Culturally Grounded Personas in Large Language Models: Characterization and Alignment with Socio-Psychological Value Frameworks
arXiv:2601.22396v2 Announce Type: replace-cross Abstract: Despite the growing utility of Large Language Models (LLMs) for simulating human behavior, the extent to which these synthetic personas accurately reflect world and moral value systems across different cultural conditionings remains uncertain. This paper investigates the alignment of synthetic, culturally-grounded personas with established frameworks, specifically the World Values Survey (WVS), the Inglehart-Welzel Cultural Map, and Moral Foundations Theory. We conceptualize and produce LLM-generated personas based on a set of interpret
The rapid advancement and deployment of LLMs necessitate a deeper understanding of their underlying cultural and moral alignment as their integration into society accelerates.
Understanding the cultural grounding of LLM personas is critical for preventing misrepresentation, bias, and unintended societal consequences that could undermine trust and adoption.
This research provides a framework for characterising and aligning LLM personas with human value systems, suggesting a new dimension for responsible AI development.
- · AI developers focused on ethical AI
- · Policymakers and regulators
- · Social scientists
- · Developers ignoring cultural alignment
- · Platforms deploying unaligned LLMs
Increased focus on culturally nuanced persona development in LLMs.
Development of new metrics and benchmarks for evaluating LLM cultural alignment and moral reasoning.
Integration of cultural alignment scores as a standard feature in LLM evaluations, influencing market adoption and regulatory compliance.
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Read at arXiv cs.AI