count me as curious too!

Useful to measure scientific impact on log scales but not cognitive ability, which is roughly normally distributed and can arguably only be measured on ordinal scales. Makes zero sense to say Einstein was 10X smarter than Bohr.

Handle with care: A powerful justification for procrastination

Really enjoyed working on this with Philipp Schoenegger Philip E. Tetlock and Barbara Mellers. We tried ~50 prompt techniques (including AI classics and more theory-motivated ones) on 100 forecasting questions across 6 LLMs. No prompt showed robust improvements! arxiv.org/abs/2506.01578

a great gist packs as much insight into as few words as possible. This is one of the greatest!

Taboo trade-offs are sources of endless mischief: An inexhaustible supply of sand to throw into the logical machinery of cost-benefit analysis dropbox.com/scl/fi/filekmh…

Hindsight bias fuels forecaster over-confidence. The cure: Remind & re-remind yourself of the deeply incorrect beliefs you once held about the future before you came to hold your current clearly correct beliefs about the future

Reasonable complaint

Social scientists today do their work in silos, surrounded only by those who share their assumptions and intuitions. Adversarial collaborations, therefore, may play a key role in stimulating our collective creativity and scientific innovation. New in Theory and Society:

Solid advice if you are Patrick Collison (or just a top-2% “superforecaster”). But a bad bet for the rest of us. Most of the time, the average judgment of the crowd beats the judgment of individual members of that same crowd. Not inspirational but demonstrably true.

Our new study finds: recent AI capabilities could increase the risk of a human-caused epidemic by 2-5x, according to 46 biosecurity experts and 22 top forecasters. One critical AI threshold that most experts said wouldn't be hit until 2030 was actually crossed in early 2025. But

Authors: Bridget Williams, Josh Rosenberg, Luca Righetti, Rebecca Ceppas de Castro, Otto Kuusela, Rhiannon Britt, Seth Donoughe, Alvaro Morales, Emily Soice, Jon Sanders, James Black and Philip E. Tetlock Special acknowledgment to SecureBio for the virology evaluation collaboration.

This summary covers the key findings — the full study includes detailed methodology, participant rationales, accuracy measures, and policy implications. Read the complete report from Forecasting Research Institute: forecastingresearch.org/ai-enabled-bio…

FRI found that superforecasters and bio experts dramatically underestimated AI progress in virology: they often predicted it would take 5-10 years for AI to match experts on a benchmark for troubleshooting virology (VCT), but actually AIs had already reached this level.

Have you ever wondered how far off we are from a world in which, say, biochemistry undergrads can—with AI guidance – “cook up” new lethal subtypes of influenza in virology labs? The FRI study below lays out promising methodology for answering such questions—& the answer is we’re

Ideological immune systems in overdrive. Cory Clark documents the lengths to which some will go to minimize cognitive dissonance

Great to see our report on LLM-enabled biorisk covered in the latest issue of The Economist

Reminds me of the more disdainful reactions in the intelligence community to superforecasters— and pitting them against professional analysts in prediction tournaments

Sitting on top of all that money, Bitcoiners could have sprung for better advice on personality tests. The MBTI?