As generative artificial intelligence (AI) increasingly provides knowledge and outperforms students on conventional assessments, education faces a fundamental challenge. This paper argues that the appropriate response is to rethink what we mean by intelligence and reposition dialogic intelligence as a central educational aim. Dominant conceptions of intelligence as an individual trait, measured through rapid problem-solving, are historically tied to print literacy’s cognitive affordances and obscure the relational conditions under which meaning emerges. The rise of large language models creates an opportunity to recover an older conception of intelligence as the capacity to sustain responsive relationships through which truth and value emerge. Dialogic intelligence arises in the relational space between people, between people and nature, and between people and technology. It involves dwelling in open inquiry, allowing new insights to emerge, and critically testing and refining them. While AI can support knowledge generation and verification, dialogic intelligence depends on uniquely human capacities for care, ethical responsibility, and sustained attention. The paper outlines pedagogical approaches and assessment frameworks foregrounding relational processes rather than individual performance alone.
Rupert Wegerif (Tue,) studied this question.