Risk vs Uncertainty: What People Confuse
Risk has known probabilities; uncertainty doesn't. With risk you can calculate odds, with uncertainty you can't even assign probabilities to outcomes.
March 2026
June 2025
Origins of Decision Theory
Decision theory origins: Bernoulli introduced expected utility in 1738. Von Neumann and Morgenstern developed game theory and axioms of rationality in 1944.
Using Decision Theory in Everyday Choices
Apply decision theory: list all options, define outcomes for each, assign probabilities to outcomes, calculate expected values, then choose highest value.
December 2024
The Representativeness Heuristic: Why We Judge by Resemblance and Pay the Price
Linda is 31, outspoken, a philosophy major, passionate about social justice. Is she more likely to be a bank teller, or a bank teller active in the feminist movement? 85-90% of people choose the conjunction — which is mathematically impossible. Kahneman and Tversky called this the representativeness heuristic: we judge probability by resemblance, and resemblance ignores base rates.
November 2024
The Gambler's Fallacy: Why the Mind Insists the Universe Keeps Score
On August 18, 1913, a Monte Carlo roulette wheel hit black 26 consecutive times. Gamblers lost millions betting on red, certain it was 'due.' The wheel had no memory. Neither does a coin, a die, or any independent random event — yet the human brain insists otherwise. The science behind why we see debt in probability and what it costs us.
November 2022
How to Think About Risk: A Practical Framework
A practical framework for thinking about risk: expected value vs utility, availability heuristic, tail risks, diversification, and the Kelly criterion explained clearly.
August 2022
What Is the Monte Carlo Method: How Randomness Solves Hard Problems
The Monte Carlo method uses random sampling to solve problems too complex for direct calculation. Learn its origins, how it works, and its applications in business and science.