mlsanityData to 14 Oct 2026

Exploring Parent-Child Perceptions on Safety in Generative AI: Concerns, Mitigation Strategies, and Design Implications

arXiv 2406.10461 ↗First posted 15 Jun 2024cs.HCcited by 5

Not on the map. Why?

Abstract (arXiv)

The widespread use of Generative Artificial Intelligence (GAI) among teenagers has led to significant misuse and safety concerns. To identify risks and understand parental controls challenges, we conducted a content analysis on Reddit and interviewed 20 participants (seven teenagers and 13 parents). Our study reveals a significant gap in parental awareness of the extensive ways children use GAI, such as interacting with character-based chatbots for emotional support or engaging in virtual relationships. Parents and children report differing perceptions of risks associated with GAI. Parents primarily express concerns about data collection, misinformation, and exposure to inappropriate content. In contrast, teenagers are more concerned about becoming addicted to virtual relationships with GAI, the potential misuse of GAI to spread harmful content in social groups, and the invasion of privacy due to unauthorized use of their personal data in GAI applications. The absence of parental control features on GAI platforms forces parents to rely on system-built controls, manually check histories, share accounts, and engage in active mediation. Despite these efforts, parents struggle to grasp the full spectrum of GAI-related risks and to perform effective real-time monitoring, mediation, and education. We provide design recommendations to improve parent-child communication and enhance the safety of GAI use.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Jun 2024.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 3.

5 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026Beyond "I Can't Help With That": How Child Safety Experts Evaluate AI Chatbot Safety
  2. 2026Position: Preventing AI-Generated CSAM Necessitates New Approaches to AI Safety
  3. 2025SproutBench: A Benchmark for Safe and Ethical Large Language Models for Youth
  4. 2025LLMs and Childhood Safety: Identifying Risks and Proposing a Protection Framework for Safe Child-LLM Interaction
  5. 2025Understanding Gen Alpha Digital Language: Evaluation of LLM Safety Systems for Content Moderation
  6. 2025Safe-Child-LLM: A Developmental Benchmark for Evaluating LLM Safety in Child-LLM Interactions
  7. 2024Toward Safe Evolution of Artificial Intelligence (AI) based Conversational Agents to Support Adolescent Mental and Sexual Health Knowledge Discovery
  8. 2026Adolescents & Anthropomorphic AI: Rethinking Design for Wellbeing An Evidence-Informed Synthesis for Youth Wellbeing and Safety ↗