FORAXION TIMESNOVEMBER 2026

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Results for “collective intelligence”

2023-05-02The Forecasting Machine

Hypermind’s three tasks for collective intelligence

A May 2023 House Of Codesign webinar announcement connected Hypermind’s collective forecasting, intelligent brainstorming and business decision tools.

2023-03-24The Forecasting Machine

STORM and the energy-sobriety challenge

Hypermind, EDF and La Poste’s 2022–2023 energy-sobriety initiative used employee ideas and collective prioritisation to shape practical organisational plans.

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.

2023-02-23The Forecasting Machine

When ChatGPT invented a biography: an early argument for accountable forecasts

In January and February 2023, Émile Servan-Schreiber contrasted a fabricated ChatGPT biography with Hypermind’s scored probability record. The comparison was about evidence as much as intelligence.

2023-01-30The Forecasting Machine

L’Éléphant’s Hypermind clipping prompts a reflection on a life’s work

The recovered clipping is a short account of Hypermind’s origins and forecasting contests. Servan-Schreiber’s response turns its heading, L’anecdote, into a reflection on research.

2023-01-17The Forecasting Machine

An 84-minute conversation, then AI-selected clips: Software in Blue on collective intelligence

Steve Mayzak and Chad Tindel’s interview with Émile Servan-Schreiber connected collective intelligence to business forecasting. Two months later, the show used Dubb to select excerpts about cognition and crowd size.

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.

2022-07-13The Forecasting Machine

Collective intelligence at work: talks and workshops, 2019–2022

Archive notes trace collective-intelligence talks and workshops from coaching and corporate IT to HR, private equity and Leads France between 2019 and 2022.

2022-07-03The Forecasting Machine

Khiplace and Hypermind pool investor judgement on emerging risks

A June 2022 inaugural meeting and a July risk-prioritisation invitation show how Khiplace and Hypermind sought to combine investors’ knowledge. No ranked results survive here.

2022-06-28The Forecasting Machine

At Arthur D. Little’s Faro meeting, diversity enters the collective-intelligence equation

At Arthur D. Little’s 2022 partners meeting in Faro, Émile Servan-Schreiber connected diversity with methods for combining a group’s contributions.

2022-06-02The Forecasting Machine

Learning collective intelligence through student experiments at UM6P

Student surveys, an online social-sensitivity test and a forecaster’s account of reinvesting his winnings show how collective intelligence was taught through practice.

2022-05-13The Forecasting Machine

Edvance uses Hypermind STORM to surface nuclear-safety priorities and disagreements

A May 2022 participant account describes an Edvance exercise moving from employee ideas to voting, with disagreements made visible alongside priorities.

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