Has facial recognition technology been misused? A public perception model of facial recognition scenarios. (November 2021)

• Record Type: Journal Article
• Authors: Lai, Xiaojun; Patrick Rau, Pei-Luen
• Is Part Of: Computers in human behavior. Volume 124(2021)
• Publication Date: 2021-11
• Subjects: Facial recognition -- Misuse -- Public perception -- Trust -- Attitude; Interactive computer systems -- Periodicals; Man-machine systems -- Periodicals; 004.019
• DOI: 10.1016/j.chb.2021.106894
• Languages: English
• ISSNs: 0747-5632

Abstract

Abstract: Facial recognition technology (FRT) has been rapidly applied, and it has been accompanied by the potential for misuse due to technical limitations and legal irregularities. This study aimed to provide a conceptualizing model to investigate the public perception of FRT, and to identify FRT scenarios with the potential for misuse. We first reviewed potential FRT application examples and partitioned them into nine FRT scenarios based on the clues that the public may perceive: the data involved, the use/development purpose, the use location, and the use pattern. Then, we conducted an online survey ( N = 704) to investigate people's familiarity, trust, and attitude in each FRT scenario. Four public perception categories of FRT scenarios with a similar level of perception variables were identified (for example, category one including FRT scenarios with higher familiarity, higher trust, and more positive attitude). Besides, trust was revealed as the prominent factor of attitude in each scenario. Therefore, a public perception model of FRT scenarios including familiarity, trust, and attitude was built. FRT scenarios, including proactive, personalized services and passive business services, were perceived as most likely to be misused. Highlights: A public perception model of facial recognition technology scenarios was built. Nine FRT scenarios were constructed based on the clues the public may perceive. Trust was revealed as the prominent factor of attitude in each FRT scenario. Four public perception categories of FRT scenarios were identified. FRT scenarios perceived as unlikely/likely to be misused were identified.