Big Brains
Can We Predict The Unpredictable? with J. Doyne Farmer
Nov 14, 2024
J. Doyne Farmer, a complexity scientist and professor at Oxford, once outsmarted casinos with his scientific insights. He dives into the intriguing idea of predicting economies like weather patterns, using chaos theory and big data. Farmer discusses the potential of agent-based modeling to revolutionize economic forecasting and addresses the challenges of understanding complex systems. He also highlights how complexity economics could reshape public policy, tackle climate issues, and pave the way for sustainable growth in our unpredictable world.
33:14
Episode guests
AI Summary
AI Chapters
Episode notes
Podcast summary created with Snipd AI
Quick takeaways
- The podcast discusses how complexity economics utilizes big data and chaos theory to forecast unpredictable economic events and policies.
- Agent-based modeling allows economists to simulate real-world decision-making by incorporating human behavior, improving predictions for economic fluctuations.
Deep dives
Predicting Human Actions and Economic Implications
The discussion centers on the potential of utilizing data to predict human behavior and economic outcomes, akin to the concept presented in the film 'Minority Report.' It explores the possibility of forecasting unpredictable events, such as stock market fluctuations and various economic scenarios, through a systematic analysis of past data. This predictive approach could help gauge the consequences of actions like tax increases on wealth distribution and the impacts of inflation. By applying similar principles used in crime prevention, economists aim to enhance their understanding of complex economic phenomena.
Remember Everything You Learn from Podcasts
Save insights instantly, chat with episodes, and build lasting knowledge - all powered by AI.
