I've recently launched a new analytics dashboard under the new "Insights" tab on my Global AI Regulation Tracker.
The dashboard displays charts/graphs on interesting patterns and trends in AI regulation generated by the data that I've collated for my tracker. For this initial launch, I've started with the easy 'quick wins' to capture global patterns, including:
📈 Legislative approaches to regulating
📈 Influence of EU AI Act
📈 Top focus areas in AI regulation around the world
📈 Top 10 most active jurisdictions based on AI-related legislative and executive activity
📈 Top 10 most active jurisdictions based on AI-related news reports
📈 AI related activity by multilateral organisations
This dashboard is still in beta mode as I continue to test different formats, layouts, etc. These analytics will update automatically with the latest tracker data. That's the beauty of digital data!
This will be an ongoing hobby project for me. I'll be adding new charts from time to time, and look forward to discovering patterns that highlight nuances in AI regulation and the Global South. I finally get to combine AI law and data science together, which is a niche crossover (yet I'm loving it!)
In the meantime, any errors/corrections, please let me know.
Global
🇺🇸 🇬🇧 🇦🇺🇳🇿 [23 May 2025] US, UK, Australia and New Zealand jointly release guidance on AI data security:The US National Security Agency’s Artificial Intelligence Security Center (NSA AISC), the Cybersecurity and Infrastructure Security Agency (CISA), the Federal Bureau of Investigation (FBI), the Australian Signals Directorate’s Australian Cyber Security Centre (ASD’s ACSC), New Zealand’s National Cyber Security Centre (NCSC-NZ), and the United Kingdom’s National Cyber Security Centre (NCSC-UK) have issued a joint guidance on securing data across the AI lifecycle. The guidance addresses critical risks such as data poisoning, supply chain vulnerabilities, and "data drift" (i.e. changes in the underlying statistical properties of the input data to an operational AI system whereby the input data becomes significantly different from its original state over time). The guidance provides mitigation strategies on data management, data quality testing, and input and output monitoring.
