Résumé: Recently the Times Higher Education launched a series of 'Spotlight' articles and think pieces on AI and the University, claiming 'artificial intelligence is already impacting higher education, and signs are that the influence of evolving technologies on university life is just getting started'.Footnote 1 The collected pieces are well-considered and in places cautious about AI hype, yet they tend to reflect a widespread assumption that AI will inevitably transform the future of education-for the better. The problem with such promotion of AI and the future of education is it presupposes AI will operate as planned and intended, with any problems emerging during its development or deployment smoothed out through either technical tweaks or appropriate ethical frameworks. None of these things are necessarily the case. As Meredith Broussard argues in Artificial Unintelligence: How Computers Misunderstand the World, 'the way people talk about technology is out of sync with what digital technology actually can do' (Broussard, 2019, p. 6). She coins the phrase 'technochauvinism' to describe the flawed assumption that digital technologies like AI are always the solution. Computer technology, Broussaard argues, simply does not always work as expected or intended. It is technochauvinist to assume it will. There is no good reason to presuppose AI used in education will work as expected either. For all the current enthusiasm for AI-based teaching and learning, the evidence base for their transformative effects on education remains thin (Holmes et al., 2022). Moreover, at the time of writing, the biggest stories about AI in education concern automated natural language generating technologies. While some foresee these language 'transformer' models as transformative for student research and writing (as is the case in the Times Higher Education series), they are also extremely problematic instantiations of AI that can reproduce significant biases, generate false information, and risk disproportionately harming those at the margins (Perrotta, Selwyn and Ewin, 2022). This controversy seems far from the expected promise of AI transforming education for good, and surfaces important questions about whether future research and development in AI in education might be supported by a more social and historical sensitivity.

Langue: Anglais