Cross-linguistic disagreement as a conflict of semantic alignment norms in multilingual AI~Linguistic Diversity as a Problem for Philosophy, Cognitive Science, and AI~

L inguistic divergence can sometimes lead to cross-linguistic disagreements --disagreements purely due to semantic differences about a relevant concept. This paper identifies such disagreements as conflicts between two fundamental alignment norms in multilingual LLMs --cross -linguistic consistency (CL -consistency), which seeks universal concepts across languages, and consist ency with folk judgments (Folk - consistency), which respects language-specific semantic norms. Through examining responses of conversational multilingual AIs in English and Japanese with the cases used in philosophy (cases of knowledge -how attributions), this study demonstrates that even state-of-the -art LLMs provide divergent and internally inconsistent responses. Such findings reveal a novel qualitative limitation in crosslingual knowledge transfer, or conceptual crosslingual knowledge barriers, challenging the assumption that universal representations and cross-linguistic transfer capabilities are inherently desirable. M oreover, they reveal conflicts of alignment policies of their developers, highlight ing critical normative questions for LLM researchers and developers. The implications extend beyond technical alignment challenges, raising normative, moral -political, and metaphysical questions about the ideals underlying AI development --questions that are shared with philosophers and cognitive scientists but for which no one yet has definitive answers, invit ing a multidisciplinary approach to balance the practical benefits of cross - linguistic consistency and respect for linguistic diversity .