Today we’re launching the most rigorous, ongoing source of expert forecasts on the future of AI: the Longitudinal Expert AI Panel (LEAP). 339 top experts across AI, CS, economics, and policy will forecast AI’s trajectory monthly for 3 years. 🧵👇

Is AI on track to match top human forecasters at predicting the future? Today, FRI is releasing an update to ForecastBench—our benchmark that tracks how accurate large language models (LLMs) are at forecasting real-world events. Here’s what you need to know: 🧵

🎙️ Our CEO, Josh Rosenberg, went on @deneufville.bsky.social's podcast podcast, Talking About The Future. They discussed LLM biorisks, AI forecasters, how to make forecasting more useful to policy makers and much more. Listen here: tellingthefuture.substack.com/p/josh-rosen...

In 2022, we convened 169 experts and superforecasters for the Existential Risk Persuasion Tournament (XPT). We collected thousands of forecasts in 172 questions across time horizons. We now have answers for 38 questions covering AI, climate tech, bioweapons and more. Here’s what we found out: 🧵

Great to see our report on LLM-enabled biorisk covered in the latest issue of The Economist: www.economist.com/briefing/202...

Our new study finds: recent AI capabilities could increase the risk of a human-caused epidemic by 2-5x. One AI threshold that most experts said wouldn't be hit until 2030 was actually crossed in early 2025. But forecasters predict that enacting mitigations could reduce risk close to baseline. 🧵