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AI evals: Due
Over the past few years, we’ve seen hints of policymakers and national leaders using AI models in their actual policy decision-making. The Prime Minister of Sweden said he uses it for second opinions on policy; the German Chancellor is testing it to draft legislation; even Trump said he had it re-write a speech at some point. It’s fair to assume that senior leadership across the world, and in Washington as well, have started using AI not just for tactical or operational tasks, but increasingly for broad strategic decision-making.
While that’s exciting — there’s the promise of uplift and smarter calls on some of the most consequential decisions leaders face in foreign policy and national security — we’re also flying blind. Enormous effort and energy goes into benchmarking and evaluation for things like coding. The experiments you can run to make models better at software development are much easier to execute and much lower-stakes than running a real experiment when you’re deciding whether to invade a country or sign a treaty.
That’s why we at ChinaTalk are trying to kickstart a field aimed at helping researchers and policymakers understand exactly what they’re working with when they ask these models to support some of the most consequential decisions they may make in their lifetimes. We’re launching an evals/essay project contest to explore this theme.
I’ve brought on two expert AI eval creators to discuss why the field is important, what interesting work has already been done on how models approach broad national-security and strategic questions, and how you — as an eval professional, semi-professional, or just a concerned person — can contribute new ways to poke and prod at these models and see what they can really do.
Joining us today: Florian Brand, research engineer at Prime Intellect, and John Chen, professor at the University of Arizona, who’s done some pretty wild things getting models to start nuclear wars with each other in Civ V.
Our conversation covers:
How frontier labs are hitting eval-building limits — they’ve gone from undergrads to PhDs to field experts, and the models are now catching the experts’ mistakes.
How Civilization V exposes AI’s strategic blind spots (terrible second-order reasoning) and models’ distinct strategic personalities (Claude’s really into science!).
Why ethical prompting in Civilization V still doesn’t stop models from launching nukes.
Jordan's PresidentBench eval, where a Chinese model was nonchalant about a Taiwan invasion, while Claude wanted to keep Taiwan free and independent.
Advice for designing better AI evals and ChinaTalk’s new essay/evals contest!
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