Intersectional Sycophancy: How Perceived User Demographics Shape False Validation in Large Language Models

ArXi:2604.11609v1 Announce Type: new Large language models exhibit sycophantic tendencies--validating incorrect user beliefs to appear agreeable. We investigate whether this behavior varies systematically with perceived user graphics, testing whether combinations of race, age, gender, and expressed confidence level produce differential false validation rates.