The recent interest in the spaces and times of networked governance that emerged under the broad umbrella notion of topology is an exciting development in the sociology of education.  As stated in the NW 28 Special Call for this conference, topology represents a robust conceptual framework for the study of social constructions of time and the future. The key problem at the heart of the call is the need to identify alternative ways to think about the future, to challenge the regimes of algorithmic prediction and automation that are shaping the educational imaginary. This problem, however, requires a self-reflective discussion about the analytical scope made possible by topological thinking, which is to say, rather pithily, that the conceptualisation of alternative future narratives must be warranted by a solid empirical foundation. In this regard, a key issue is that of “topological morphology” (Decuypere et al., 2022; Decuypere & Vanden Broeck, 2020), understood as a conceptual category that can direct research efforts. Morphology, in this context, refers to spatial-temporal forms that are observable and can be subjected to empirical scrutiny, and which can be held up as either problematic (the forms we don’t want) or progressive - maybe even “hopeful” (the forms we want).  In this conceptual paper, I wish to contribute to this self-reflective discussion.

One of the key theses of topology is that relations among people and sociotechnical infrastructures of digitisation are ontologically constitutive (Lury et al., 2012), leading to continuities and discontinuities which may be dynamic and flowing across borders, but are nonetheless visible and researchable. These topological morphologies mostly emerge in two ways: a) firstly, they operate as practical enactments, observable in the “generative” dynamism that occurs across spaces, times and within assemblages of people and infrastructures (Lewis & Decuypere, 2023); b) secondly, they operate as part of a political-economic discourse connected to the logic of value creation, creating topological forms by projecting into the future imagined gains, benefits and sometimes risks (Williamson & Komljenovic, 2023). As these promissory anchor points are placed in the rarefied space-time of the future, they hold the present in place, steering policy and investment strategies and creating regimes of understanding and governance.

Moving tentatively across the terrain defined by these constitutive relations is the researcher, not a neutral and detached observer but a partial cartographer drawing - sometimes creatively – the shifting boundaries of emerging morphologies. The researcher is therefore framed as an agent and a “methodological bricoleur”, self-reflectively navigating the complexities of interpretative analysis to assemble critical accounts of bordering and debordering (Decuypere, 2021).

A central methodological problem in this framework is that of the account: who or what produces the empirical accounts of topological forms? There are a few possible answers to this question, but I wish to focus on one for obvious reasons of scope.  This answer posits that researchable accounts of education governance are, or will soon, emerge from the hybridisation of machine logic and human cognition (Gulson & Sellar, 2024; Gulson et al., 2022). The temporal horizon of this hybridisation of cognition is left deliberately vague. As humans and machines conjoin (or will soon do) in multiple ways, they provide (or will soon do) “synthetic” accounts of themselves and of novel topological morphologies. This conceptual and methodological argument is gaining interest in the study of education governance, and it is without doubt a valuable attempt to bridge policy sociology with recent innovations in the cultural and philosophical study of algorithms (Amoore, 2020; Parisi, 2019), which explored the risks but also the possibility of novel ethico-political opportunities arising from human-machine cognitive architectures.

This paper’s main contention is that an undue emphasis on the “cognitive” character of these human-machine accounts might create a methodological impasse, taking us further away from the situatedness of practice. The notion of a conjoined human-machine empirical account – understood as something visible and researchable - is framed in the work cited previously as a key moment of social construction where networks, alliances and the border politics of contemporary education governance are brought into being through a mixture of computational mathesis, sociological structuration and subjectivity. The partiality and ambiguity of these accounts are not threats to empirical scrutiny but are instead evidence of “infrastructural latencies” (Amoore, 2018): malleable and fluid affordances that arise unpredictably from the very nature of algorithmic logics and which, under unclear circumstances, may bring about innovation in policy and practice. I wish to propose a different argument: the accounts that people-plus-algorithms give of themselves are not evidence of cognitive complexity but of what could be better described as pseudo-cognition or “performed” cognition: the result of a sociotechnical-interactionist dynamic. The notion of sociotechnical interactionism is therefore put forward here as a conceptual and methodological alternative to the psychologism of “cognitive architecture”. Sociotechnical interactionism brings to the discussion several relational concepts derived from empirical sociology. For example, it affords a Goffmanian reading of topological accounts; one that does not inadvertently eulogise the (unwarranted) more-than-human character of the phenomena under scrutiny but examines instead the relationships between actors and algorithmic infrastructures as an ethnomethodological interplay of presentational and situational micropolitics (Goffman, 1964; Marres, 2020). The accounts that constitute empirical material for a topological sociology are thus reframed: not a conjoining of human and machine logics but a collection of situational encounters with ritualistic elements inherited from computational cultures as well as from established and ossified policy praxis. Therefore, the “policy situation”, with its repetitive aspects and interactional scripts, comes back into empirical focus. My contention is that this refocusing enables analyses more nuanced than what is offered by a cognitive focus of “joint rationalities” with all its implicit (and deterministic) assumptions about psychologised agency and machinic augmentation.

