Bias 1: Causality Fallacy

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interviewIt is time to recruit an assistant. Let’s assume we know a lot of people (let’s suppose infinite) that are qualified for this job and the candidates are split equally between men and women.

Today, we are suppose to meet five candidates. What is the most probable repartition of genders for these candidates, in their order of arrival?

  1. MMMMM
  2. FFFFF
  3. MFMFF

As there is a lot of potential candidates qualified for this job, with 50% of men and women, meeting a male or a female candidate are independent events.

Therefore, the three scenarios are equally probable; however, the third scenario ”looks more” random and, intuitively, we would like this third event to be more probable than the other two.

This heuristic view results from the tendency of our brain to look for causality in totally random events. If we meet only male or female candidates, we will make various suppositions. We will think that this is because the description of the job was gender-biased or because this kind of job is becoming more female or male. In short, we will find a reason to explain a series of events whose only explanation is chance.

We failed the exam? It was because we saw a black cat just before, wasn’t it?

References:

Thinking fast and slow, D.Kahneman

Epstein, R. J. (2013). Has discovery-based cancer research been a bust?. Clinical and Translational Oncology15(11), 865-870.

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