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2025-09-30The Forecasting Machine

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.

2025-09-16The Forecasting Machine

The Forecasting Machine opens to the public after 18 months of research

On 16 September 2025, The Forecasting Machine came out of closed beta: an AI platform that reads global news, runs an ensemble of language models and turns open questions into updated probabilities.

2025-05-20The Forecasting Machine

AI gathers, crowds guess: Servan-Schreiber’s hybrid forecasting model in Prague

At the Europe as a Task conference in Prague in May 2025, Émile Servan-Schreiber split forecasting into information gathering, where AI now leads, and guessing, where crowds still take better-calculated risks.

2025-03-19The Forecasting Machine

How humans and an early forecasting AI saw 2030: the OECD's Hypermind pilot

An OECD foresight exercise compared aggregate human forecasts with an early LLM-based system across 25 possible AI benefits and risks to 2030—and emphasized the limits of both.

2025-01-20The Forecasting Machine

Glimt opens to the public: Sweden’s crowd-forecasting platform for Ukraine

On 20 January 2025, FOI opened Glimt, a free platform where volunteers forecast the war, politics and economy questions that Ukrainian analysts worry about, using Hypermind’s technology. Within five weeks it had more than 10,000 forecasters.

2024-10-19The Forecasting Machine

Red bars and blue bars: how betting markets and forecaster panels split over Harris and Trump

In the final weeks of the 2024 US election, Émile Servan-Schreiber tracked eleven forecasting venues. Real-money markets leaned Trump, forecaster panels leaned Harris, and the result reopened an old argument about what money adds to a forecast.

2024-09-18The Forecasting Machine

AI versus the crowd: Hypermind’s hybrid forecast map of the 2024 US presidential election

In September 2024 Hypermind set its new retrieval-augmented AI Forecasting Machine against its human prediction market on a state-by-state election map. How the experiment worked, what it forecast, and what the result can and cannot tell us.

2023-09-20The Forecasting Machine

“Governing is predicting”: crowd forecasting at the Brussels Democracy Lab

At a Democracy Lab on smarter crowdsourcing in Brussels on 19 September 2023, Émile Servan-Schreiber gave EU policymakers five reasons to use crowd forecasting, starting with the idea that governing is predicting.

2023-02-24The Forecasting Machine

Hypermind’s Ukraine war forecasts, 2022–2023: what the crowd got right and wrong

On the war’s first anniversary, Émile Servan-Schreiber published Hypermind’s forecasts for its second year. A look back at the crowd’s record since January 2022: an invasion it rated as possible but not likely, a serious early misjudgment about Zelensky, and a run of calls that held up.

2022-10-21The Forecasting Machine

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.

2022-07-11The Forecasting Machine

“Arising Intelligence”: what Hypermind’s crowd got right and wrong about AI progress

From 2021, Hypermind ran contests asking forecasters to predict AI benchmarks with Jacob Steinhardt of UC Berkeley. Progress on maths and language beat the crowd’s expectations; robustness lagged them.

2022-05-02The Forecasting Machine

Bettors versus pollsters: the Hypermind–Le Point panel and the 2022 Macron–Le Pen run-off

Across 143 daily rolling polls of the 2022 French presidential run-off, the Hypermind–Le Point panel’s forecast was closer to the final result in 128 cases. What was compared, how the panel worked, and where the comparison has limits.

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