Blog
Briefings and posts from the research team
Last updated: 23 July 2026
Posts and analysis as they happen. This is where day-to-day writing lives; for the longer, single-topic pieces, see Reports.
- What Databricks’ $188 Billion Valuation Does Not Prove
Databricks’ $188 billion funding valuation is a business signal, not evidence that its AI products are useful, accountable or good value. - New York Pauses Hyperscale AI Datacentre Permits
New York’s one-year pause on new hyperscale AI datacentres puts energy, water and accountability under scrutiny. - AI Wealth Redistribution Needs More Than Promises
Neil Rimer’s comments expose the gap between AI wealth concentration and voluntary giving. - 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. - Outside the EU, Inside the Act: What UK Universities Need to Check
The EU AI Act can reach UK universities with EU students or EU data, even without an EU campus. What Article 2(1)(c) means, and where to look first. - 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. - University Assessment Needs Verifiable Judgment, Not AI Detection
HEPI argues that universities should assess verifiable judgement rather than rely on AI detection alone. - Albanese AI framework faces 2027 wait as Greens push halt
Australia’s proposed national AI rules protect creatives but delay legislation to early 2027, prompting Greens calls to pause hyperscale datacentres. - 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.