Articles Behavioural

Feminism, gambling and the fat-free

In 1974, Daniel Kahneman and Amos Tversky exposed a blatant fault in our judgement under uncertainty

When we make judgments daily, we use shorthand methods of dealing with situations, also commonly associated with being on auto-pilot. We get out of bed, brush our teeth and walk out in the morning without thinking about it because our brain has compared this day to every other day, and acted accordingly. This is functional because it conserves mental capacity for more taxing tasks. However, this way of short-cutting life does lead to some odd outcomes.

Throughout much of the 21st century, being fat or weight gain was associated with excessive fat consumption. What was the evidence? Very little. In fact, we now associate weight gain with other factors, one of which is carbohydrate consumption. But why would that assumption come about in the first place? Because a logical leap was made between fat and the fat – the link was made between the two different meanings of fat. This spread like wildfire leading ultimately to the fat-free, diet and slim labels all over the packaging. A quintessential discovery in the field of behavioural psychology was made in a similar fashion by Amos Tversky and Daniel Kahneman and is named after Tversky’s secretary at Stanford. Kahneman gave the following puzzle to his students at the University of British Columbia.


Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in anti-nuclear demonstrations.

Which is more probable?

  1. Linda is a bank teller
  2. Linda is a bank teller and is active in the feminist movement

If you find yourself in the majority of the population, then you will have picked the second option. Now do the maths.

The probability of Linda being a bank teller = X, where X < 1

The probability of Linda being a member of the feminist movement = Y, where Y < 1

X * Y < X

i.e., the probability of option 2 will always be less than the probability of option 1


In retrospect, you may be kicking yourself for ignoring basic rules of probability, but it is important to understand the rationale behind this decision. When we evaluate new events, we naturally look at the similarity between this event and one we typically associate with it. In this case, your brain has made an association between a description of a woman concerned with issues of social justice and a typical image of a member of the feminist movement. Therefore, our brain signals for the second option because it appears more representative than the first. This is known as the conjunction fallacy – when specific conditions are thought to be more probable than a single general one.

“My colleagues, they study artificial intelligence; me, I study natural stupidity.” – Amos Tversky

Another incidence of this heuristic (which simply means a mental shortcut taken for daily problem solving) is the Gambler’s fallacy – the belief that the increased occurrence in the present will lead to a decreased occurrence in future. The most notable example of this was in the Monte Carlo casino on August 18th, 1913, when the ball landed black 26 times in a row in sequential games of roulette. This bias is an example of the representativeness heuristic, whereby “people evaluate the probability of a certain event by assessing how similar it is to events they have experienced before.” In practice, this means that we expect deviations from the average to balance out in the long run. Unfortunately, this is an example of another bias, the “law of small numbers”, whereby we typically assume that small samples must be representative of the larger population. This concept also applies to investing in the stock market. Investors often liquidate their holdings after it has been rallying for a while, under the false pretence that following a rally, the position is more likely to decline.

In short, we aren’t perfectly rational beings, but at least there is a reason for it. Thousands of years ago, overanalysing a problem may well have led to an untimely death at the jaws of a lion, or even a lightning strike “statistically” unlikely to land twice in the same spot…

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