The Book of Why: The New Science of Cause and Effect

The Book of Why: The New Science of Cause and Effect

A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence "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 Jud A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science...

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Title:The Book of Why: The New Science of Cause and Effect
Author:Judea Pearl
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Genres:Science
ISBN:The Book of Why: The New Science of Cause and Effect
ISBN
Format Type:Hardcover
Number of Pages:432 pages pages

The Book of Why: The New Science of Cause and Effect Reviews

  • Carl Zimmer
    Jul 05, 2018
    Cause and effect may seem like the stuff of pure philosophy, but Judea Pearl shows how important causation is to the applications of science, from the technology in our cell phones to the link from smoking to cancer. Pearl, a UCLA computer scientist, presents a personal history of this...
  • Andy
    Jan 19, 2019
    This review is for the audio version. This topic is very interesting but audio is a terrible format for this book. The narrator is reading out equations. The whole point of the book is to use diagrams. There is a PDF with the audiobook, but the figures are not meaningful on their own. ...
  • Karel Baloun
    Nov 05, 2018
    Valuable for your permanent for ongoing reference and inspirational revisiting, with an absolutely ideal annotated bibliography. Artisan crafting to certainly withstand the test of time. Invest 2-3 days in simplifying and repairing how you think causally! I?m sure glad I did. Fun ...
  • Nancy
    Jan 23, 2019
    Chapters 1-6 are very general audience friendly and frames statistics in a historical context. Pearl does a great job making the case that science needs to study cause over just the effects and he advocates a common, simple framework/language that can be quickly shared across all disci...
  • Jason Furman
    Aug 16, 2018
    This was a long, strange trip through the statistical analysis of causation. Judea Pearl writes beautifully and in an almost grandiose manner, dubbing himself a Whig historian of the science of causation--how it was forgotten by statistical analysis that put correlation at the pinnacle...
  • Shreef A
    Feb 17, 2019
    I'm not a statistician by education so don't know how ground breaking the ideas discussed in the book, and don't how to argue for them or against them. Judea Pearl (author) himself a has a great track record in that field, and still he admits that he gets a lot of push back from ot...
  • Nilesh
    Jun 11, 2018
    Here is an excellent book by a renowned expert but potentially with deep fundamental flaws and conclusions. The reviewer is more likely mistaken in these views given that the author is clearly a master thinker on the subject - a point worth noting for any soul wading through this long ...
  • Gary  Beauregard Bottomley
    Jan 13, 2019
    There were some real flaws with this book that bothered me to no end. I had no problem following his statistical examples and how to think about data analysis in the way the author suggests we all should. I even enjoyed it when the author connected what he called Smart Artificial Intel...
  • Jayson Virissimo
    Jun 23, 2018
    I was expecting something at about the level of Thinking: Fast and Slow, but this book is far more technical, and much of it went over my head. I?ll have to revisit this after reviewing stats and actually learning some graph theory before giving this a meaningful rating. ...
  • nostalgebraist
    Sep 03, 2018
    I had high hopes for this book. I've been interested in causal inference for a number of years, and I think it's an field that could drastically improve the practice of statistical science if its techniques became widely adopted. A popular book on the field, written by one of its found...
  • Richard Thompson
    Jun 27, 2018
    My mistake with this book was to listen to it as an audio book. I'm sure that it would have been better if I had listened with the PDF diagrams at my side, but Mr. Smarty Pants thought he could absorb it all in his car. Not. I certainly got the general drift and understood the concepts...
  • Siddarth Gore
    Jun 24, 2018
    Have you ever noticed that, among the people you date, the attractive ones tend to be jerks? The book presents a new way of looking at how we program computers and also a new tool to do statistical modelling in general. The theory is indeed very interesting and surprisingly simple t...
  • Rif A. Saurous
    Jun 21, 2018
    This is a popular science intro to causality from Judea Pearl (cowritten with a Dana Mackenzie, a science writer, who probably did most of the writing, although the book is told in Pearl's "voice"). Judea Pearl is an absolute titan of computer science and machine learning, being more-o...
  • Tõnu Vahtra
    Mar 10, 2019
    Beyond big data... one of those books that you should not be taking up as audiobook, the mathematical discussions were difficult to follow at times to say the least. Though the calculus is probably too much for everyday life/work anyway, on a practical level familiarity with those conc...
