Academic-Integrity
Last updated: 10 August 2026
- The Verification Turn: Why AI Outputs Need Boundaries and Proof
AI governance is shifting from trusting model outputs to demanding traceable use, enforceable limits and independent checks. - Cambridge Hiring Review Tests Academic Accountability
Cambridge’s review of senior academic hiring raises questions about vetting, independent oversight and fair treatment of contested claims. - How Top Universities Actually Regulate Generative AI
A 2026 survey of top-20 research universities' generative-AI policies shows a spectrum from prohibition to permitted-with-disclosure, not a single model. - The Fundamental Rights Impact Assessment, Explained for Education
Article 27 requires a Fundamental Rights Impact Assessment before first use of high-risk AI. What it covers, who completes it, and how it relates to a DPIA. - High-Risk by Classification: What the EU AI Act Actually Asks of Detection Tools
AI-text detectors and proctoring sit in the EU AI Act's high-risk category. What accuracy and human-oversight duties mean for tools with known false positives. - The Quiet Ban on 'Engagement Detection': Emotion-Recognition AI in EU Classrooms
EU law has prohibited emotion-recognition AI in education since February 2025. What the banned tools claimed to do, and why the science behind them fell short. - The EU AI Act and the Classroom: What Changes for Assessment and Detection
The EU AI Act treats exam monitoring and grading as high-risk, and the literacy duty is already live. What that means for assessment and AI detection tools. - University Assessment Needs Verifiable Judgment, Not AI Detection
HEPI argues that universities should assess verifiable judgement rather than rely on AI detection alone. - The Knowledge Governance Gap: Institutions Are Improvising While AI Reshapes How Knowledge Is Made
From classrooms to codebases, AI is already inside knowledge work while schools, journals, and governments still improvise their response. - Detection or entrapment? The ethics of the professor's hidden-text trap
White-on-white instructions in briefs can catch AI use, yet they blur detection and entrapment and quietly erode trust on campus.