Why Detection Failed and Oral Defense Survives
Detection-based approaches to AI cheating have one structural weakness: they require the tool to outpace the model generating the work, and that race is already lost. The lecturer who announced the viva requirement was not describing a policy innovation — they were describing the only remaining leverage point an educator has, which is the moment a student must speak . A student who submitted AI-generated prose and cannot name the source they supposedly consulted has been caught not by a detector but by their own silence.
The viva's durability as a response lies in what it actually tests. A reported wave of perfect homework paired with blank stares captures the gap precisely: the submitted artifact looks learned; the student, asked to explain it, is absent. That gap is not a cheating problem — it is an assessment design problem. Educators who have reframed it that way have already moved on from the detection debate.