Mind over data
The ladder of causation
From buccaneers to guinea pigs: the genesis of causal inference
From evidence to causes: Reverend Bayes meets Mr. Holmes
Confounding and deconfounding: or, slaying the lurking variable
The smoke-filled debate: clearing the air
Paradoxes galore!
Beyond adjustment: the conquest of mount intervention
Counterfactuals: mining worlds that could have been
Mediation: the search for a mechanism
Big data, artificial intelligence, and the big questions

"Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.