AI and Culture

This research area examines how AI systems, particularly recommender systems and language models, shape and interact with cultural content and experiences. This includes developing metrics like commonality to measure how recommendation systems promote shared cultural experiences across populations, moving beyond personalization to consider broader cultural citizenship and democratic values inspired by public service media principles. The research also addresses cultural competence in large language models, examining how these systems handle cultural norms and values in text generation tasks, and develops frameworks for evaluating art datasets to prevent cultural appropriation and representational harm.