Investigation of the Privacy Concerns in AI Systems for Young Digital Citizens: A Comparative Stakeholder Analysis
Molly Campbell, Ankur Barthwal, Sandhya Joshi, Austin Shouli, Ajay, Kumar Shrestha

TL;DR
This study explores privacy concerns among young digital citizens by analyzing stakeholder perspectives, revealing key factors influencing trust and highlighting the importance of education, transparency, and user-centric privacy controls.
Contribution
It provides a comparative stakeholder analysis of privacy concerns in AI systems for youth, introducing empirical data and insights for ethical AI design and governance.
Findings
Education influences data ownership and risk perception
Data control impacts transparency and trust
Minimal influence of perceived risks on parental data sharing
Abstract
The integration of Artificial Intelligence (AI) systems into technologies used by young digital citizens raises significant privacy concerns. This study investigates these concerns through a comparative analysis of stakeholder perspectives. A total of 252 participants were surveyed, with the analysis focusing on 110 valid responses from parents/educators and 100 from AI professionals after data cleaning. Quantitative methods, including descriptive statistics and Partial Least Squares Structural Equation Modeling, examined five validated constructs: Data Ownership and Control, Parental Data Sharing, Perceived Risks and Benefits, Transparency and Trust, and Education and Awareness. Results showed Education and Awareness significantly influenced data ownership and risk assessment, while Data Ownership and Control strongly impacted Transparency and Trust. Transparency and Trust, along with…
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Taxonomy
TopicsEthics and Social Impacts of AI
