Manifold Markets Founder - Predictions Markets & Revolutionizing Governance

ℹ️ EPISODE INFO

Released

May 5, 2022

Duration

50m

Channel

Dwarkesh Podcast

Watch on YouTube

▶ Open ↗

📝 EPISODE DESCRIPTION

Stephen Grugett is a cofounder of Manifold Markets, where anyone can create a prediction market. We discuss how prediction markets can change how countries and companies make important decisions. Manifold Markets: https://manifold.markets/ Podcast website + Transcript: https://www.dwarkeshpatel.com/p/stephen-grugett Apple Podcasts: https://apple.co/3cDjwBF Spotify: https://spoti.fi/3RkZD12 Follow me on Twitter to be notified of future content: https://twitter.com/dwarkesh_sp TIMESTAMPS: Introduction 0:00:00 Predicting the future 0:02:29 Getting Accurate Information 0:05:16 Potentials 0:06:20 Not using internal prediction markets 0:09:29 Doing the painful thing 0:11:04 Decision Making Process 0:13:31 Grugett’s opinion about insider trading 0:14:52 The Role of prediction markets 0:16:23 Dealing with the Speculators 0:18:17 Criticism of Prediction Markets 0:20:33 The world when people cared about 0:22:24 Grugett’s Profile Background/Experience 0:26:10 User Result Market 0:28:49 The most important mechanism 0:30:17 The 100 manifold dollars 0:32:59 Efficient financial markets 0:40:30 Manifold Markets Job/Career Openings 0:46:28 Objectives of Manifold Markets 0:48:02

🎤 SPEAKERS

• Dwarkesh Patel

  host

• Narrator

  other

• Stephen Grugett

  guest

🧾 EPISODE SUMMARY

In this episode of Dwarkesh Podcast, featuring Dwarkesh Patel and Narrator, Manifold Markets Founder - Predictions Markets & Revolutionizing Governance explores manifold Markets: Play-Money Prediction Markets To Reshape Information And Governance The conversation explores Manifold Markets, a play‑money platform for user-created prediction markets designed to aggregate information and surface highly calibrated forecasters. Founder Stephen Griggott explains why status, competition, and reputation can motivate serious participation even without real-money trading, and how user-resolved markets make the system scalable despite some risk of fraud. They discuss why internal corporate prediction markets rarely survive, how prediction markets might inform journalism, governance, and AI risk debates, and why usability and simplicity have blocked earlier widespread adoption. The episode closes with Manifold’s internal use of markets for company decisions, emergent user behaviors, and the team’s hiring and long‑term vision for prediction markets embedded across media and institutions.

🔗 RELATED EPISODES

General relativity from first principles – Adam Brown

Grant Sanderson (@3blue1brown) – AI disproved a famous math conjecture. Now what?

@Asianometry & Dylan Patel — How the semiconductor industry actually works

Ilya Sutskever (OpenAI Chief Scientist) — Why next-token prediction could surpass human intelligence

Daniel Yergin — Oil destroyed Hitler, fracking destroyed Putin

Lars Doucet — Progress, poverty, Georgism, & why rent is too damn high