AI as a stress test for education
The living center of Kim Flintoff’s work is the collision between generative AI and education systems. The selection does not treat AI as a novelty. It returns to the harder question: whether universities were already strained by assessment habits, workload pressures and brittle ideas of academic integrity before AI made those strains visible.
A recurring editorial instinct is to test institutional reflexes. Detection software, watermarking and policing appear less as solutions than as symptoms of panic. The more durable interest is in redesigning assessment, rebuilding trust and helping teachers and students understand what AI changes about learning.
The strongest thread is capacity building. Cross-campus AI academies, faculty fluency, AI literacy and practical student guidance all point to a pragmatic belief: institutions need shared learning cultures, not scattered tools or one-off rules.
- Further reading
- Are you using AI to study? Here’s how to do it well
- What most AI tutorbots get wrong about learning
- Our research shows how AI is getting better at exams. Here’s how unis can respond
- Academics and AI marking: a welcome aid for overworked staff or a sloppy shortcut?
- From Fear to Fluency: Helping Faculty Navigate AI