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The Forecasting Machine Partners With Institut Montaigne on France’s 2027 Policy Choices
Institut Montaigne’s Les repères de Montaigne programme will use The Forecasting Machine’s probabilities to examine priority government actions after the 2027 election. The contribution belongs to the forthcoming 25th note, on the opening months of the next term.
Turning Signals Into Decisions: The Forecasting Machine at the OECD GFC Annual Meeting 2026
After two days at the OECD Government Foresight Community’s 2026 annual meeting, Gilles Haumont argued that foresight needs a faster route into institutional decisions. His account also points to the OECD’s existing use of The Forecasting Machine, alongside an earlier record of forecasting experiments and presentations.
Which 2027 Candidate Will Talk Digital Best? The Forecasting Machine’s First Campaign Forecasts on POL/N
On Delphine Sabattier’s POL/N podcast, Émile Servan-Schreiber presented The Forecasting Machine’s first forecasts on digital issues in France’s 2027 presidential race, from AI’s likely effect on the vote to Europe’s best chance of a real technology race, and debated them with Bernard Benhamou of the Institut de la souveraineté numérique.
Four lessons from 25 years of crowd forecasting: Servan-Schreiber at the Lürssen Foundation workshop
At a workshop convened by MIT’s Dražen Prelec in Rijeka on 1–2 October 2026, Émile Servan-Schreiber was scheduled to present four lessons on money, Brier scores, the Bayesian Truth Serum and AI forecasting.
Polls, Prediction Markets or AI? Servan-Schreiber and Verian’s Laure Salvaing on Reading France’s 2027 Election
In an Atlantico cross-interview, Émile Servan-Schreiber and pollster Laure Salvaing disagreed on what prediction markets measure and whether AI-simulated voters can replace real ones. A B SMART interview the same month added his view that, for forecasting at scale, AI has already won.
“Those markets are killed forever”: Servan-Schreiber on insider trading and the truth-machine problem
In an interview with Compliance+More on 15 September 2026, Émile Servan-Schreiber argued that suspected insider trading damages the product itself, not just compliance. It drives informed traders out of real-money prediction markets, and play money removes the incentive to rig outcomes.
Teaching students to forecast: Servan-Schreiber’s seminar at IE University and his class in the UM6P Executive MBA
A new run of “How to predict the future with collective and artificial intelligence” began at IE University on 14 September 2026, with students learning by forecasting in live prediction tournaments.
“Prediction People”: Servan-Schreiber on why money builds the business but not the forecast
In Stuart Crowley’s “Prediction People” interview, published on 24 August 2026, Émile Servan-Schreiber separated the forecasting mechanism from the business model. He also talked about forecasters who have kept playing for 25 years, AI competing with his own product, and why governments should use crowd forecasts.
“Performance = Expertise + Diversity”: Servan-Schreiber on the If This Then Dev Podcast
In an hour-long episode of the French developer podcast If This Then Dev, published on 12 August 2026, Émile Servan-Schreiber explained why groups need rules to be smart, how many novices it takes to match an expert, and why he sees large language models as collective intelligence.
