SOURCE-LINKED INTELLIGENCE

Alignment by Stereotyping: How LLMs Sacrifice Individual Distinctiveness for Cultural Adaptation

arXiv · AI, language, vision and robotics · article · Sep 5, 2026 · UTC

Large language models are increasingly deployed for personalized interaction, and demographic conditioning via user profiles is a widely adopted strategy for cultural adaptation. We ask whether this approach genuinely serves individual users or achieves accuracy by erasing individual distinctiveness. Studying seven models including frontier GPT-5.1 on the World Values Survey, we find that demographic profiles improve value alignment accuracy for most models, but at a systematic cost to individuality. That is, models pull responses toward demographic group centroids rather than preserving indiv

Read original source ↗ Open in workspace

recordType

paper

region

Global