ChildSafeLLM (Child Safety Aligned Evaluation Prompts for Generative AIs) is a developmental benchmark comprising 200 total prompts carefully crafted and curated for two distinct age cohorts—ages 6-12 and ages 7-13. Drawing on evidence-based child-safety guidelines, school curricula, and authentic questions from children and caregivers, the prompts were sourced from reputable organizations across six continents to ensure broad cultural and linguistic representation. Available in .xlsx, ChildSafeLLM supports a wide range of natural-language processing tasks, including harmful-content detection, age-appropriateness classification, response-consistency analysis, safety-alignment fine-tuning, and developmental language modeling. Beyond its use for model training, the corpus offers a reproducible benchmark for evaluating ambiguity resolution, risk-category labeling, and multi-turn dialogue safety in child–AI interactions. By standardizing safety scenarios for younger users, ChildSafeLLM advances research into trustworthy AI design and helps practitioners assess how generative models accommodate children’s cognitive and emotional needs. (2025-06-10)
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Jun 14, 2025
Jiao, Junfeng; Kevin Chen; Afroogh, Saleh; Murali, Abhejay; Atkinson, David; Dhurandhar, Amit, 2025, "ChildSafeLLM: A Dataset of Child Safety Aligned Evaluation Prompts for Generative AIs", https://doi.org/10.7910/DVN/MRZGNB, Harvard Dataverse, V1
ChildSafeLLM (Child Safety Aligned Evaluation Prompts for Generative AIs) is a developmental benchmark comprising 200 total prompts carefully crafted and curated for two distinct age cohorts—ages 6-12 and ages 7-13. Drawing on evidence-based child-safety guidelines, school curricula, and authentic questions from children and caregivers, the prompts...
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