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LLM Safety for Children

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arxiv 2502.12552 v1 pith:R3A3GC2O submitted 2025-02-18 cs.CY cs.AI

classification cs.CYcs.AI
keywords childrensafetychildllmsmodelsuserapplicationsliterature
verification ladder T0 review T1 audit T2 compute T3 formal
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This paper analyzes the safety of Large Language Models (LLMs) in interactions with children below age of 18 years. Despite the transformative applications of LLMs in various aspects of children's lives such as education and therapy, there remains a significant gap in understanding and mitigating potential content harms specific to this demographic. The study acknowledges the diverse nature of children often overlooked by standard safety evaluations and proposes a comprehensive approach to evaluating LLM safety specifically for children. We list down potential risks that children may encounter when using LLM powered applications. Additionally we develop Child User Models that reflect the varied personalities and interests of children informed by literature in child care and psychology. These user models aim to bridge the existing gap in child safety literature across various fields. We utilize Child User Models to evaluate the safety of six state of the art LLMs. Our observations reveal significant safety gaps in LLMs particularly in categories harmful to children but not adults

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Cited by 1 Pith paper

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  1. FORTRESS: Frontier Risk Evaluation for National Security and Public Safety

    cs.CY 2025-06 conditional novelty 6.0 of 10

    A new benchmark with instance-specific rubrics measures frontier LLMs' willingness to assist with national security and public safety threats, alongside a paired over-refusal test.

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