Unpacking Youth Privacy Management in AI Systems: A Privacy Calculus Model Analysis

被引:0
作者
Shouli, Austin [1 ]
Barthwal, Ankur [1 ]
Campbell, Molly [1 ]
Shrestha, Ajay Kumar [1 ]
机构
[1] Vancouver Isl Univ, Dept Comp Sci, Nanaimo, BC V9R 5S5, Canada
来源
IEEE ACCESS | 2025年 / 13卷
关键词
Privacy; Artificial intelligence; Phase change materials; Data privacy; Ethics; Social networking (online); Calculus; Digital intelligence; Decision making; Medical services; Data ownership; education; ethical artificial intelligence; parental data sharing; privacy calculus theory; transparency; trust; user control; youth;
D O I
10.1109/ACCESS.2025.3585635
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The increasing use of Artificial Intelligence (AI) in daily life has introduced substantial issues in protecting user privacy, particularly for young digital citizens. This study examines the complex dynamics of privacy management in AI systems utilizing the Privacy Calculus Model (PCM), with 482 participants: 176 young digital citizens (ages 16-19), 146 parents and educators, and 160 AI specialists. The research used a mixed methods approach to analyze key characteristics, including data ownership, user control, parental data sharing attitude, transparency, trust, perceived risks, benefits, and education. The results underscore the necessity of promoting digital literacy, establishing trust through transparent practices, and implementing collaborative approaches for privacy governance. The study emphasizes the significance of customized educational activities and regulatory frameworks that enable users to manage the trade-offs between the advantages and risks of data sharing by including varied views. This research enhances ethical AI development and advocates equal privacy safeguards for children and young adults.
引用
收藏
页码:115780 / 115803
页数:24
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