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This is a research prototype. The data and analyses are preliminary and not yet validated — we'd welcome your .

About the AI Risk Navigator

A project of the MIT AI Risk Initiative and MIT FutureTech, the Navigator connects AIRI's datasets through a shared risk taxonomy to make cross-cutting analysis and search accessible.

This is a research prototype. The Navigator is under active development, and the data and analyses shown here are preliminary and have not been fully validated. Figures may change or contain inaccuracies, so please verify against the original AIRI datasets before citing or relying on any specific numbers. We're sharing it at this stage to gather feedback — you can share yours via the feedback form.

Motivation

AIRI has built some of the most comprehensive datasets on AI risk. But until now, these datasets existed in isolation. A researcher who wanted to know whether governance attention matched expert concern, or whether the risks most frequently studied in the literature were the same ones causing real-world harm, would have had to manually cross-reference across separate Airtable interfaces and published papers.

The Navigator was built to close that gap. By using the risk domain taxonomy as a central navigation point and providing easy-to-use search interfaces, it makes the kind of detail-oriented, integrative, and cross-cutting questions that motivated AIRI's research program possible to ask — and to answer — in one place.

How to Use This Tool

The Navigator offers several ways to explore AI risk data, depending on what you're looking for.

Resources

Built with React and Next.js. Frontend design uses Tailwind CSS and shadcn/ui. Visualizations use Nivo and Recharts. Search functionality is hosted on Upstash, and the site is deployed on Vercel. We use PostHog for analytics.

The Navigator is v1.3.1, released June 3, 2026. Data was last updated May 26, 2026. The site is under active development.

Acknowledgements

The AI Risk Navigator was built by me, Spencer Michaels, during a Spring 2026 research fellowship at the Cambridge Boston Alignment Initiative.

Creating this website would not have been possible without the support and guidance of my mentors, Alexander Saeri and Peter Slattery. A huge thank you also goes to my research manager, Emre Yavuz, and my collaborators at AIRI, Simon Mylius, Ben Olsen, and Victoria Snorovikhina.

Finally, thank you to all of my CBAI friends (especially the Dana St residents) for making breaks, weekends, and the entire CBAI fellowship such an incredible time.

The datasets that power this tool represent years of research by the AIRI team and its collaborators. Any errors in their presentation here are my own.

— Spencer

Questions, feedback, or ideas for collaboration? Contact me at spenmich [at] mit [dot] edu, or fill out the feedback form.