which not only facilitates their daily life but also does not disclose personal privacy information.
Highlights
Face recognition is a biometric recognition technology that uses pattern matching to recognize individual identities based on facial feature data
Nowadays, relying on ubiquitous mobile camera devices, face recognition technology has been widely used in various fields, including face attendance, face payment, smart campus, access control system, and security system, which demonstrate the advances in the face recognition service level in the intelligent hardware system
In this study, taking the users of face recognition as the research objects, the technology acceptance model (TAM) was integrated, and variables such as privacy concerns, perceived risk, and trust were added to the model to developing face recognition, enterprises must pay attention to technical ethics, as well as privacy, to ensure personal privacy and protect against biological information leakage
Summary
Face recognition is a biometric recognition technology that uses pattern matching to recognize individual identities based on facial feature data. It demonstrates the impact of privacy concerns, perceived risk, trust, social cognition, and cross-cultural aspects on facial recognition This result enriches face recognition literature, and a hypothesis model based on perceived ease of use and perceived usefulness— the two determinants of user behavior—is created. In order to ensure the scientificity and credibility of the measurement variables, this study modified the mature scale in previous studies and combined it with the information concerns of current users on the use of face recognition and developed a questionnaire. Based on the test results, the overall Cronbach’s α coefficients of privacy concerns, perceived risk, perceived ease of use, perceived use, trust, and actual use are between 0.876 and 0.907, all of which are greater than 0.7 This indicates that the measurement of each latent variable shows excellent internal consistency and that the questionnaire is reliable as a whole.
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