In just a few decades, a new vocabulary - consisting of platforms, clouds, machine learning, personalisation and much more - has become inevitable to describe a rapidly growing part of our social world. Under the heading of algorithmic management, sociologists have begun to study how these new elements relate to the contemporary conditions of work and its control. By and large, their conclusions suggest that algorithms open up novel ways to discipline labour in pursuit of ever greater efficiency – Taylorism on steroids, for short.  Despite some similarities, I argue that algorithmic management should not be understood as a simple extension of scientific management, since it operates within a different worldview: Whereas Taylor’s scientific management saw humans as programmable machines, algorithmic management sees machines as capable of learning.

This contribution explores this different worldview of algorithmic management, so as to illustrate how the concept can be made useful for the sociology of education. This is done by focusing on classroom instruction as a moment where algorithms, professional practice and school organization intersect. Taking cues from Niklas Luhmann’s systems theory and pragmatist theories of interaction, I examine how digital interactivity translates educational aspirations into the interaction with a lifeless object. How are the defining traits of pedagogical interaction reorganised to orchestrate its progression? This translation act, I shall argue, hinges on its ability to (algorithmically) anticipate and coordinate futures, so that a platform or app's intent to educate can appear as a constancy. On basis of this characterisation, I aim to complement the existent literature on datafication which has hitherto understood the above depicted evolution as either the unwelcome intrusion of surveillance capitalism or as the surge of mindless automatons that threaten to strip professional care of its humanity. In contrast with that literature, I highlight how digitally mediated (self-)instruction participates in and perpetuates education’s broader wish to program an uncontrollable future.

My contribution builds on ethnographic fieldwork in New York’s EdTech scene and classroom observations in Emilia Romagna (Italy), carried out via an extended case method. In contrast to grounded theory, this sociological approach is theory-driven and aims to observe (conflictual) situations that might lead to theoretical innovation. The unique benefit of using systems theory for such scope is that this method can still be used to observe the self-narration and self-organisation of the social world – an advantage usually reserved for grounded theory. Central to the fieldwork and this contribution is precisely this focus on self-organisation and differentiation processes.

The contribution's primary goal is to provide an impetus for a novel theorization of our relationship with digital tools. It thus wishes to articulate a counter-intuitive perspective on recent developments in education and more particularly its emergent platformisation brought forth by digital technology. The aim is to arrive at a theoretically innovative and empirically underpinned conceptualisation that avoids the pitfalls of all too easy moralisation -- that is not interested in merely passing judgement, be it condemnation or praise.

Esposito, Elena (2022). Artificial Communication. Cambridge, Massachusetts: MIT Press. Luhmann, Niklas (2002). Das Erziehungssystem der Gesellschaft (D. Lenzen, editor). Frankfurt am Main: Suhrkamp. Kellogg, Kate C., Valentine, Melissa, and Christin, Angèle (2019). Algorithms at work: The new contested terrain of control. Academy of Management Annals, 14(1), 366-410. Stark, David & Vanden Broeck, Pieter (forthcoming). Algorithmic Management and New Class Relations. Witzenberger, Kevin and Gulson, Kalervo N. (2021). Why EdTech is always right: Students, data and machines in pre-emptive configurations. Learning, Media and Technology, 46(4), 420–434.