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Understanding User Perception of Biometric Privacy in the Era of Generative AI

生物识别 计算机科学 互联网隐私 感知 生成语法 信息隐私 人机交互 计算机安全 人工智能 心理学 神经科学
作者
Srihari Srinivasan
标识
DOI:10.1109/c2i659362.2023.10430931
摘要

In the dynamic world of technology, the fusion of biometrics and artificial intelligence has ushered in an unprecedented era marked by convenience, security, and cutting-edge innovation. Biometrics, the science of using unique physical or behavioral attributes for identification and authentication, has seamlessly merged into daily routines. From unlocking smartphones with a fingerprint to clearing airport security with facial recognition, biometrics has transformed the way people interact with technology and the world. Simultaneously, Generative AI, powered by machine learning models, has unlocked new frontiers in generating remarkably realistic synthetic data, including human faces, voices, and fingerprints. This convergence of biometrics and Generative AI lies at the heart of a complex and rapidly evolving landscape, giving rise to profound questions concerning individual privacy and security. This study examines the correlation between demographic factors like age, gender, educational background, technological competence, and the regularity of employing biometric authentication, and their awareness about biometric technologies. Additionally, this research explores concerns regarding the potential misuse of biometric data and the notion that organizations should seek explicit consent before collecting such data. Lastly, it assesses the awareness of potential privacy risks and the belief that individuals should receive education regarding the utilization of their biometric data in AI systems. Descriptive research design has been used in this study. The first section of the questionnaire using Microsoft Forms covers the demographic factors, technological proficiency and frequency of using biometric authentication (e.g., fingerprint, facial recognition). The next section focuses on awareness and usage of biometric technologies, biometric privacy, trust, education, awareness of biometrics, generative AI and deepfakes using the Likert Scale. 53 samples were obtained through Simple Random Sampling from UAE residents. Then, testing of hypothesis using correlation analysis was done using SPSS. The results reveal that demographic variables do not exhibit a statistically significant relationship with privacy concerns. However, there is a statistically significant correlation exists between biometric authentication and awareness & knowledge parameters.

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