Judea Pearl is a computer scientist and philosopher, best known for championing the probabilistic approach to artificial intelligence and the development of Bayesian networks. He is also credited for developing a theory of causal and counterfactual inference based on structural models. He is the 2011 winner of the ACM A.M. Turing Award, the highest distinction in computer science, "for fundamental contributions to artificial intelligence through the development of a calculus for probabilistic and causal reasoning." Here he discusses the causal revolution, why stats and big data can't answer any causal questions, the two languages of the causal revolution, the ladder of causation, classical statistics, Bayesian networks, Hume, Lewis and counterfactual reasoning, free will, human minds as causal not statistical machines, how this changes the way data is used, mediation, and why we should note that we are smarter than our data.
3:AM: What made you become, among other things, a philosopher?
Judea Pearl: Philosophers do not consider me one of them. Perhaps because I have degrees in engineering and physics or because I show no interest in digging into the irrelevant writings of ancient philosophers. My interest in philosophy was sparked by my highshool teachers who insisted on teaching us about the lives of Pythagoras, Socrates, Archimedes, Epicurus and Diogenes. I recall that, unlike most of my classmates, I was deeply concerned with the foundational issues: what do we mean by an electric field, how do we know that 1 Ampere measured one way is the same 1 Ampere measured differently. etc.
I later read quite a few books in the philosophy of science, from Reichenbach to Nelson Goodman, from Popper to Toulmin and A J Ayer. Through their influence, I went back and read Locke and Hume. But I could not stand Hegel and Kant.
From 3:AM Magazine
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