foreword
Twenty-seven lawyers in the room, anybody know ‘post hoc, ergo propter hoc?’
—President Josiah Bartlett ( The West Wing)
“Post hoc ergo propter hoc” is a logical fallacy regarding causation: “After it, therefore because of it.” The idea dates back at least to Aristotle (the fallacy appears in On Sophistical Refutations). More than two thousand years after Aristotle, Welsh economic theorist Sir Clive Granger inverted “post hoc ergo propter hoc” to provide one of the two principles underlying what is now known as Granger Causality, namely that something cannot cause something if it happened before it.
Humans have been fascinated by the notion of causality—what causes what—since their early recorded writing. Indeed, causal reasoning is a major distinguishing feature of human cognition. On a practical level, the importance is obvious: one cannot control something if one does not understand cause and effect. Causal AI is the first book I know of that draws together the necessary theory, the technical foundations (i.e., the packages and libraries), and a host of real examples, to allow anyone with a decent grounding in basic probability theory and software engineering to get started using causal AI to tackle any problem they choose.