What Is Causal Inference?

The Unreasonable Importance of Causal Reasoning

We are immersed in cause and effect. Whether we are shooting pool or getting vaccinated, we are always thinking about causality. If I shoot the cue ball at this angle, will the 3 ball go into the corner pocket? What would happen if I tried a different angle? If I get vaccinated, am I more or less likely to get COVID? We make decisions like these all the time, both good and bad. (If I stroke my lucky rabbit’s foot before playing the slot machine, will I hit a jackpot?)

Whenever we consider the potential downstream effects of our decisions, whether consciously or otherwise, we are thinking about cause. We’re imagining what the world would be like under different sets of circumstances: what would happen if we do X? What would happen if we do Y instead? Judea Pearl, in The Book of Why, goes so far as to say that reaching the top of the “ladder of causation” is “a key moment in the evolution of human consciousness” (p. 34). Human consciousness may be a stretch, but causation is about to cause a revolution in how we use data. In an article in MIT Technology Review, Jeannette Wing says that “Causality…is the next frontier of AI and machine learning.”

Causality allows us to reason about the world and plays an integral role in all forms of decision making. It’s essential to business decisions, and often elusive. If we lower prices, will sales increase? (The answer is sometimes no.) If we impose a fine on parents ...