arXiv:2606.14626v1 Announce Type: new Abstract: The global use of artificial intelligence has increased interest in assessing the ability to generate culturally localized content, including stories. Cultural localization in stories often occurs through either templated localization -- the use of cultural markers (e.g., names, locations) in a generic narrative -- or holistic localization -- the variation of plots, values, and themes, in addition to cultural markers. We propose a method to measure the degree to which content was generated through templated localization. Specifically, we identify
The increasing global deployment and integration of AI across diverse cultures necessitates methods to evaluate its cultural nuance and bias.
Understanding cultural localization in AI-generated content is crucial for ethical AI development, market adoption, and preventing unintended cultural homogenization or misrepresentation.
This research provides a framework for measuring 'templated localization' in AI-generated narratives, enabling more sophisticated analysis beyond simple cultural markers.
- · AI developers focused on global markets
- · Cultural institutions and researchers
- · Ethical AI frameworks and auditors
- · AI models lacking cultural sensitivity
- · Content producers using generic AI for diverse audiences
AI-generated content will become more culturally relevant and less prone to superficial localizations.
This improved cultural nuance could accelerate AI adoption in sensitive sectors like education and media, especially in non-Western markets.
The ability to accurately characterize cultural localization may influence future regulatory frameworks for AI content generation, pushing towards more holistic cultural integration.
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Read at arXiv cs.CL