About Metaculus

Metaculus is an online forecasting platform and aggregation engine working to improve human reasoning and coordination on topics of global importance. By bringing together an international community and keeping score for thousands of forecasters, Metaculus is able to deliver machine learning-optimized aggregate predictions that both help partners make decisions and benefit the broader public.

We Value Community

Because we are wiser together.

Collective intelligence is at the heart of Metaculus. Our community has written thousands of questions and created hundreds of thousands of forecasts. The aggregation of the predictions of many forecasters is more accurate than that of (almost) any individual.

In addition to forecasting performance, the caliber of community discourse is very high on Metaculus. Through discussion, we can all learn from each other.

For these reasons, we will always welcome forecasting questions, suggestions, ideas, and input from our forecasters. We care about their experience, and we want to keep making it better.

We Respect Knowledge & Truth

Because we want a shared reality.

In order to cooperate with each other, humans need ways of arriving at a consensus about what is true, what is real, how we know what we know, and how to measure things we care about.

Science is the most successful system in history at enabling large numbers of people to coordinate in creating knowledge.

In an increasingly fragmented, post-truth societal landscape, Metaculus is a place where shared knowledge can be built and tracked over time, and where shared truth can be arrived at through transparent, accountable processes. Just like in a scientific experiment, each forecast expresses a modeled future state, and the resolution criteria is specified ahead of time in order to understand its validity.

Because we want to create the best knowledge in the world about the future, we focus on optimizing forecasting performance (in terms of accuracy, calibration, and foresight).

We Create Public Accountability & Trust

Because we want sensible public discourse, and trustworthy leadership.

We share the Metaculus track record publicly, so that the world can hold us accountable for our forecasts. We will always enable and promote public track records for individual forecasters who participate on our platform, so that reliable forecasters can be identified.

We work to better understand all the dimensions of forecasting science in order to improve the performance, accountability, and trustworthiness of our system.

Accountability is also important for forecasters who want to ameliorate their skills. Feedback in the form of scoring rules, points and related means of performance analysis are accountability mechanisms that enable forecasters to improve over time.

We Build for Transparency & Understanding

Because we want our audiences to be able to interpret our results.

Unlike AI systems that don’t explain how they arrive at answers, it’s important that Metaculus outputs are transparent. Our rules and incentive systems should be understandable to all our participants.

We Build Tools for Collaborative Systems Thinking

Because complexity is increasing, and we need new ways to make sense of the world.

Collective intelligence can help solve complex problems. “Classic” science works in controlled environments. Simulations, machine learning, and data science have given us new tools that work, but only with the right data and causal models.

For everything else – truly complex systems – Metaculus provides the infrastructure for collaboratively modeling, testing, understanding, and determining the right interventions in the real world.

Our goal is to build tools for collaborative systems thinking, fueled by an open and accountable ethos and a collaborative forecasting community.

Team

Gaia Dempsey

Gaia Dempsey

CEO
Tom Liptay

Tom Liptay

Program & Operations Director
Nate Morrison

Nate Morrison

Chief of Staff
Dan Schwarz

Dan Schwarz

Chief Technology Officer
Anastasia Miliano

Anastasia Miliano

Director of Special Projects
Alex Leader

Alex Leader

Forecasting Program Director
Atakan Seçkin

Atakan Seçkin

Head of Design
Peter Mühlbacher

Peter Mühlbacher

Research Scientist
Ioana Bitoiu

Ioana Bitoiu

Product Designer
Peter Scoblic

Peter Scoblic

Director of Nuclear Risk
Kirill Yakunin

Kirill Yakunin

Machine Learning Engineer
Christian Williams

Christian Williams

Director of Communications & Data
Sylvain Chevalier

Sylvain Chevalier

Technical Product Manager
Lawrence Phillips

Lawrence Phillips

AI Forecasting Lead
Martin Račák

Martin Račák

Software Engineer
Ryan Beck

Ryan Beck

Forecasting Program Coordinator
Juan Cambeiro

Juan Cambeiro

Biosciences Analyst
Rudolf Ordoyne

Rudolf Ordoyne

Forecasting Analyst
Nikos Bosse

Nikos Bosse

Research Coordinator
Gustavo Lacerda

Gustavo Lacerda

Quantitative Research Analyst

Advisors

Tamay Besiroglu

Tamay Besiroglu

Welton Chang

Welton Chang

Burak Nehbit

Burak Nehbit

Steven Schkolne

Steven Schkolne

Board

Anthony Aguirre

Anthony Aguirre

Founder & Chairman of the Board (Prof. of Physics, UCSC; PhD 2000, Harvard)

Greg Laughlin

Greg Laughlin

Founder & R&D Fellow (Prof. of Astronomy, Yale; PhD 1994, UCSC)
Max Wainwright

Carroll “Max” Wainwright

Founder & AI Advisor (AI Researcher & Data Scientist, PhD 2013, UCSC)
David Levine

David Levine

Founder
Gaia Dempsey

Gaia Dempsey

CEO