This article is an excerpt from the Shortform summary of "Thinking, Fast and Slow" by Daniel Kahneman. Shortform has the world's best summaries of books you should be reading.
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What is expected utility theory? How is it used to predict human behavior? And what are its flaws?
Expected utility theory is a theory of how people make choices and take risks when they don’t know the outcome. Traditional expected utility theory asserts that people are rational agents that calculate the utility of each situation and make the optimum choice each time.
We’ll look at how expected utility theory for decision making works and cover some of its flaws.
Expected Utility Theory
How do people make decisions in the face of uncertainty? There’s a rich history spanning centuries of scientists and economists studying this question. Each major development in decision theory revealed exceptions that showed the theory’s weaknesses, then led to new, more nuanced theories.
Expected utility theory says that you’re a rational being who makes the optimum choice with the right information.
If you preferred apples to bananas, would you rather have a 10% chance of winning an apple, or 10% chance of winning a banana? Clearly you’d prefer the former.
Similarly, when taking bets, expected utility theory assumes that people calculate the expected value and choose the best option.
This is a simple, elegant theory that by and large works and is still taught in intro economics. But it failed to explain the phenomenon of risk aversion, where in some situations a lower-expected-value choice was preferred.
The Problem with Expected Utility Theory
Consider: Would you rather have an 80% chance of gaining $100 and a 20% chance to win $10, or a certain gain of $80?
The expected value of the former is greater (at $82) but most people choose the latter. This makes no sense in classic utility theory—you should be willing to take a positive expected value gamble every time.
Risk Aversion and Bernoulli’s Expected Utility Theory
To address this, in the 1700s, Bernoulli argued that 1) people dislike risk, and that 2) people evaluate gambles not based on dollar outcomes, but on their psychological values of outcomes, or their utilities.
Bernoulli then argued that utility and wealth had a logarithmic relationship. The difference in happiness between someone with $1,000 and someone with $100 was the same as $100 vs $10. On a linear scale, money has diminishing marginal utility.
This concept of logarithmic utility neatly explained a number of phenomena:
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- Why we get easily fooled when we're stressed and preoccupied
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- How to protect yourself from making bad decisions and from scam artists
