The Interaction Order of AI-Mediated Education: Micro-Sociology and the Limits of Principle-Based Regulation

Abstract

Regulation of artificial intelligence in education is currently formulated as principles and institutional obligations. UNESCO’s guidance on generative AI calls for a human-centered approach; the EU AI Act classifies several educational uses of AI as high-risk, and Russian policy frames the digitalization of schooling through national strategies and state information systems. These instruments share a blind spot: they say little about the level at which AI and digital platforms actually enter education, namely the encounters, face-to-face and screen-mediated, between students, teachers, and machines. This review argues that this level, which Goffman called the interaction order, has its own regularities and that these regularities systematically refract policy. Drawing on Goffman’s dramaturgy and frame analysis, on ethnomethodology and conversation analysis, and, in a supporting role, on symbolic interactionism and phenomenology, the paper identifies three mechanisms through which the interaction order reshapes regulatory intentions: the situated completion of rules, the redistribution of exposure and face-work, and the reconfiguration of participation frameworks when AI systems become participants in classroom talk. Each mechanism is illustrated with empirical research on video-mediated teaching, camera policies, AI-detection tools, and generative AI tutors, and the three mechanisms are traced in recent developments in Russian education. From these mechanisms, it derives three propositions for research and policy evaluation, including the claim that visibility rules convert unequal backstage resources into unequal classroom standing. It concludes that principle-based regulation needs to be complemented by interaction-level assessment if it is to achieve its own stated aims.