Discourse analysis reveals seven forms of academic erasure in educator discussions of generative AI, suggesting a shift from intellectual inquiry to performative fluency.
This paper introduces the concept of ‘academic erasure’ to describe how generative AI tools, while producing fluent and compliant writing, undermine the critical thinking and epistemic labour traditionally associated with academic work. Drawing on academic literacies, critical pedagogy, and discourse analysis, the study examines 49 Reddit posts by educators and identifies seven forms of erasure: epistemic labour, authentic voice, educator efficacy, trust, pedagogical method, the human-AI boundary, and institutional legibility. These themes suggest a shift from intellectual inquiry to performative fluency, where writing becomes a product rather than a process. The study argues that the risks of AI extend beyond plagiarism or misconduct, subtly altering the very meaning of learning and authorship. It highlights the need for a reorientation of assessment and pedagogy towards process, voice, and intellectual depth, urging educators to prioritise the labour of thinking over algorithmic correctness in an increasingly automated educational landscape.
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Nwagboso et al. (2026) studied this question.
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