Advancing a critical artificial intelligence theory for schooling

Abstract

Artificial intelligence (AI) has gradually been integrated into major aspects of schooling and academic learning following breakthroughs in algorithmic machine learning over the past decade. Interestingly, history shows us that as new technologies become perceived as ‘normal’ they fade into uncritical aspects of institutions. Considering that schools produce and reproduce social practices and normative behavior through both explicit and implicit codes, the introduction of AI to classrooms can reveal much about schooling. Nevertheless, artificial intelligence technology (specifically new machine learning applications) has yet to be properly framed as a lens with which to critically analyze and interpret school-based inequities. Recent education discourse focuses more on practical applications of technology than on the institutional inequalities that are revealed when analyzing artificial intelligence technology in the classroom. Accordingly, this paper advances the case for a critical artificial intelligence theory as a valuable lens through which to examine institutions, particularly schools. On the cusp of machine learning artificial intelligence becoming widespread in schools’ academic and hidden curricula, establishing a practical epistemology of artificial intelligence may be particularly useful for researchers and scholars who are interested in what artificial intelligence says about school institutions and beyond.