Causal Fallacies
Causal fallacies are errors in reasoning about cause and effect, often involving incorrect assumptions that correlation implies causation or ignoring confounding variables.
THE IDEA
Causal Fallacies
Nothing is so difficult as not deceiving oneself.
Ludwig Wittgenstein
When to use it
When interpreting research findings to ensure that reported causal claims are justified.
In policy-making, to avoid implementing interventions based on spurious correlations.
In personal decision-making, like attributing success or failure to specific actions without considering other factors.
In debugging systems, to avoid assuming that a change caused an outcome without controlling for other variables.
FROM THEORY TO EVERYDAY LIFE
In practice
Post Hoc Ergo Propter Hoc
Assuming that because event B followed event A, A caused B. For example, after a rooster crows, the sun rises, leading to the false belief that the crowing causes the sunrise.
Confusing Correlation with Causation
Assuming that two correlated variables have a causal relationship. For instance, ice cream sales and drowning incidents both increase in summer, but ice cream does not cause drowning; heat is a common cause.
A MOMENT TO REFLECT
Put it to work.
Recall a recent conclusion you drew about a cause and effect. What evidence did you use? Could a causal fallacy be at play?
How can you design an experiment to test a hypothesized causal relationship more rigorously?
Why might it be difficult to admit that a cherished belief based on a causal assumption might be wrong?
CONTINUE THE CONVERSATION
Source texts
- Informal Logical Fallacies A Brief Guide