I’m pleased to share my chapter, “The New Spirit of Education and the Techno-Politics of AI” (Chapter 3), published in the Handbook of Critical Studies of Artificial Intelligence and Education (Edward Elgar, 2026), edited by Wayne Holmes — a volume that brings together leading international scholars to examine, from a critical perspective, the ethical, sociocultural, and political implications of AI for education. Its release coincides with the launch of the Critical Studies of Artificial Intelligence and Education network, a new space for researchers, teachers, policymakers, and students to share ideas, challenge one another, and collaborate.

You can read my chapter here: Chapter 3 — The New Spirit of Education and the Techno-Politics of AI (PDF). Below is the introduction.

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INTRODUCTION

Here’s the full Introduction (3.1) cleaned up into proper paragraphs — no broken lines, ready to copy and paste:

A (new) spectre is haunting education – the spectre of Artificial Intelligence (AI). This spectre is being shaped, promoted, and delivered by a new holy alliance: Big Tech corporations and venture capitalists, neoliberals and ultra-libertarians, neo-reactionaries, and proponents of eugenics. Moreover, intergovernmental organisations such as the World Bank (WB), Organisation for Economic Co-operation and Development (OECD), United Nations (UN), and European Union (EU), among others, further contribute to this phenomenon through policies and soft governance practices often framed in the language of neutrality and objectivity. While diverse in nature, these political-ideological rationalities converge, mutually reinforce, and collectively shape contemporary educational agendas.

To critically explore the shifting role of education under these technological and ideological conditions, this chapter introduces the concept of the ‘New Spirit of Education’ (NSE). The NSE describes the contemporary ideological, political, and technological paradigm reshaping education through intensified market rationalities, data-driven governance, and technological determinism. To situate NSE within historical continuities and changes, the chapter unfolds in three interconnected parts.

First, the chapter historicises the techno-political apparatus in education and establishes the earlier ‘spirits’ that shaped educational practices, governance structures, and ideological orientations. This section, titled ‘Schools-as-Machines-for-Learning’, provides a critical genealogy tracing how instruments for behavioural control, surveillance, and punishment were introduced in educational settings. It starts with eighteenth-century Victorian-era disciplinary techniques, exemplified by the Lancaster Method, moves through the emergence of statistical prediction and eugenics in the nineteenth century, and culminates in the post-World War II momentum of radical behaviourism and early teaching machines.

The second section argues that the advent of AI in education does not represent a departure from this historical trajectory but rather extends and intensifies it under the contemporary banner of Machine Learning-for-Schools. Here we define the NSE explicitly as a cohesive ideological transformation expressed through three interrelated dimensions: (i) the resurgence of metaphysical quantification and classification, now rebranded through machine learning (ML) science (Agüera y Arcas, 2019; Winston, 2018; Michell, 2022); (ii) the neoliberal imperative of market-driven education, characterised by increasing influence from business firms acting as political entities that privatise, commodify, and redefine public educational goods (Scherer et al., 2009; Santori et al., 2016; Komljenovic et al., 2023); and (iii) the rise of anti-democratic ideologies and culture driven by Big Tech elites and neo-reactionaries associated with movements such as the ‘Dark Enlightenment’ and ultra-libertarianism (McQuillan, 2022; Gebru & Torres, 2024). Together, these features represent not isolated phenomena but the collective manifestation of a cohesive, ideologically driven transformation reshaping contemporary educational institutions.

Finally, the third section explores how the NSE affects the educational experiences, agency, and autonomy of teachers and learners. Introducing theoretical concepts of seriality (Sartre, 1978/2004) and interpassivity (Pfaller, 2017), we critically analyse how AI-driven education fosters alienation, passive engagement, and isolated subjectivities. Such outcomes undermine education’s crucial role as a precondition for democratic society – developing competent, reflective agents who actively take part in social, economic, cultural, and political life, capable of collectively changing and renewing societal norms and structures.

In conclusion, the chapter calls for reclaiming education as a democratic, relational, and emancipatory public good, proposing pathways of resistance to the technologically intensified threats posed by the NSE.