My goal is to do work that counterfactually reduces AI risk from loss-of-control scenarios. My perspective is shaped by my experience as the founder of a VC-backed AI startup, which gave me a firsthand understanding of the urgent need for safety.
I have a B.S. in Artificial Intelligence from Carnegie Mellon and am currently a CBAI Fellow at MIT/Harvard. My primary project is ForecastLabs, where I’m building predictive maps of the AI landscape to improve strategic foresight.
I subscribe to Crocker’s Rules and am especially interested to hear unsolicited constructive criticism. http://sl4.org/crocker.html—inspired by Daniel Kokotajlo.
(xkcd meme)
Thanks for the great post. As someone who builds these kinds of bots, I find this really interesting.
One thought: I think the way we prompt and guide these AI models makes a huge difference in their forecasting accuracy. We’re still very new to figuring out the best techniques, so there’s a lot of room for improvement there.
Because of that, the performance on benchmarks like ForecastBench might not show the full picture. Better scaffolds could unlock big gains quickly, so I lean toward an earlier date for AI reaching the level of top human forecasters.
That’s why I’m paying closer attention to the Metaculus tournaments. They feel like a better test of what a well-guided AI can actually do.