SOURCE-LINKED INTELLIGENCE
Toward Cultural Alignment: Human-Centered Evaluation of Multimodal AI Stories Across Five African Communities
In this paper, we examine how well AI-generated multimodal stories align with the lived practices, relationships, language, values, and visual expectations of the communities they represent. We conduct a community-grounded mixed-methods evaluation with 19 culture representatives across five African communities, combining quantitative annotations with qualitative focus group discussions. We find that cultural alignment depends not simply on recognizable cultural markers, but on how those markers fit social, linguistic, procedural, and visual context. From these evaluations, we develop a taxonom
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-29T11:45:39.000Z
First collected: 2026-09-21T07:51:58.603Z. This is not the publication date.