What is Probabilistic Causation?
Probabilistic Causation is concept in probability theory that examines the relationship between cause and effect. The essence of probabilistic causation is not that one factor causes
another to happen, but rather one factor increases the likelihood of another event happening, all else being equal. The term "Causation" is specifically defined in terms of a cause preceding and increasing the probability of an event or effect.
How does Probabilistic Causation work?
Probabilistic Causation is often confused with general a deterministic relationship. In deterministic relationships factor A causes factor B every single time. Often, however, deterministic relationships don't accurately describe phenomena. For example, an unhealthy diet doesn't cause death, a heart attack does. In this instance, it is helpful to describe the relationship in terms of probabilistic causation. An unhealthy diet increases the probability that one will die as it increases the likelihood of having a fatal heart attack. In short, probabilistic causation is almost always described verbally as, "A will probably lead to B."
Probabilistic In the example image above, Probabilistic Causation is represented visually. Taking birth control pills has a probabilistic effect on both pregnancy and thrombosis. The chance of pregnancy is reduced when taking birth control pills, but there's an increase in the chance of thrombosis. Similarly, pregnancy increases the chances of thrombosis as well, however no factor inherently causes another to occur.