Understanding Parents’ Desires in Moderating Children’s Interactions with GenAI Chatbots through LLM-Generated Probes

要旨

This paper studies how parents want to moderate children’s interactions with Generative AI Chatbots, with the goal of informing the design of future GenAI parental control tools. We first used an LLM to generate synthetic Child--GenAI Chatbot interaction scenarios and worked with four parents to validate their realism. From this dataset, we carefully selected 12 diverse examples that evoked varying levels of concern and were rated the most realistic. Each example included a prompt and GenAI Chatbot response. We presented these to parents (N=24) and asked whether they found them concerning, why, and how they would prefer to modify the responses and be informed. Our findings reveal three key insights: (1) parents express concern about interactions that current GenAI Chatbot parental controls neglect; (2) parents want fine-grained transparency and moderation at the conversation level; and (3) parents need personalized controls that adapt to their desired strategies and children's ages.

著者
John Driscoll
University of California San Diego, La Jolla, California, United States
Yulin Chen
University of California San Diego, La Jolla, California, United States
Viki Shi
University of California San Diego, La Jolla, California, United States
Izak Vucharatavintara
San Diego State University, San Diego, California, United States
Yaxing Yao
Johns Hopkins University , Baltimore, Maryland, United States
Haojian Jin
University of California San Diego, La Jolla, California, United States

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: AI in Family, Dating and Private Life

P1 - Room 117
6 件の発表
2026-04-13 20:15:00
2026-04-13 21:45:00