In the frenzied attempt to address the impact of generative artificial intelligence (Gen-AI) in higher education, universities have narrowed their concerns to a key question: how to design ‘secure’ assessments that resist the influence of Gen-AI large language models. Such framing implicitly casts students as being at risk of Gen-AI influence. This is evident in institutional memos, working groups and practitioner discussions, which reflect a persistent concern with upholding academic integrity and ensuring that student work reflects their own effort. Yet, conversely, these same institutions champion Gen-AI as a tool for innovation and learning. These inconsistencies are too apparent to be ignored. This contradiction is not just ironic; it is symptomatic of a more profound issue. Gen-AI has come to expose higher education’s long-standing curriculum crisis: the transactional, performative approach to education that has undermined the deeper aims of higher learning, that of fostering meaningful intellectual growth and critical inquiry.
