Recently, I fell on a train platform when I tripped over my trolley bag while rushing to catch a train. The result: I missed the train anyway and broke two ribs. Six months later, I still feel discomfort, even though the severe pain I felt at first has gone away.
More recently, I slammed the back of my right hand into a door handle with all my weight, which left me disabled for several weeks and still hasn’t healed.
Two weeks ago, I left my suitcase on a train and didn’t realize it until several minutes after getting off, which meant I had to rush back to retrieve it before the train left again. I managed to do so, but at the cost of momentary exhaustion.
The accumulation of so many unpleasant and painful incidents made me think. My analysis identified one important factor: each incident happened in Paris.
Can I conclude that I should avoid this city from now on?
Before discussing the phenomenon behind this conclusion, let’s clarify two terms: causality and correlation.
There is a correlation between two elements when variations in one are statistically associated with variations in the other.
There is a causal link between two elements when a variation in one is the direct cause of a variation in the other.
There are true correlations and coincidences (correlations due to chance).
True correlation: children’s shoe size and their reading ability.
False correlation: the presence of storks and the birth rate.
Concluding that I should avoid Paris because I regularly have unpleasant experiences there is a false causality. Paris does not cause more difficulties than any other city, and vice versa.
False causality can unfortunately be used maliciously, as in the example of a boss who blames a new employee for the systematic failure of the projects in which he participates. While there may be a correlation, which is most likely coincidental, there is no demonstrable cause and effect. It is more a case of looking for a scapegoat than anything else.
Since teleworking has been allowed in the team, there is no solidarity among the members. Teleworking therefore destroys teams.
Here are some examples of false causality:
“After redesigning our logo, our brand awareness has increased. The new logo is the key to this success.”
« Since we started using this tracking tool integrated into the order management system, delays have increased: we need to look for another tool.“
”The team that took the training became more efficient, so the training must be given to all staff to boost productivity.“
”The month we launched this new brochure, sales almost stopped. We urgently need to thoroughly review this brochure. »
We understand that it is impossible to draw such conclusions without verification, as there are other, probably more plausible explanations in each case.
The succession of events over time does not mean that one causes the other.
If the explanation remains accurate regardless of the alternatives used, then the presumption of causality becomes a very serious possibility.
If it is impossible to logically demonstrate how one event leads to another, the causality becomes weaker.
Three ideas for countering false causality:
- Identify hypotheses without drawing conclusions: the hypothesis is therefore that… ?
- Look for at least one other explanation
- Identify the mechanism, step by step
If this false causality is imposed on us to weaken us, it is imperative to react assertively and use our critical thinking skills. Let’s not let ourselves be pushed around. And if this happens during a meeting, we understand even better how essential it is to have a devil’s advocate whose role is to question, in order to avoid reaching the wrong conclusions and making the wrong decisions.
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