Can Artificial Intelligence be Socratic?

Abstract

This essay introduces the concept of Socratic Intelligence (SI) and proposes five premises: (1) artificial and human agents learn through observation, interaction, and reflective examination of those interactions; (2) what is learned depends on metacognition and reinforcement; (3) SI comprises five interlocking dimensions: epistemic curiosity, critical self-awareness, assumption analysis, dialogical competence, and intellectual humility; (4) Generative SI, embedded in Intelligent Tutoring Systems (ITS) or Large Language Models (LLMs), can scaffold human learning; and (5) Generative SI can apply the Socratic method recursively to a system’s own computational processes as a form of internal epistemic self-regulation. We situate SI within several philosophical traditions: Plato’s elenchus and docta ignorantia, Aristotle’s phronesis, virtue epistemology on intellectual humility, Dreyfus’s critique of cognitivism, and recent epistemology of LLMs. We argue that SI construct gives the philosophy of AI a normative vocabulary that interfaces classical philosophy with current machine-learning practice.