  • Minh Nhật
    Jan 06, 2019
    khen cu?n ny th th?a, m?t cu?n pop-sci vi?t b?i 1 h?c gi? l?n trong l thuy?t xc su?t v h?c my. C c?m h?ng s? vi?t review honh trng c? m c ai quan tm ko nh? T^T, ko th thi kh?i z?yyyyyyy ...
  • Ryan Sloan
    Jan 02, 2019
    There are great ideas in this book. I'm not an expert on causality or statistics, but I found the idea of modeling causality using a directed graph, and using that graph as a tool for both a) determining valid controls in experimental data and b) performing counterfactual reasoning to ...
  • Athan Tolis
    Oct 08, 2018
    My son George?s first language is Japanese. His first annoying habit, which raised its head very soon after he was granted the gift of speech, was to answer every request / question / casual comment with ?doshte?? ?Doshte,? you guessed it, is Japanese for ?why?? ...
  • Alex Telfar
    May 21, 2018
    I enjoyed this book! It did everything a good book should do, it provides; understandable examples, entertaining side-notes, applications to the real world, something useful that is novel/little known. The book could have been better (5 stars) if it was more concise, explained the...
  • Siddhartha Banerjee
    Aug 09, 2018
    Every now and then you read a book that introduces you to a new concept and forces you to reevaluate your world view, leaving you better for it. For me, this was one such book. Highly, highly recommend. ...
  • Thiago Marzagão
    Jun 06, 2018
    This is an engaging, well articulated discussion of causal inference - what it is, what the available tools are (RCTs, IVs, matching, etc), how they have changed over the years, and how they could be improved. The bits that tell the history of causal inference are especially illuminati...
  • Daniel Christensen
    Jul 18, 2018
    If you are a science or stats geek, or frustrated with the replication crisis in across various disciplines, or even a philosophy/ cognitive science boffin, this book is highly recommended. Judea Pearl is a heavy heavy hitter. He was a big deal in Computing and Artificial Intelligen...
  • Emre Sevinç
    Nov 18, 2018
    If I've earned a penny every time I heard the sentence "correlation is not causation", I'd be a richer man by now, and that'd probably be a causal relationship. If correlation is not causation, then what is causation? I, like many others, asked this question since I took my first un...
  • Zining
    Nov 26, 2018
    I think this book gives good introductions to the topics in causal reasoning. I particularly like two parts: (1) The chapter talking about Simpson's paradox, where the author gives multiple view points to understand the phenomenon. (2) The chapter about back-door and front-door adju...
  • Jeethu Rao
    Mar 19, 2019
    The book of why ?Correlation does not imply causation? is the oft cited maxim in statistics. This book begins with the question, ?If correlation does not imply causation, then what does?? and then proceeds to introduce the nature of causality and causal inference. The author...
  • Vicki
    Jan 12, 2019
    The examples were good, but for the rest of it the writing was muddled. Plus, I chose to listen to this as an audio book which was a huge mistake because you can't see any of the diagrams and this book seems to rely on them. I think his theory is interesting, but I wouldn't recommend t...
  • Kelly Jade
    Dec 04, 2018
    The book would have been 100 pages shorter if the author spent less time name dropping and talking himself up. We get it. Everyone who opposes you is wrong and stupid and you're the greatest and smartest, just look at all your students with all these high level faculty position...
  • Peter McCluskey
    Jul 17, 2018
    This book aims to turn the ideas from Pearl's seminal Causality into something that's readable by a fairly wide audience. It is somewhat successful. Most of the book is pretty readable, but parts of it still read like they were written for mathematicians. History of science A fa...
  • Terran M
    May 24, 2018
    I've never met Pearl, but having read a couple of his books, I'm pretty sure he's an asshole. His anger and bitterness comes through very clearly in his book ? he spends as much space naming and vilifying his professional enemies, both living and dead, as he does explaining his work....
  • Andrew Harlan
    Dec 05, 2018
    Failed revolution In an old joke, an engineer, a physicist and an economist are marooned on a desert island with canned food. They are trying to figure out the best way to open the cans, and while the engineer and the physicist propose various mechanical schemes to get the job done,...
  • Teo 2050
    Jun 03, 2018
    Contents: (view spoiler)[Pearl J & Mackenzie D (2018) Book of Why, The - The New Science of Cause and Effect Dedication Preface Introduction: Mind over Data ? a blueprint of reality 01. The Ladder of Causation ? the three levels of causation ? the mini-Turing te...