Anticipating disruption: artificial intelligence and minor experiments in education policy

Abstract

ABSTRACT The growing use of artificial intelligence in education extends and intensifies technologies of governing, including datafication, performativity and accountability. In this article, we outline how the use of AI and data science has the disruptive potential to create new norms in education policy and governance. We report on an ethnographic investigation into an education department initiative that involved data scientists using machine learning to identify causal links between different school-based and non-school based factors, and educational outcomes. The article proposes that machine learning is being introduced into this education department as a set of minor experiments in education governance. We focus on issues of changing expertise and evidence and differences in method between new data science approaches and established statistical expertise in this education department, in order to highlight minor but important new governance practices. We conclude that the increasing use of AI in education, as part of new cognitive infrastructures, is quietly shifting the ways in which education systems operate.