Schools struggle to define what AI competence means for teachers

<p>The development of artificial intelligence (AI) in education has been underway for over half a century. It is only in the past decade that commercial AI-based technologies have been introduced into classrooms, with the promise of improving and transforming teachers’ work. This compilation thesis aims to generate an improved understanding of the implications of AI for the teaching profession. It does so by exploring the ways in which AI is being introduced in school settings, how AI comes into being—how it is materialised—and what this materialisation implies. Actor-Network Theory is applied as a methodological approach and analytical lens to explore the enactments between humans and three different AI technologies, where technology plays an active role.</p><p>The thesis comprises five papers. Paper I is a literature review examining teachers' professional knowledge related to AI. Papers II-V are based on three fieldwork studies conducted in Swedish primary and secondary schools between 2020-2023. AI is introduced and materialised on the one hand as an emergent yet implicitly defined form of professional knowledge that teachers are expected to acquire and integrate into their practice. On the other hand, AI comes into being as different data-driven technologies in the making, strongly underpinned by ideas of automating and augmenting teachers’ work. The findings also show how teachers adapted to the technology and compensated for its shortcomings in different ways, even when the technology acted to undermine their professional expertise.</p><p>Taken together, the thesis proposes that AI, as related to the teaching profession, is far from a settled affair. AI has still to deliver on its claimed promises. In this context, teachers’ ethical judgement (phronesis) can play an important role in the future making of AI, a making that moves beyond f(ai)th.</p>