The Structural Risks of AI in Higher Education: From Integrity Discourse to Epistemic Reconfiguration
DOI:
https://doi.org/10.54097/v2xckm96Keywords:
Artificial intelligence; higher education; structural risk; educational agency; algorithmic governance; critical AI literacy.Abstract
Debates about artificial intelligence in higher education often focus on individual misconduct and academic integrity. This paper examines risks that arise when AI becomes embedded in the infrastructures, routines, and governance of universities. Through a conceptual analysis informed by existing literature, it considers surveillance and data extraction, algorithmic bias, epistemic convergence, cognitive deskilling, relational displacement, and institutional dependence on technological systems. It argues that these risks are reinforced by commercial acceleration, delayed governance, and tensions between educational values and platform priorities. The discussion develops responses centred on institutional accountability, assessment redesign, critical AI literacy, and the protection of educational agency. It also considers the practical constraints of resources, expertise, and institutional capacity. The paper concludes that responsible AI integration requires attention to how technologies reshape knowledge, academic work, and educational relationships, alongside safeguards for individual users.
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