This chapter argues that intelligence diversitydiversity, rooted in Howard Gardner’sGardner theory of multiple intelligencesmultiple intelligences, provides the essential epistemological foundation for AI pluralismAI pluralism and educational transformation. Generative AI systems excel at the narrow linguistic and logical-mathematical tasks that have dominated traditional education. This chapter exposes the inadequacy of intelligence singularity paradigms that marginalize other valid forms of human knowing. Drawing on Dewey’sDewey pragmatismpragmatism, Haraway’sHaraway situated knowledgessituated knowledges, and Hegel’s dialectical method, the author demonstrates how recognizing multiple intelligences challenges the singular intelligence model structuring both educational assessment and AI development. The chapter examines how AI systems trained on data reflecting educational biases toward linguistic and logical reasoning perpetuate these narrow conceptions of intelligence. To counter this, the author proposes intelligence diversity as cognitive infrastructure for AI pluralism, arguing that cultivating multiple ways of knowing prepares students for meaningful human-AI collaboration. The chapter advocates for pedagogical approaches like debatedebate that engage diverse intelligences, moving beyond the fact-versus-opinion binary toward “epistemic contestationepistemic contestation“that embraces uncertainty and multiplicity. This transformation positions intelligence diversity not as accommodation for human limitation, but as recognition of cognitive abundance essential for democratic education and ethical AI development.