Families' Vision of Generative AI Agents for Household Safety Against Digital and Physical Threats

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 cyberbullying and digital harassment. Families emphasized the need for agent-specific privacy boundaries, recognized generational differences in trust toward AI agents, and stressed the importance of maintaining open family communication alongside the assistance of AI agents. Based on these findings, we propose a multi-agent system design featuring four privacy-preserving principles: memory segregation, conversational consent, selective data sharing, and progressive memory management to help balance safety, privacy, and autonomy within family contexts.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-10-16
DOI
https://doi.org/10.1145/3757598
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

Families' Vision of Generative AI Agents for Household Safety Against Digital and Physical Threats

Lanjing Liu, Yaxing Yao, Zikai Alex Wen
Proceedings of the ACM on Human-Computer Interaction
Ethics and Social Impacts of AI
article

Families' Vision of Generative AI Agents for Household Safety Against Digital and Physical Threats

Lanjing Liu, Yaxing Yao, Zikai Alex Wen
article en

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 cyberbullying and digital harassment. Families emphasized the need for agent-specific privacy boundaries, recognized generational differences in trust toward AI agents, and stressed the importance of maintaining open family communication alongside the assistance of AI agents. Based on these findings, we propose a multi-agent system design featuring four privacy-preserving principles: memory segregation, conversational consent, selective data sharing, and progressive memory management to help balance safety, privacy, and autonomy within family contexts.

Proceedings of the ACM on Human-Computer InteractionVol. 9(7)
Johns Hopkins University (US), University of Washington Tacoma (US)
Openalex Percentile: Top 71%
Ethics and Social Impacts of AI
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Families' Vision of Generative AI Agents for Household Safety Against Digital and Physical Threats — Lanjing Liu, Yaxing Yao, et al. · Proceedings of the ACM on Human-Computer Interaction (2025) | TGRS Research Map | TGRS