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Paper short abstract

AI in higher education is often framed as inevitable progress. Drawing on STS concepts of sociotechnical imaginaries and paradoxical infrastructure, my paper shows how techno-deterministic narratives constrain governance responses, producing regulatory ritualism rather than meaningful oversight.

Paper long abstract

Discourses surrounding artificial intelligence (AI) in higher education frequently frame the technology as an inevitable stage in the evolution of teaching and learning. This paper argues that such narratives function as hegemonic normative frameworks that constrain institutional and policy responses to AI. Rather than opening space for deliberation about alternative sociotechnical futures, the rhetoric of inevitability creates a narrow trajectory in which AI adoption is assumed to be both necessary and desirable.

Drawing on Science and Technology Studies (STS), the paper conceptualises AI in higher education as a paradoxical infrastructure: a sociotechnical system that simultaneously promises efficiency, accessibility and innovation while generating tensions around academic integrity, educator autonomy, labour conditions and educational equity. These tensions are interpreted through competing sociotechnical imaginaries that frame AI as either transformative opportunity or existential threat.

Using qualitative document analysis of policy reports, academic literature and institutional materials relating to the Australian tertiary education sector, the paper examines how these imaginaries shape governance practices. The analysis demonstrates that techno-deterministic narratives of AI inevitability contribute to an environment of uncertainty in which universities adopt highly visible but often ineffective governance strategies. These practices resemble what Braithwaite et al (2007) describe as regulatory ritualism, where policy activity prioritises symbolic responsiveness over substantive regulatory transformation.

By situating AI governance within a debate about hegemonic normative frameworks in research and innovation policy, the paper shows how imagined technological futures delimit institutional decision-making and constrain possibilities for alternative trajectories in higher education.