Liu Tao, Yang Bijiao, Geng Yanan, Du Sumin
Department of Sociology, Hangzhou Dianzi University, Hangzhou, China.
Front Psychol. 2021 Dec 24;12:809736. doi: 10.3389/fpsyg.2021.809736. eCollection 2021.
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.
随着大数据技术的发展,人脸识别的隐私问题已成为信息共享时代最关键的社会问题。基于感知易用性、感知有用性、社会认知和跨文化等方面,本研究分析了人脸识别的隐私性及其影响因素。该研究通过互联网收集了518份问卷,使用SPSS 25.0对问卷数据进行分析并评估数据的可靠性,本研究采用Cronbach's alpha(α系数)来衡量数据。我们的研究结果表明,当用户感知到通过人脸识别其私人信息有被泄露的风险时,他们会有更大的隐私担忧。然而,大多数用户仍会选择提供个人信息以换取他们所需的服务和应用。对技术和平台的信任可以降低用户对其设防的意愿。用户认为人脸识别平台可以为人脸识别技术的使用创造安全条件,从而表现出更高的使用该技术的倾向。尽管由于准确性和技术成熟度等其他外部因素,感知易用性对人脸识别的实际使用没有显著的积极影响,但感知有用性对人脸识别的实际使用仍有显著的积极影响。这些结果丰富了人脸识别应用行为的文献,并在社会个体更好地使用人脸识别方面发挥重要作用,这不仅方便了他们的日常生活,而且不会泄露个人隐私信息。