This event took place on 15th June 2023.
Dr Carlo Perrotta, University of Melbourne
Abstract
In this paper, I tentatively draw on Foucault’s work on the historical analysis of knowledge (Foucault, 1966) and, in particular, I pay attention to his use of Cervantes’ Don Quixote as a case study to examine the changes that occurred in knowledge in the 15th and 16th Centuries, as language began to break relationships of similitude and resemblance with reality. Foucault argued that Don Quixote is a tragic figure who has not moved on with the times. He is not aligned with the change in the epistemic landscape, where the similarities between things are no longer a source of knowledge but a source of confusion to be unpicked and exposed. In this new, confusing reality, Don Quixote is locked in a relentless quest, relying on the codifications of chivalric fiction to confirm his own very existence: ‘He must endow with reality the signs-without-content of the narrative’ (p46). The paper engages with the thesis – without committing to it - that we are entering an epistemic condition where generative AI rearranges our relationship with language and meaning along similar lines. In this sense, generative AI is the culmination of what Foucault called the ‘Leibnizian project of establishing a mathematics of qualitative orders.’ The overarching provocation is that Don Quixote is a fitting metaphor for what we are experiencing in education in the current historical moment: epistemic confusion, simulated competence, and automated extravagance.
Foucault, M. (1966). The Order of Things. Routledge.
Biography
Carlo Perrotta is Associate Professor of Digital Education at the Melbourne Graduate School of Education, which is part of the University of Melbourne, Australia. He holds a PhD from the University of Bath (UK). His research and teaching focuses on the relationship between technology, education, and society. His current work examines the impact of platformisation, automation and Artificial Intelligence (AI) on policy and practice.
ORCID: https://orcid.org/0000-0003-3572-0844