A critical review of GenAI policies in higher education assessment: a call to reconsider the "originality" of students' work

This study offers a critical examination of university policies developed to address recent challenges presented by generative AI (GenAI) to higher education assessment. Drawing on Bacchi's 'What's the problem represented to be' (WPR) framework, we analysed the GenAI policies of 20 world-leading universities to explore what are considered problems in this AI-mediated assessment landscape and how these problems are represented in policies. Although miscellaneous GenAI-related problems were mentioned in these policies (e.g. reliability of AI-generated outputs, equal access to GenAI), the primary problem represented is that students may not submit original work for assessment. In the current framing, GenAI is often viewed as a type of external assistance separate from the student's independent efforts and intellectual contribution, thereby undermining the originality of their work. We argue that such problem representation fails to acknowledge how the rise of GenAI further complicates the process of producing original work and what it means by originality in a time when knowledge production becomes increasingly distributed, collaborative and mediated by technology. Therefore, a critical silence in higher education policies concerns the evolving notion of originality in the digital age and a more inclusive approach to address the originality of students' work is required.