{
  "id": 3410,
  "url": "https://arxiv.org/abs/2606.00369v1",
  "title": "Quantifying the Salience of Geo-Cultural Values for Pluralistic Safety Alignment",
  "summary": "Safe global deployment of AI models requires alignment with human values that vary across cultures. Yet rater pools in safety evaluation datasets remain largely geographically homogeneous, failing to capture geo-cultural differences. Further, it remains unclear whether such differences persist after controlling for demographics such as age, gender, and ethnicity. Through a meta-analysis of safety datasets, we find that most do not report geo-cultural information, and those that do lack a unified",
  "authors": "Arkadiy Saakyan, Charvi Rastogi, Lora Aroyo",
  "category": "research",
  "topics": "safety-alignment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-29T21:21:39.000Z",
  "fetched_at": "2026-07-14T16:30:14.369Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/3410",
  "original_url": "https://arxiv.org/abs/2606.00369v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}