Conference Agenda

Since ChatGPT’s public launch in late 2023, AI has excited imaginations, generated symbolisations and stirred up anxieties—nowhere more so than in education. As educators we might think that AI will replace us; that we must police students’ ‘misuse’ of it, often with yet more AI tools; and that we should constantly update our educational practices to ‘keep up’. At the same time, AI is seductive in that it relieves us of some donkey work and can offer us moments of pleasure, curiosity and creative experimentation.

In this algorithmic age, AI appears as a neutral tool, obscuring its enmeshment in its circuits of politics, power and privilege. AI has also become a fetishistic object onto which we, as educators, project fantasies, hopes, fears, desires and insecurities. It unsettles taken-for-granted ideas about what it means to know, to educate, to teach, and to act responsibly as educators, who constantly struggle to perform ‘expertise’ while, at the same time, we grapple with uncertainty and unknowing, both consciously and unconsciously.

This symposium speaks to the ECER 2026 theme of knowing and acting in the changing conditions and potentials of education research by treating AI not only as a desirable object of policy or methodological interest, but as a disruption of subjectivity, knowledge and practice in education. We share three papers that engage with AI’s disturbances and openings, by drawing on psychoanalytical perspectives, including poetic, artistic and experimental thinking.

Issues and questions we explore include (but are not limited to):

● How might our obsession with AI be understood conceptually (e.g. psychoanalytic, philosophical, sociological, political-economic lenses)?

● To what extent is our pleasure in AI symptomatic of broader neoliberal, managerial or audit cultures in education?

● How does AI reconfigure desire, fantasy, professional identity and teachers’ relations to knowledge and ignorance?

● What forms of negativity such as doubt, uncertainty, or absence accompany AI and should be taken seriously as (non)productive forces in teacher education and teacher-education research?

● How might creative, experimental or situated forms of thinking and enquiry help us stay with the trouble of AI, rather than resolving it too quickly?

In an era when artificial intelligence is growing exponentially and it is difficult to separate marketing hype, utopian fantasies, and dystopian anxieties of human replacement (Merchant 2024), it is important to engage in new forms of critical analysis. To this end, the papers of this symposium bring psychoanalytic and other theories to bear on the problematic presented by AI. Paper 1 explores the issue of the relation between humans and so-called artificial intelligence through the question of whether Artificial Intelligence can be said to have an unconscious. Paper 2 critically examines what it might mean for our worldly engagement, within educational contexts, if we delegate our thinking to AI – if we are letting the ‘machine’ do the difficult work of grappling with negativities for us. Paper 3 takes a Lacanian lens to explore what ‘intelligence’ means, asking how thinking changes through the use of artificial intelligence in higher education contexts.

Artificial intelligence (AI) is a ‘hot topic’ in education (and society) today, one that evokes both utopian and dystopian responses. Of course, AI is not a singular entity and the term is often used when people are specifically referring to its generative forms, such as Chat GPT and Co-Pilot. However, both the utopian and dystopian discourses assume that AI, with its promises “to separate neuroscience from biology and thought from the body” (Millar, 2021, p. 1), simulates, and has the capacity to surpass, human intelligence. In this paper, we explore the relation between human and artificial intelligence by asking whether AI has an unconscious. We explore this question from several angles, including underlying psychoanalytic questions about the relationship between being and thinking and between knowing and enjoying, as well as questions about our status as subjects of knowledge versus subjects of desire (McGowan, 2013, 2016). If, for Lacan, subjectivity is tied to and shaped by the signifier and the socio-symbolic system of language, while the notion of ‘extimacy’ subverts hard and fast distinctions between the individual and the social, does anthropomorphising in discussions of AI cease to be an issue, not least because the individual subject is not purely human in the sense envisaged by humanism, but also because to the extent that AI comprises signifiers it inevitably ‘carries’ the desires (and lack/absence) that those signifiers evoke. To the extent that the ‘human' and ‘artificial’ are a continuum, rather than a pure opposition, and to the extent that trauma is inherent to symbolisation, whether by humans or machines, does it make sense to talk about an ‘algorithmic unconscious’ and ‘algorithmic desire,’ to describe the complex, opaque processes that influence an AI's behaviour and decision-making, without either its, or its creators’, full understanding and ‘awareness’. If AI has an unconscious, how are we formative of its unconscious via the early trauma we inflict upon it, as manifested in its prejudicial algorithms? Might AI be viewed as a discomforting prosthetic unconscious, whose 'talking back' echoes and amplifies our individual and collective racism, sexism, homophobia, etc.? Conversely, perhaps, is the unconscious excluded from AI by definition, at least in its current Large Language Model (LLM) formations, that merely predict text and images based on statistical probabilities, because, amongst other considerations, AI can metonymise but not metaphorise? In this paper, we explore these and other questions with consideration of their implications for Education.

McGowan, T. (2013). Enjoying what we don't have: The political project of psychoanalysis. Lincoln, NE: University of Nebraska Press. McGowan, T. (2016). Capitalism and desire: The psychic cost of free markets. New York: Columbia University Press. Millar, I. (2021). The psychoanalysis of artificial intelligence. London: Palgrave Macmillan.

