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The Book of Why: The New Science of Cause and Effect Hardcover – May 15, 2018
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"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.
- Print length432 pages
- LanguageEnglish
- PublisherBasic Books
- Publication dateMay 15, 2018
- Dimensions6.3 x 1.4 x 9.4 inches
- ISBN-10046509760X
- ISBN-13978-0465097609
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From the Publisher
Editorial Reviews
Review
"Illuminating... The Professor Pearl who emerges from the pages of The Book of Why brims with the joy of discovery and pride in his students and colleagues... [it] not only delivers a valuable lesson on the history of ideas but provides the conceptual tools needed to judge just what big data can and cannot deliver."―New York Times
"Cause and effect is one of the most heavily debated, difficult-to-prove things in science and medicine. This book really gets you thinking about cause and effect as it applies to issues of our time, such as: How come cigarettes were around for years and we never showed they were causing cancer or heart disease? The authors goes through these cases like an interrogation, and it's just extraordinary."―Science Friday
"Seriously, everyone should read The Book of Why."―Jeff Witmer, American Mathematical Monthly
"'Correlation is not causation.' That scientific refrain has had social consequences...Judea Pearl proposes a radical mathematical solution...now bearing fruit in biology, medicine, social science and AI."―Nature
"Lively and accessible...Pearl was one of the visionary leaders of the causal revolution, and The Book of Why is his crowning achievement."―Jewish Journal
"Anyone interested in probing connections between cause and effect, and their relevance for the future of AI, will find this a fascinating and provocative book. Highly recommended."―CHOICE
"Judea Pearl is on a mission to change the way we interpret data. An eminent professor of computer science, Pearl has documented his research and opinions in scholarly books and papers. ... With the release of this historically grounded and thought-provoking book, Pearl leaps from the ivory tower into the real world...Pearl has given us an elegant, powerful, controversial theory of causality."―American Mathematical Society
"Have you ever wondered about the puzzles of correlation and causation? This wonderful book has illuminating answers and it is fun to read."―Daniel Kahneman, winner of the Nobel Memorial Prize in Economic Sciences and author of Thinking, Fast and Slow
"Pearl's accomplishments over the last 30 years have provided the theoretical basis for progress in artificial intelligence... and they have redefined the term 'thinking machine.'"―Vint Cerf, Chief Internet Evangelist, Google, Inc.
"Judea Pearl has been the heart and soul of a revolution in artificial intelligence and in computer science more broadly."―Eric Horvitz, Technical Fellow and Director, Microsoft Research Labs
"If causation is not correlation, then what is it? Thanks to Judea Pearl's epoch-making research, we now have a precise answer to this question. If you want to understand how the world works, this engrossing and delightful book is the place to start."―Pedro Domingos, professor of computer science, University of Washington, and author of The Master Algorithm
"The Book of Why ... questions and redefines the building blocks of our AI systems"―theverge.com
About the Author
Dana Mackenzie is a PhD mathematician turned science writer. He has written or co-written fourteen books, mostly on mathematical topics. He lives in Santa Cruz, California.
Product details
- Publisher : Basic Books
- Publication date : May 15, 2018
- Edition : 1st
- Language : English
- Print length : 432 pages
- ISBN-10 : 046509760X
- ISBN-13 : 978-0465097609
- Item Weight : 1.42 pounds
- Dimensions : 6.3 x 1.4 x 9.4 inches
- Best Sellers Rank: #528,554 in Books (See Top 100 in Books)
- #49 in Artificial Intelligence & Semantics
- #49 in Technology (Books)
- #1,403 in Computer Science (Books)
- Customer Reviews:
About the authors

Discover more of the author’s books, see similar authors, read book recommendations and more.

Writing is my second career, but it was my first love. As a kid, all I wanted to be was a writer. Nevertheless, my academic career took a different direction. I loved mathematics too, and earned a doctorate from Princeton. I taught math for six years at Duke University and seven years at Kenyon College in Ohio. I enjoyed it, but I have to say I never felt that teaching was my true calling.
In 1996, using the newfangled invention called the World Wide Web, I found out about the Science Communication Program at the University of California at Santa Cruz. Suddenly all the pieces of the puzzle clicked together. I could be a writer, as I had always wanted to be, and still make use of my knowledge of math and science.
At UCSC I learned about journalism and made the contacts I needed to hit the ground running. An internship at American Scientist in the summer of 1997 gave me some practical experience in writing and editing with a deadline. Since the fall of 1997, I have been a full-time freelance writer.
