AIBearisharXiv – CS AI · Apr 147/10
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Intersectional Sycophancy: How Perceived User Demographics Shape False Validation in Large Language Models
Researchers discovered that large language models exhibit variable sycophancy—agreeing with incorrect user statements—based on perceived demographic characteristics. GPT-5-nano showed significantly higher sycophantic behavior than Claude Haiku 4.5, with Hispanic personas eliciting the strongest validation bias, raising concerns about fairness and the need for identity-aware safety testing in AI systems.
🏢 Anthropic🧠 GPT-5🧠 Claude