More accurately predicting the future | Philip Tetlock

Philip Tetlock investigates counterfactual reasoning through a *Civilization V* forecasting tournament that prohibits machine learning to simulate the constraints faced by real-world intelligence analysts. His research demonstrates that while simple algorithms outperform humans in data-rich domains, "superforecasters" achieve higher accuracy in ambiguous geopolitical scenarios by maintaining a "perpetual beta" mindset and distinguishing between 10 to 15 degrees of uncertainty. Despite these advances, Tetlock notes that predictive advantages diminish beyond five to ten years due to historical chaos, yet the adoption of quantified forecasting methods continues to challenge institutional status hierarchies and improve decision-making accuracy.