Some of the magazines I have written for are Discover, Smithsonian, Science, and New Scientist. "The Big Splat, or How Our Moon Came to Be" published by John Wiley & Sons, was my first book. Since then, I have written two booklets for the American Mathematical Society, called "What's Happening in the Mathematical Sciences," volumes 6 and 7. I am working on another book about mathematics now, and I will post more information as it comes closer to fruition.
The Story of "The Big Splat"
The idea for my first book, "The Big Splat, or How Our Moon Came to Be," came out of a meeting that I covered in 1998 for Science magazine. It was a conference about the origin of Earth and the Moon, and I was the only reporter there. In three days of talks, I was astounded to hear over and over about the giant impact theory of the Moon's origin -- a theory that was completely unfamiliar to me, and yet was really the only one seriously discussed at this conference. I was amazed that the experts had more or less agreed on where the Moon came from, and yet no one outside the planetary science community knew about it! There was clearly a failure of communication between scientists and the public. It was up to me to bridge the gap.
Writing the book was a lot of fun. It was the perfect size for a first book. It came out to be twelve chapters long, and I had about twelve months to write it. That meant that I had to tell one in-depth story a month, which was just the right pace for me. I enjoyed the feel of working on a long-term project, as a change of pace from jumping around from one article to another.
A special treat, which I did not at all anticipate, was doing historical research with original documents. To research one chapter I traveled to Cambridge, England, to delve into the Charles Darwin papers. (What does Charles Darwin have to do with the Moon? Read my book to find out!) It's hard to express the thrill of holding in my hands a letter that Darwin sent to his son a century ago, realizing that I might be he first person to read it since then.
"The Big Splat" came out in the spring of 2003, and received excellent reviews. Booklist, a magazine published by the American Library Association, named it as one of their Editor's Choices for 2003 -- an honor accorded to only 63 books that year, and only four science books.
In June of 2007 I appeared the History Channel's new series, "The Universe," in an episode called "The Moon." In fact, if you watch carefully you will see that about half of the hour-long show is based on "The Big Splat." It was a dream come true to see what was essentially a "TV version" of my book. In August 2009 I appeared on "The Universe" again, this time in an episode about how Earth would be different if we had no moon.
Everything Else You Wanted to Know about Dana Mackenzie
In my free time, I am also an avid chess player. I was the state champion of North Carolina in 1985 and 1987, and earned the National Master title in 1988. In 2006, I joined the team of master teachers at www.chesslecture.com, where I record two video lectures a month. Ironically, I find teaching chess to be more satisfying than teaching math was, and my "students" seem to like me better. Why?!? Maybe because chess is, in the language of academia, an elective course, while math often is not.
My other hobbies include music and dancing. I started folk dancing in college, and years later I met my wife, Kay, in an international folk dance group. Four years ago I joined the Hula School of Santa Cruz, a warm, supportive, and family-oriented group. I strongly encourage any of you who have ever experienced the aloha spirit to find your local halau and give hula a try. The photo shows me before one of our performances.
Kay is also a writer -- we call ourselves the "Mackenzie Publishing Empire"! If you are into quilting, please check out her books, either here at Amazon.com or by visiting her webpage at quiltpuppy.com.
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Another Key Contribution from Judea Pearl
Top reviews from the United States
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- Reviewed in the United States on May 17, 2018Format: HardcoverVerified PurchaseThe Book of Why is a popular introduction to Judea Pearl’s branch of causal inference. But it is also so much more.
Pearl has written many other textbooks introducing his graphical approach. But in this book, Pearl provides an engaging narrative of the history of causal inference, the important distinctions he sees in his branch and its importance for the future of Artificial Intelligence.
Briefly, Pearl views classical statistics as seriously flawed in not having developed a meaningful theory of causality. While able to demonstrate correlation, Pearl asserts that in classical statistics all relationships are two-way: that is 2x=3y+6 can also be written 3y=2x-6. We are left in doubt as to whether x causes y or y causes x.
Fundamentally, Pearl sees this problem as still plaguing all artificial intelligence and statistics. In its place, Pearl argues that the exact causal relationship between all variables should be explicitly symbolized in graphical form and only then can mathematical operations tease out the precise causal effect.
