This presentation draws on recent research in the UK and China that has examined the increasing use of artificial intelligence (AI) to develop and deploy so-called ‘personalised’ or ‘adaptive’ education technology. Suggested by these terms, AI technologies might be perceived as rather straightforward ways of adjusting, differentiating and individualising educational provisions in response to student diversity; attributes which tend to be framed as effective approaches to realising inclusive education (Lindner and Schwab, 2020). However, we argue that there is a pressing need to re-examine such assumptions and consider how AI technologies might be better designed in the future, by building a greater understanding of the precise functioning of AI systems and connecting this knowledge deliberately with critical perspectives on inclusive education, particularly those that pose important questions over the implications of continuing a traditional special, additional, or individualised needs response to diversity (e.g., Florian, 2014; Slee, 2011). The analysis developed in this paper builds on the recent call for critical studies of digital education platforms (Decuypere et al. 2021). In particular, Decuypere et al. suggest the need for more research that examines the ‘performative effects of platforms’ (2021, p2); in other words, the capacity of such technologies to shape educational practice, often in ways unforeseen by technology designers and teaching practitioners themselves. Two specific AI-driven software platforms will be discussed: UK-based ‘Century’ (https://www.century.tech/) and China-based ‘Squirrel AI’ (http://squirrelai.com/), with a focus on how particular conceptualisations about knowledge, learning, and teaching are ‘built-in’ to the design and subsequent functioning of the technology. This includes, for instance, the ways such technologies predefine a mathematical representation of all knowledges in a particular domain, position and categorise learners as passive recipients of automated decision-making over what they should be learning and how, and de-professionalise teachers by marginalising their roles with the AI-infused classroom. Such effects are counterproductive for inclusive education systems that value diversity, especially as such AI systems appear to standardise curricula, activities, and experiences, and significantly reinforce barriers to learners and teachers’ agency. The paper concludes that we must give more attention to the current development and usage of AI technologies and ensure the participation of learners, teachers, and broader communities in a process of co-creating change for inclusive education (Pantić and Florian, 2015; Wang, 2023).

Decuypere, M., Grimaldi, E. & Landri, P. (2021) Introduction: Critical studies of digital education platforms. Critical Studies in Education, 62(1): 1-16. Florian, L. (2014) Reimagining special education: why new approaches are needed. In Florian, L. (ed) The SAGE Handbook of Special Education (2nd edition). London: SAGE. pp. 9-22. Lindner, K. and Schwab, S. (2020) Differentiation and individualisation in inclusive education: a systematic review and narrative synthesis. International Journal of Inclusive Education. AHEAD-OF-PRINT, 1-21. Pantić N., Florian L. (2015). Developing teachers as agents of inclusion and social justice. Education Inquiry, 6(3), 333–351. Slee, R. (2011) The Irregular School: Exclusion, Schooling and Inclusive Education. Abingdon: Routledge. Wang, Y. (2023) ‘It is the easiest thing to do’: university students’ perspectives on the role of lecture recording in promoting inclusive education in the UK. Teaching in Higher Education. Advance online publication. pp.1-18.