Detectors put Thélyson Orélien’s bestselling novel at 92 to 100 per cent AI. What decided the case four weeks later were his working files. Eight facts from the case, and what they mean for exams, theses and publishers.

Every academic integrity measure processes personal information. What courts, regulators and universities in the UK, US and Australia say about plagiarism checks, AI detection, proctoring and process documentation, and the conditions under which each tool holds up.

AI detection has improved sharply on one axis: it rarely accuses innocent writers now. On the axis that decides cases, catching text that was deliberately disguised, far less has changed. And even a perfect detector would answer the wrong question.

Does generative AI harm learning or support it? It depends on the task, the stage of learning and what the assessment is meant to demonstrate. AIAS 2.1 turns that complexity into a practical assessment-design framework.

Since August 2026, new Claude models have been weaving an invisible watermark into their text. For universities, that sounds like a useful new signal for AI detection. But a watermark answers a different question from the one examination boards actually face, and Anthropic says so itself.

Bavaria requires documentation but does not say what it consists of. TEQSA describes what process evidence is but cannot make it binding. Both aim to make documentation practically workable. Here is what that looks like and why almost nothing changes for students.

Within weeks of each other in the summer of 2026, two agencies on two continents reached the same conclusion by entirely different routes. Australia’s TEQSA argues from sector practice; Bavaria legislates. Both land on documenting the path to the text.

Bavaria’s draft law inverts the default: allow AI in unsupervised written exams, but document its use. What the draft says — and what it leaves open.

Dr. Monika Oertner has put the academic core competencies online as a rotatable deltahedron: it answers the question of what AI use does to it. Why this model convinces us and how our corroboration standard protects the spaces where those competencies are trained.

Translate a source and plagiarism checkers go blind: research shows it. How semantic detection keeps academic integrity intact in the AI era.