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Engines of Evidence – A Conversation with Judea Pearl
- dirtyaura 10y agoPearl's "Probabilistic Reasoning in Intelligent Systems" was one of the most lauded books during my time in the university. I remember when Pearl gave a talk about his upcoming book Causality, my professor said that it might become one of the most important math and philosophy books of our life time. I never read Causality, and it is now 16 years since the publication. Can anyone who follows the field comment how it is perceived today?
- kobeya 10y agoRead the last few paragraphs of TFA.
- pinouchon 10y agoI'm 20 pages in. I'll eventually read it in full, but it is very math heavy and hard to digest. I am reading it at a very slow pace (a few pages per week) because that's the only way for me to assimilate the content. My personal opinion is that it is a very good book, just a bit hard.
- gabrielgoh 10y agoIm not completely sold on his book being a textbook. It is incredible bit of research, I agree, but it still has rough edges and should be treated as such, a work in progress. I do not think this book should be the bible of causality, and I think we're worse off for thinking it is. Personally, I find the work of Richardson and Robins in Single World Intervention Graphs https://www.csss.washington.edu/Papers/wp128.pdf https://www.csss.washington.edu/Papers/wp128.pdf far more intuitive and compelling than Pearl's do-calculus. The notation is too slightly cleaner and it does away mostly with the unorthodox notation Pearl uses.
- s_ngularity 10y agoI would like to get an introduction to the main ideas in current causality research. Is Pearl's book still the best introduction, or would you recommend something else instead?
- johnmyleswhite 10y agoI think most people who study causal inference would say that Pearl's writing is seldom as clear as a person unfamiliar with his ideas would like it to be. These days, I suspect most people would benefit from starting with Morgan and Winship instead: https://www.amazon.com/Counterfactuals-Causal-Inference-Principles-Analytical/dp/0521671930 https://www.amazon.com/Counterfactuals-Causal-Inference-Prin... In addition to presenting Pearl's ideas more clearly than Pearl himself tends to do, Morgan and Winship also describe Rubin's work more fairly than Pearl does. (On the other hand, Rubin also tends to disparage Pearl's work more than is necessary.)
- chrismealy 10y agoI tried reading Pearl's "Causality" but it was too much for me. Anybody get through it? What did you think?
- MrQuincle 10y agoThere will be a popular science book from him coming out, I read a draft a while ago. It will present it all in a digestible way. The do-calculus to me looks a bit cumbersome. I'm not generally attracted to math that doesn't look like math, except if it is nice looking. :-) On a more general level, when I'm building robots, I consider the interface between their minds and the world a Markov blanket. This means that state in the world can only be represented in the robot by learning through its interface by a combination of forward and inverse models. The existence of a physical barrier makes it possible to define information going through it. You might suggest that the world is created by the robot's mind, but that is probably difficult to back with any information criterion. If the robot learns its body, it knows that it is itself who is performing a movement or if it is being pushed. Knowing that it was itself the actor is enough to know the direction of the causal arrow.
- MrQuincle 10y agoInteresting research that addresses some weaker points: https://yanirseroussi.com/2016/05/15/diving-deeper-into-causality-pearl-kleinberg-hill-and-untested-assumptions/ https://yanirseroussi.com/2016/05/15/diving-deeper-into-caus...
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- jasoncrawford 10y agoSee also this introduction to Pearl's causal calculus by Michael Nielsen: If Correlation Doesn’t Imply Causation, then What Does? http://www.michaelnielsen.org/ddi/if-correlation-doesnt-imply-causation-then-what-does/ http://www.michaelnielsen.org/ddi/if-correlation-doesnt-impl...
- shoo 10y agoThis is a great introductory article, I heartily recommend it. I read this myself few years ago, got very excited, and had a go at writing a program that could automatically perform the derivation from Nielsen's worked example: https://github.com/fcostin/d_separation https://github.com/fcostin/d_separation This was really interesting to work on, but I guess I became disinterested in it after I got it to crudely work. Be aware that the quality of the code, documentation, and the entire idea of the "proof-search" aspect of it is probably not very good.
- szemet 10y agoA good link maybe: http://plato.stanford.edu/entries/causation-mani/ http://plato.stanford.edu/entries/causation-mani/ Pearl's theory summarized in chapter 5, but it is put into context: related work, criticism, etc...
- Caligula 10y agoJust an interesting note, his son was Daniel Pearl, who was tragically murdered in Pakistan. I enjoyed Probabilistic Reasoning in Intelligent systems. I was unaware of Causality.
- lordnacho 10y agoI came across Causality via this LessWrong article a few years ago. Seemed to make sense, but it is of course a very deep subject. http://lesswrong.com/lw/ev3/causal_diagrams_and_causal_models/ http://lesswrong.com/lw/ev3/causal_diagrams_and_causal_model...