Academics’ weak(ening) resistance to Generative AI: The cause and cost of prestige?
Authors
Watermeyer, RichardLanclos, Donna
Phipps, Lawrie
Shapiro, Hanne
Guizzo, Danielle
Knight, Cathryn
Affiliation
University of Bristol; Munster Technological University; University of ChesterPublication Date
2024-12-03
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The disruptive potential of generative AI (GenAI) tools to academic labour is potentially vast. Yet as we argue herein, such tools also represent a continuation of the inequities inherent to academia’s prestige economy and the intensified hierarchy and labour precarisation endemic to universities as prestige institutions. In a recent survey of n = 284 UK-based academics, reasons were put forward for avoiding GenAI tools. These responses surface concerns about automative technologies corrupting academic identity and inauthenticating scholarly practice; concerns that are salient to all who participate within and benefit from the work of scholarly communities. In discussion of these survey results, we explore ambivalence about whether GenAI tools expedite the acquisition or depletion of prestige demanded of academics, especially where GenAI tools are adopted to increase scholarly productivity. We also appraise whether, far from helping academics cope with a work climate of hyper-intensifcation, GenAI tools ultimately exacerbate their vulnerability, status-based peripheralisation, and self-estrangement.Citation
Watermeyer, R., Lanclos, D., Phipps, L., Shapiro, H., Guizzo, D., & Knight, C. (2025). Academics’ weak(ening) resistance to Generative AI: The cause and cost of prestige? Postdigital Science and Education, 7, 1171–1191. https://doi.org/10.1007/s42438-024-00524-xPublisher
SpringerAdditional Links
https://link.springer.com/article/10.1007/s42438-024-00524-xType
ArticleLanguage
enDescription
The version of record of this article, first published in [Postdigital Science and Education], is available online at Publisher’s website: http://dx.doi.org/10.1007/s42438-024-00524-xISSN
2524-485XEISSN
2524-4868Sponsors
Unfundedae974a485f413a2113503eed53cd6c53
10.1007/s42438-024-00524-x
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Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by/4.0/


