AI's Blind Spot: Language Worldviews to the Rescue

This paper examines the intersection between artificial intelligence (AI), linguistic diversity, and cultural cognition through the lens of linguistic relativity. It argues that language is not merely a communication tool but a fundamental framework shaping human cognitive perception, memory, and social behavior. Using a contrastive analysis of word formation in English and Ukrainian, the study illustrates how different linguistic structures reflect distinct worldviews. It further examines how AI development, centered mostly around English and other dominant languages, risks reinforcing cultural and linguistic homogenization. Experimental testing demonstrates how AI-generated outputs fail to capture culturally embedded emotional and metaphorical distinctions, particularly in underrepresented languages. The paper also highlights that the loss of a language entails the loss of a unique worldview and a diminished capacity for cognitive comparison. Linguistic and cultural diversity enable self-reflection, enhance communication, reduce bias, and strengthen social justice and identity. In response, the paper proposes the creation of an Atlas of Language Worldviews - an AI-enhanced platform to systematically document, preserve, and map cultural perspectives across languages as well as to train AI. The Atlas would anchor a “worldview” with measurable components and integrate linguistic, historical, and cultural data, which would offer a critical tool for supporting cultural self-reflection of language groups, intercultural understanding, preserving endangered cultures, and training the ethical development of culturally sensitive AI systems. The paper provides the roadmap for Atlas creation.