News from the frontier of AI forecasting
FORAXION, the company behind The Forecasting Machine, pushes the limits of actionable foresight.
Results for “Research”
A 2017 field guide to prediction markets for foresight, reread in 2026
Futuribles International has made Émile Servan-Schreiber’s 14-page toolbox on prediction markets free to download. Written in 2017 for foresight practitioners, its practical rules still hold, and its list of research frontiers reads differently now that AI forecasting exists.
Crowds versus language models: the more accurate the AI forecaster, the more it errs like humans
A Philosophical Transactions B paper co-authored by Émile Servan-Schreiber compares 76 language-model setups with human crowds on 580 ForecastBench questions and finds evidence for the accuracy–correlation effect.
Superforecasting at ten, and the “proven forecasters” NewsFutures spotted in 2006
Ten years after Tetlock and Gardner’s Superforecasting, Émile Servan-Schreiber dug out a 2006 NewsFutures market in which the previous quarter’s best forecasters beat the crowd. Why the idea took a decade to be recognised, and where AI fits now.
Do prediction markets reward the lone right answer? Servan-Schreiber’s reply to a PNAS model of collective intelligence
A 2017 PNAS model found that “market rewards” make crowds herd and proposed paying accurate minorities instead. Émile Servan-Schreiber argues that real prediction markets already pay that way.
