Coaching practices for Expected Utility
Describe almost anything you are working through and IX Coach finds the practices whose real-world fit is closest. For Expected Utility, these are the strongest matches in the current practice library.
Does this sound like the set of challenges you might be facing?
- The math says this bet is worth taking, but if it goes wrong the loss would genuinely wreck me
- This is a one-way door
- There’s a chance in front of me where the worst case is small and survivable
- I make these probability guesses in my head
- I keep playing out this decision in my head as if there’s just one way it goes
Practices that may help
- Adjust raw expected value for risk aversion on large stakes
A 50% chance of losing everything is not equivalent to a certain 50% loss — adjust for your actual risk tolerance.
Expected Value Thinking: Deciding Under Uncertainty - Expected Value Thinking: Deciding Under Uncertainty
Expected value thinking multiplies each possible outcome by its probability and sums the results, giving a single number that represents the average payoff of a decision. It is the mathematical foundation of rational decision-making under uncertainty — well grounded in decision theory — but it has real limits: probabilities are often uncertain, outcomes are not always quantifiable, and raw expected value ignores risk aversion that can be legitimate. - Use maximin reasoning for high-stakes, irreversible decisions under ambiguity
Choose the option whose worst plausible outcome is most survivable — when you can’t compute expected value, optimize the floor.
Ambiguity Aversion — Why Unknown Odds Feel Worse Than Bad Odds - Look for decisions with asymmetric upside — large potential gain, small defined loss
Seek situations where the worst case is bounded and small while the best case is large and open-ended.
Expected Value Thinking: Deciding Under Uncertainty - Keep a decision journal to score your EV estimates
Log your probability estimates and payoff predictions, then compare them to what happened.
Expected Value Thinking: Deciding Under Uncertainty - Enumerate scenarios and their probabilities before deciding
Write down each meaningful outcome, assign a probability, and compute the weighted total.
Expected Value Thinking: Deciding Under Uncertainty - Accept positive-EV decisions even when they feel uncomfortable
If the expected value is clearly positive, take the decision — even if most individual outcomes are losses.
Expected Value Thinking: Deciding Under Uncertainty - Ambiguity Aversion — Why Unknown Odds Feel Worse Than Bad Odds
Ambiguity aversion, demonstrated by Daniel Ellsberg's 1961 paradox, is the tendency to prefer bets with known probabilities over bets with unknown probabilities — even when expected value is identical or the unknown option may be better. It is driven by discomfort with Knightian uncertainty and systematically steers people away from unfamiliar but potentially high-value opportunities. - Calculate the expected value of gathering more information
Before researching further, ask whether the additional information is actually worth the cost to obtain.
Expected Value Thinking: Deciding Under Uncertainty - Check whether you’re demanding an unfair ambiguity premium
Estimate what you’d accept under comparable known-odds risk — if your bar is much higher for unknown odds, that gap is the bias.
Ambiguity Aversion — Why Unknown Odds Feel Worse Than Bad Odds
Related concerns
- Expected Value Calculation
Expected value thinking multiplies each possible outcome by its probability and sums the results, giving a single number that represents the average payoff of a decision. It is the mathematical foundation of rational decision-making under uncertainty — well grounded in decision theory — but it has real limits: probabilities are often uncertain, outcomes are not always quantifiable, and raw expected value ignores risk aversion that can be legitimate.
- Expected Value Explained
Expected value thinking multiplies each possible outcome by its probability and sums the results, giving a single number that represents the average payoff of a decision. It is the mathematical foundation of rational decision-making under uncertainty — well grounded in decision theory — but it has real limits: probabilities are often uncertain, outcomes are not always quantifiable, and raw expected value ignores risk aversion that can be legitimate.
- Expected Value Thinking Deciding Under Uncertainty For My Teenager
Expected value thinking multiplies each possible outcome by its probability and sums the results, giving a single number that represents the average payoff of a decision. It is the mathematical foundation of rational decision-making under uncertainty — well grounded in decision theory — but it has real limits: probabilities are often uncertain, outcomes are not always quantifiable, and raw expected value ignores risk aversion that can be legitimate.
- Expected Value Thinking Deciding Under Uncertainty On A Budget
Expected value thinking multiplies each possible outcome by its probability and sums the results, giving a single number that represents the average payoff of a decision. It is the mathematical foundation of rational decision-making under uncertainty — well grounded in decision theory — but it has real limits: probabilities are often uncertain, outcomes are not always quantifiable, and raw expected value ignores risk aversion that can be legitimate.
- Expected Value Thinking Deciding Under Uncertainty When Burned Out
Expected value thinking multiplies each possible outcome by its probability and sums the results, giving a single number that represents the average payoff of a decision. It is the mathematical foundation of rational decision-making under uncertainty — well grounded in decision theory — but it has real limits: probabilities are often uncertain, outcomes are not always quantifiable, and raw expected value ignores risk aversion that can be legitimate.
- Expected Value Thinking Deciding Under Uncertainty After A Loss
Expected value thinking multiplies each possible outcome by its probability and sums the results, giving a single number that represents the average payoff of a decision. It is the mathematical foundation of rational decision-making under uncertainty — well grounded in decision theory — but it has real limits: probabilities are often uncertain, outcomes are not always quantifiable, and raw expected value ignores risk aversion that can be legitimate.
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