Forecasting the things that matter (with Peter Wildeford)

Read the full transcript here.

How can we change the way we think about expertise (or the trustworthiness of any information source) using forecasting? How do prediction markets work? How can we use prediction markets in our everyday lives? Are prediction markets more trustworthy than large or respectable news outlets? How long does it take to sharpen one's prediction skills? In (e.g.) presidential elections, we know that the winner will be one person from a very small list of people; but how can we reasonably make predictions in cases where the outcomes aren't obviously multiple-choice (e.g., predicting when artificial general intelligence will be created)? How can we move from the world we have now to a world in which people think more quantitatively and make much better predictions? What scoring rules should we use to keep track of our predictions and update accordingly?

Peter Wildeford is the co-CEO of Rethink Priorities, where he aims to scalably employ a large number of well-qualified researchers to work on the world's most important problems. Prior to running Rethink Priorities, he was a data scientist in industry for five years at DataRobot, Avant, Clearcover, and other companies. He is also recognized as a Top 50 Forecaster on Metaculus (international forecasting competition) and has a Triple Master Rank on Kaggle (international data science competition) with top 1% performance in five different competitions. Follow him on Twitter at @peterwildeford.

Further reading

ClearerThinking.org's "Calibrate Your Judgment" practice program
Metaculus (forecasting platform)
Manifold Markets
Polymarket
"Calibration Scoring Rules for Practical Prediction Training", a paper by Spencer Greenberg

Staff

Spencer Greenberg — Host / Director
Josh Castle — Producer
Ryan Kessler — Audio Engineer
Uri Bram — Factotum
Janaisa Baril — Transcriptionist

Music

Affiliates

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