Principles of Safe AI Companions for Youth: Parent and Expert Perspectives
Yaman Yu, Mohi, Aishi Debroy, Xin Cao, Karen Rudolph, Yang Wang
Abstract
AI companions are increasingly popular among teenagers, yet current platforms lack safeguards to address developmental risks and harmful normalization. Despite growing concerns, little is known about how parents and developmental psychology experts assess these interactions or what protections they consider necessary. We conducted 26 semi-structured interviews with parents and experts, who reviewed real-world youth–AI companion conversation snippets. We found that stakeholders assessed risks contextually, attending to factors such as youth maturity, AI character age, and how AI characters modeled values and norms. We also identified distinct logics of assessment: parents flagged single events, such as a mention of suicide or flirtation, as high risk, whereas experts looked for patterns over time, such as repeated references to self-harm or sustained dependence. Both groups proposed interventions, with parents favoring broader oversight and experts preferring cautious, crisis-only escalation paired with youth-facing safeguards. These findings provide directions for embedding safety into AI companion design.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Cited by top-tier papers2
- Understanding Teen Overreliance on AI Companion Chatbots Through Self-Reported Reddit NarrativesMohammad (Matt) Namvarpour, Brandon Brofsky, Jessica Y. Medina, Mamtaj Akter et al.CHI 2026 · 19 citations
- Do Teachers Dream of GenAI Widening Educational (In)equality? Envisioning the Future of K-12 GenAI Education from Global Teachers' PerspectivesRuiwei Xiao, Qing Xiao, Xinying Hou, Phenyo Phemelo Moletsane et al.CHI 2026 · 4 citations
Builds on14
- The Dark Side of AI Companionship: A Taxonomy of Harmful Algorithmic Behaviors in Human-AI RelationshipsRenwen Zhang, Han Li, Han Meng, Jinyuan Zhan et al.CHI 2025 · 122 citations
- From Parental Control to Joint Family Oversight: Can Parents and Teens Manage Mobile Online Safety and Privacy as Equals?Mamtaj Akter, Amy J. Godfrey, Jess Kropczynski, Heather Richter Lipford et al.CSCW 2022 · 64 citations
- Protection or Punishment? Relating the Design Space of Parental Control Apps and Perceptions about Them to Support Parenting for Online SafetyGe Wang, Jun Zhao, Max Van Kleek, Nigel ShadboltCSCW 2021 · 63 citations
- The Role of AI in Peer Support for Young People: A Study of Preferences for Human- and AI-Generated ResponsesJordyn Young, Laala M. Jawara, Diep N. Nguyen, Brian Daly et al.CHI 2024 · 58 citations
- Child Safety in the Smart Home: Parents' Perceptions, Needs, and Mitigation StrategiesKaiwen Sun, Yixin Zou, Jenny S. Radesky, Christopher Brooks et al.CSCW 2021 · 51 citations
Related papers
- Exploring Parent-Child Perceptions on Safety in Generative AI: Concerns, Mitigation Strategies, and Design ImplicationsYaman Yu, Tanusree Sharma, Melinda Hu, Justin Wang et al.S&P 2025
- "Pikachu would electrocute people who are misbehaving": Expert, Guardian and Child Perspectives on Automated Embodied Moderators for Safeguarding Children in Social Virtual RealityCristina Fiani, Robin Bretin, Shaun Alexander Macdonald, Mohamed Khamis et al.CHI 2024 · 18 citations
- Who Gets to Define Safety? A Systematic Review of How Generative AI Research Addresses Youth Online SafetyOzioma Collins Oguine, Adriana Alvarado Garcia, Michael J. Muller, Karla Badillo-UrquiolaCHI 2026 · 2 citations
- Understanding Parents' Desires in Moderating Children's Interactions with GenAI Chatbots through LLM-Generated ProbesJohn Driscoll, Yulin Chen, Viki Shi, Izak Vucharatavintara et al.CHI 2026 · 2 citations
- YouthSafe: A Youth-Centric Safety Benchmark and Safeguard Model for Large Language ModelsYaman Yu, Yiren Liu, Yuqi Zhang, Yun Huang et al.CCS 2025 · 1 citation
