Conference Program

Since the 2022 emergence of advanced generative AI systems such as ChatGPT, narratives of urgency and transformation have come to dominate education policy debates. This paper critically investigates how two major international organizations (OECD and UNESCO) conceptualize “AI literacy” in their flagship policy documents. Drawing on text-mining and network text analysis, we compare their respective visions and the strategic selectivities they advance for reshaping national education systems. Guided by Jessop’s (2005) strategic-relational approach, our analysis identifies a significant socio-technical shift: rather than positioning technology as something to be integrated into society, these frameworks portray society itself as being integrated into generative AI. Within this emerging educational paradigm, students are cast as “cybernetic” co-producers of knowledge who continuously interact with AI systems through feedback loops, while teachers are largely sidelined and confined to basic monitoring roles rather than pedagogical mediation. Educational institutions, in turn, are stripped of their pedagogical functions and reduced to sites that legitimize compliance.

We contend that these strategic selectivities mark a sharp departure from earlier approaches to educational technology policy. In the documents examined, generative AI is presented as a totalizing force that reorganizes classrooms around productivity and assessment while downplaying key issues such as teacher agency, institutional context, and critical engagement. In particular, within the OECD/EU framework, schools are positioned simultaneously as testing environments and extraction sites for generative AI systems, fundamentally reshaping educational priorities and the roles of educational actors. Most significantly, these efforts to define AI literacy risk foreclosing opportunities for learners to develop a critical understanding of power and influence in a world increasingly shaped by oligarchic control.