Families' Vision of Generative AI Agents for Household Safety Against Digital and Physical Threats
Zikai Wen, Lanjing Liu, Yaxing Yao

TL;DR
This study explores how families envision using multiple specialized generative AI agents to enhance household safety, emphasizing privacy, trust, and communication in integrating AI into daily family life.
Contribution
It introduces a family-centered multi-agent system design with privacy principles, based on qualitative insights into family safety needs and AI role preferences.
Findings
Families prefer multiple AI agents with specific roles.
Privacy boundaries and trust vary across generations.
Open communication remains vital alongside AI support.
Abstract
As families face increasingly complex safety challenges in digital and physical environments, generative AI (GenAI) presents new opportunities to support household safety through multiple specialized AI agents. Through a two-phase qualitative study consisting of individual interviews and collaborative sessions with 13 parent-child dyads, we explored families' conceptualizations of GenAI and their envisioned use of AI agents in daily family life. Our findings reveal that families preferred to distribute safety-related support across multiple AI agents, each embodying a familiar caregiving role: a household manager coordinating routine tasks and mitigating risks such as digital fraud and home accidents; a private tutor providing personalized educational support, including safety education; and a family therapist offering emotional support to address sensitive safety issues such as…
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