Relatively uncritically, has AI become an everyday technology in education. It comes with a lot of promises, such as its ability to handle huge amounts of information that we, as human beings, cannot, that it can save us from a lot of frustrating struggles in education linked to productivity, solutionism, effective teaching etc. (Costa and Murphy, 2025). It is also claimed that AI can be a source of inspiration for us, as educators, as well as for our students, helping us/them to come up with new and thoughtful ideas and so on. Still, we do not know what the effects will be from the use of AI in education. Thinking, for example, is not just a matter of being able to figure things out. It is also about ‘getting lost’, ‘getting stuck’, confronting dangerous ideas and taboos, and trying to think the unthinkable by playing with signifiers and meanings in radically new and unforeseen ways. However, it is often a demanding and very frustrating affair, as it can also confront us with the lack, the unknown, absences, and incompleteness in our symbolic-imaginary approaches to the world. Because of AI, we might not confront our unconscious struggles. The questions are: What does it mean if this task is given to AI, and if we thereby relieve ourselves of this task and avoid (inter)personal engagements with negativities in education? (Rüsselbæk Hansen, 2024). What does it mean to think and speak as human beings without being enframed symbolically by AI-generated technology (Žižek, 2025)? And what can such enframing do, for example, in education – if we cannot transgress it – to our ethical-political aspirations and horizons? (Lacan, 1997). The paper engages with such and similar questions inspired by psychoanalytical theory and by focusing on concepts such as desire, negativity, pleasure, the big Other, uncertainties, and human subject experiences.

Costa, C and Murphy, M. (2025). Generative artificial intelligence in education: (what) are we thinking? Learning, Media and technology. https://doi.org/10.1080/17439884.2025.2518258 Lacan, J. (1997). The seminar of Jacques Lacan, Book VII: The ethics of psychoanalysis 1959-1960 (D. Porter, trans.). Norton. Rüsselbæk Hansen, D. (2024). Democratic engagements with negativities in education and public school. Speki. Nordic Philosophy and Education Review, 1(1), 43-57. Yadlin-Gadot, S. and Hadar, U. (2023). Lacanian Psychoanalysis: A Contemporary Introduction. Routledge. Žižek, S. (2025). Quantum History: A new Materialist Philosophy. Bloomsbury.

AGI (Artificial Generative Intelligence) usage in higher education contexts has increased rapidly over the past few years, igniting debate around its effects on student (and indeed educator) capacity for thought. Seen as a new potential for ‘human-level’ thought by some (Van Den Berg and Du Plessis, 2023), others see AGI as muting human capacity for thought, with thinking relocated out of the human brain and into the machine (Purser, 2025). Our own observations indicate that often students refer to AGI tools to think around a topic. In this paper, we explore what is happening in this debate around AI and human thought, revisiting Descartes through a Lacanian lens. We ask what ‘intelligence’ means, how this might relate to thinking, and interrogate the differences between human and AGI ‘thought’. We first tangle with the notion of ‘intelligence’ and situate the word ‘generative’ within thought and structures of language. We ask what this means for AGI/ human beings, comparing LLMs to Lacan’s notion of the combinatorial logic of linguistic exchange and language's role in formation of subjectivity (Lacan, 1977). Through this discussion, we resituate AGI away from popular anthropomorphisms and back into its technological being. However, the existence of such anthropomorphism, we argue, should be taken seriously, as it is in human attitudes towards and beliefs about AGI that we will find our own unravelling. Through a Lacanian reading of human being as driven by the lack that motivates action and thought, we examine how AGI tools have garnered prolific usage in academic contexts (Lacan, 1992). We explore how, within the discourse of the university, the dominant cause of desire is that of knowing, or, in Lacanian terms, the generation of the subject-supposed-to-know (Black, 2025). It is not knowing, positioned as undesirable social status, that compels engagement with a tool marketed to synthesise ‘knowledge’. AGI is thus, we argue, given mythical status as a knowing Other, superior to the human mind and student subject. Whilst the subject is lost in the ‘thinking’ of AGI, humans programme the machine with human desires, evoking a destructive projection of the self into the machine. By so doing, we gift our unconscious desires to the Big Other of modern capitalism (the owners of AGI-generated data) whilst simultaneously dehumanising our education by outsourcing the language that structures our thinking: we do not think therefore we are not.

Black, J. (2025) The Subject of AI: A Psychoanalytic Intervention. Theory Culture and Society, pp. 1–17. Lacan, J. (1977) Ecrits. Abingdon: Routledge. Lacan, J. (1992) The Ethics of Psychoanalysis. Abingdon: Routledge. Purser, R. (2025) AI Is Destroying the University and Learning Itself. Current Affairs [Online], 1 December. Available from: . Van Den Berg, G. and Du Plessis, E. (2023) ChatGPT and Generative AI: Possibilities for Its Contribution to Lesson Planning, Critical Thinking and Openness in Teacher Education. Education Sciences, 13 (10) September, p. 998. Available from: .