TY - GEN
T1 - Youth-Centered GenAI Risks (YAIR)
T2 - 21st Symposium on Usable Privacy and Security, SOUPS 2025
AU - Yu, Yaman
AU - Liu, Yiren
AU - Zhang, Jacky
AU - Huang, Yun
AU - Wang, Yang
N1 - We would like to thank Margie Lachman and anonymous reviewers for their valuable feedback on this work. This work was in part supported by a MassAITC pilot award, and NSF grants 2229876 and 2055233. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of their employers or sponsors.
PY - 2025
Y1 - 2025
N2 - Generative AI is changing how youth engage with technology, yet the unique risks they face remain underexplored and are missing from existing safety frameworks. Without a focused taxonomy, important harms to youth may be overlooked. To fill this gap, we present the first Youth-Centered Risk Taxonomy for generative AI (YAIR), built from 344 youth–GAI chat logs, 30,305 Reddit discussions, and 153 AI incident reports. We identify six key risk categories and 84 specific risks organized along four interaction pathways. Our findings reveal unique risks for youth rooted in their developmental stage, e.g., Mental Wellbeing Risks, Behavioral and Social Developmental Risks, and new manifestations of Toxicity, Privacy, Bias/Discrimination and Misuse/Exploitation, which are not addressed in existing child online safety taxonomies and AI risk taxonomies. Grounded in real-world data, this taxonomy offers a clear framework to help AI practitioners, educators, parents, and policymakers better understand and address risks in youth–GenAI interactions.
AB - Generative AI is changing how youth engage with technology, yet the unique risks they face remain underexplored and are missing from existing safety frameworks. Without a focused taxonomy, important harms to youth may be overlooked. To fill this gap, we present the first Youth-Centered Risk Taxonomy for generative AI (YAIR), built from 344 youth–GAI chat logs, 30,305 Reddit discussions, and 153 AI incident reports. We identify six key risk categories and 84 specific risks organized along four interaction pathways. Our findings reveal unique risks for youth rooted in their developmental stage, e.g., Mental Wellbeing Risks, Behavioral and Social Developmental Risks, and new manifestations of Toxicity, Privacy, Bias/Discrimination and Misuse/Exploitation, which are not addressed in existing child online safety taxonomies and AI risk taxonomies. Grounded in real-world data, this taxonomy offers a clear framework to help AI practitioners, educators, parents, and policymakers better understand and address risks in youth–GenAI interactions.
UR - https://www.scopus.com/pages/publications/105021085399
UR - https://www.scopus.com/pages/publications/105021085399#tab=citedBy
M3 - Conference contribution
AN - SCOPUS:105021085399
T3 - Proceedings of the 21st Symposium on Usable Privacy and Security, SOUPS 2025
SP - 149
EP - 165
BT - Proceedings of the 21st Symposium on Usable Privacy and Security, SOUPS 2025
PB - USENIX Association
Y2 - 11 August 2025 through 12 August 2025
ER -