Quantifying the Salience of Geo-Cultural Values for Pluralistic Safety Alignment
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 methodology to jointly analyze geo-cultural and demographic correlates. Using the Inglehart-Welzel dimensions of cross-cultural variation, we demonstrate via multilevel modeling that cultural zone...
| Authors | Arkadiy Saakyan, Charvi Rastogi, Lora Aroyo |
|---|---|
| Primary category | cs.CY |
| Published | 29 May 2026 |
| Last updated at source | 29 May 2026 |
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