Mixed-methods research in Saudi Arabia reveals that GenAI use by youth creates culturally specific privacy and safety risks tied to family honor and shared accounts, requiring context-sensitive design.
Understanding generative ai risks for youth: A taxonomy based on empirical data
4 Pith papers cite this work, alongside 1 external citations. Polarity classification is still indexing.
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2026 4verdicts
UNVERDICTED 4representative citing papers
CAREBench is a new benchmark with 500 prompts in 12 risk categories that measures how often frontier LLMs fail to refuse or redirect child-safety risks, reporting failure rates between 2% and 58%.
Proposes an expert-guided and incident-grounded framework for child safety evaluation in generative AI and applies it in education to find that Llama Guard models struggle with unsafe prompts.
RiskNet releases a large-scale dataset of aligned and annotated AI risk incidents extracted from news via a structured processing pipeline, along with benchmark subsets and an online exploration platform.
citing papers explorer
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Culturally Aware GenAI Risks for Youth: Perspectives from Youth, Parents, and Teachers in a Non-Western Context
Mixed-methods research in Saudi Arabia reveals that GenAI use by youth creates culturally specific privacy and safety risks tied to family honor and shared accounts, requiring context-sensitive design.
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CAREBench: A Child-Safety Risk Benchmark for Language Models
CAREBench is a new benchmark with 500 prompts in 12 risk categories that measures how often frontier LLMs fail to refuse or redirect child-safety risks, reporting failure rates between 2% and 58%.
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Child Safety in Generative AI: An Expert-Guided and Incident-Grounded Evaluation Framework
Proposes an expert-guided and incident-grounded framework for child safety evaluation in generative AI and applies it in education to find that Llama Guard models struggle with unsafe prompts.
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RiskNet: A large-scale dataset of AI risk incidents from news with alignment and multi-dimensional annotations
RiskNet releases a large-scale dataset of aligned and annotated AI risk incidents extracted from news via a structured processing pipeline, along with benchmark subsets and an online exploration platform.