Gambler's Fallacy
We believe that past random events affect the likelihood of future random events.
The gambler's fallacy (also known as the Monte Carlo fallacy or the fallacy of the maturity of chances) is the incorrect belief that, if a particular event occurs more frequently than normal during the past, it is less likely to happen in the future (or vice versa), when it has otherwise been established that the probability of such events does not depend on what has happened in the past. This is a fundamental misunderstanding of statistical independence.
What it looks like in the wild.
- Everyday life Roulette Red-Black After roulette lands on red 10 times in a row, gamblers believe black is 'due' — each spin is statistically independent.
- Everyday life Baby Gender Prediction Parents of three boys think their fourth child is more likely to be a girl; the probability remains 50%.
Someone has already built a business on this.
Biases are not only private errors. They are design targets — patterns deliberately engineered into interfaces because they reliably work.
- Games Near-Miss Engineering Slot machines are programmed to show near-misses (two of three symbols matching) more than probability would dictate, exploiting the gambler's fallacy to encourage continued play.
Recognising a definition is not the same skill as spotting it.
Two scenarios from the app, with distractors drawn from the same family of biases — which is what makes them hard.
Rachel's team has scored in the last three soccer games. She tells a teammate, 'The other team is definitely going to score first next game.'
Having just survived two near-miss accidents on the highway, Olivia continues driving recklessly, feeling her luck has been used up.
Biases rarely arrive alone.
Understand more. Assume less.
188 biases, 18,869 scenarios, and a record of how you actually decide.
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