The topological character of contemporary networked governance and its entanglement with technologies of prediction and automation is not being contested here. What’s being contested is the empirical apparatus being assembled for its study. The sharing of cognitive functions between humans and machines - and the accounts they produce and which go on to become objects of empirical analysis - should be reframed as the outcomes of situational encounters between actors/entities, whose goals and agendas are momentarily aligned and may shift depending on the flow of the emerging topological morphology. In conclusion, we don’t need new ontological categories that allude to post-human cognitive hybridisation to make sense of topological morphologies. It might be sufficient to reconsider the role of autonomous or semi-autonomous agents - to be understood as composite, distributed and indeed “infrastructural” rather as individuated entities. These infrastructural actors are now increasingly implicated in the micro-political dynamics of education governance. The notion of sociotechnical interactionism that I propose here also brings into view the political interplay between empirical accounts: those provided by people, those provided by machines, and those provided by humans who have become momentarily entangled – rather than cybernetically fused - with machines. Of course, several methodological challenges arise from this conclusion - chief among them the need to move beyond description in the analysis of the situational politics that bring humans into contact with digital infrastructures. As noted by Marres (Marres, 2020), this move should involve active curatorial work from the researcher: a deliberate effort to tease out empirically interesting situations from computational arrangements which are opaque, black-boxed, biased and where participation is distributed, patchy and constantly shifting.

Amoore, L. (2018). Cloud geographies: Computing, data, sovereignty. Progress in Human Geography, 42(1), 4-24. Amoore, L. (2020). Cloud ethics: Algorithms and the attributes of ourselves and others. Duke University Press. Decuypere, M. (2021). The topologies of data practices: A methodological introduction. Journal of New Approaches in Educational Research, 10(1), 67-84 , ISSN = 2254-7339. Decuypere, M., Hartong, S., & van de Oudeweetering, K. (2022). Introduction―Space-and time-making in education: Towards a topological lens. European Educational Research Journal, 21(6), 871-882. Decuypere, M., & Vanden Broeck, P. (2020). Time and educational (re-) forms—Inquiring the temporal dimension of education. In (Vol. 52, pp. 602-612): Taylor & Francis. Goffman, E. (1964). The neglected situation. American anthropologist, 66(6_PART2), 133-136 , ISSN = 0002-7294. Gulson, K. N., & Sellar, S. (2024). Anticipating disruption: artificial intelligence and minor experiments in education policy. Journal of Education Policy, 1-16. Gulson, K. N., Sellar, S., & Webb, P. T. (2022). Algorithms of Education: How Datafication and Artificial Intelligence Shape Policy. University of Minnesota Press. http://www.jstor.org/stable/10.5749/j.ctv2fzkpxp Lewis, S., & Decuypere, M. (2023). ‘Out of time’: Constructing teacher professionality as a perpetual project on the eTwinning digital platform. Tertium Comparationis, 29(1), 22-47. Lury, C., Parisi, L., & Terranova, T. (2012). Introduction: The becoming topological of culture. Theory, Culture & Society, 29(4-5), 3-35 , ISSN = 0263-2764. Marres, N. (2020). For a situational analytics: An interpretative methodology for the study of situations in computational settings. Big Data & Society, 7(2), 2053951720949571. Parisi, L. (2019). Critical computation: Digital automata and general artificial thinking. Theory, Culture & Society, 36(2), 89-121. Williamson, B., & Komljenovic, J. (2023). Investing in imagined digital futures: the techno-financial ‘futuring’ of edtech investors in higher education. Critical Studies in Education, 64(3), 234-249. https://doi.org/10.1080/17508487.2022.2081587