Guardrails or Handbrakes? How Australian Universities Frame AI in Policy, and the Dominance of Misconduct Narratives

This project offers a critical analysis of how Australian universities are responding to generative artificial intelligence (GenAI) through institutional policy. Drawing on a national dataset of all Australian universities, identified via Universities Australia, the study examines publicly available policy and procedure documents to understand how AI is framed within higher education governance.

Using a critical policy analysis approach informed by Bacchi’s “What’s the problem represented to be?” (WPR) framework, the study does not treat policies as neutral responses to technological change. Instead, it investigates how universities construct the “problem” of AI, and what assumptions, priorities, and silences are embedded within these constructions.

Preliminary findings indicate that, consistent with international research, AI is most commonly framed through the lens of academic integrity and misconduct. Policies frequently position AI as a threat to the originality of student work, emphasising risks such as plagiarism, cheating, and unauthorised assistance. This framing often assumes a clear distinction between “human” and “AI-assisted” work, reinforcing traditional notions of authorship and individual effort.

At the same time, this dominant narrative appears to obscure alternative perspectives. There is comparatively limited attention to AI as a tool for learning, collaboration, or knowledge construction, and little engagement with how concepts such as originality may be evolving in an AI-mediated educational landscape.

By analysing these patterns, the project contributes to a deeper understanding of how Australian universities are shaping the role of AI in higher education. It highlights the need for more balanced and forward-looking policy approaches that move beyond risk and compliance, towards supporting ethical, transparent, and pedagogically meaningful uses of AI in teaching and assessment.

Project Team and Collaborators:
Dr Grace Jefferson