To be transparent, I am trained in the Rubin approach to causal inference and disagree with some of Pearl’s history and characterization of statistics. But that is not the point. The history is well-written, engaging and understandable by the lay reader. Similarly, his account of graphical causal inference theory is followable even for someone like myself who did not learn these techniques in graduate school.
The last part of the book, where Pearl opines on the future of AI, is the most sensational. Pearl believes that if computers were programmed to understand his symbolization of causal inference theory they would be empowered to realize counterfactuals and thus engage in moral decision making. Furthermore, since Pearl himself was a pioneer in deep learning, his characterization of contemporary AI as hopelessly doomed in the quest to replicate human cognition because of a lack of understanding in causal inference will be sure to garner attention.
But one would be misguided to think that speculations about AI or mischaracterizations of other kinds of causal inference make this book any less of a classic. For the first time, Pearl has written a popular, interesting and provocative book describing his branch of causal inference theory—past, present and future.
This book is a must read then, not only for causal inference theorists, but more widely for those with any interest in contemporary developments in computer science, statistics or Artificial Intelligence. A book that, like Kahneman’s Thinking Fast and Slow, is a triumphant summary of a lifetime of work in scientific topics that have ramifications, not only for fellow scientists, but for all of humanity.
- Reviewed in the United States on June 27, 2019Format: HardcoverVerified PurchaseThe book's subtitle, The New Science of Cause and Effect, aroused both my skepticism and my curiosity: skepticism because I wondered how such a science could possibly be new, curiosity because I wanted to find out. The authors explain: Causal reasoning is ingrained in us and essential to our thinking, yet the human and social sciences often shy away from it, partly because they lack the proper models for its application. To stay on the safe side, people often speak in terms of "correlation" rather than causation. But this just evades the problem of causality, which can actually be described and tackled. The book shows how.
Reading it slowly, I reached the point where I could understand the explanations of the diagrams and formulas. I especially enjoyed Chapters 6 and 8 (on paradoxes and counterfactuals, respectively). Yet I was well aware, along the way, that to truly understand this subject--that is, to be able to create and apply causal models on my own--I would need to read the book several times, work through each of the examples, and then work independently on related problems. Even then, I could not guarantee that I would do this well, since causal reasoning requires careful analysis of the problem at hand: of all the variables involved in it and their causal relationship to each other.
Take, for example, the discussion of the smoking/cancer debate in chapter 5. Those who doubted that smoking causes cancer--R. A. Fisher and Jacob Yerushalmy among them--posited a constitutional factor, a so-called "smoking gene," that would predispose a person not only to smoking, but to other unhealthy behaviors that can likewise lead to cancer. Pearl and Mackenzie demonstrate, through causal diagrams, that such an explanation of the smoking-cancer relation is implausible. That is, even if such a gene exists (and it does), it does not erase the direct causal relationship between smoking and cancer. This all makes sense and looks elegant on paper. But to arrive at it is a different matter. The book does not turn anyone into an expert; rather, it helps readers at all levels perceive the scientific problems more clearly.
I have many books waiting for me, but this is one that I hope to reread. Its science is real, its problems intriguing, and its implications compelling. With models for causal reasoning, we can tackle issues like global warming with greater clarity and confidence. We don't have to choose between unwarranted conclusions and flailing uncertainty. Causal reasoning allows us not only to pose clearer questions, but to work our way toward answers. The Book of Why opens up a promising field.
Top reviews from other countries
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CGReviewed in Mexico on January 10, 20225.0 out of 5 stars Buen libro
Format: PaperbackVerified PurchaseDetallado en la exposición del tema.
Marcos Augusto Burgos SaavedraReviewed in Australia on July 16, 20255.0 out of 5 stars Loved the book
Loved the book
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JaguarellaReviewed in Brazil on October 28, 20255.0 out of 5 stars Um pacote com matemática, probabilidade, estatística e inteligência artificial
Format: PaperbackVerified PurchaseLivro interessante e muito informativo para quem se interessa por matemática, inteligência artificial.
Victor LiReviewed in Singapore on May 27, 20215.0 out of 5 stars Easy to read
Format: HardcoverVerified Purchaseit is good to read no matter which area of study you are doing. I am doing research in CS and found this one quite useful. The book is written in a casual and easy understanding way.
Ivan SarmientoReviewed in Canada on January 15, 20255.0 out of 5 stars Good science
Format: PaperbackVerified PurchaseGood science in accessible language.



















