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 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.

Title:The Book of Why: The New Science of Cause and Effect
ISBN:9780465097609
Format Type:

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

  • nostalgebraist

    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 tech...

  • Andrew Harlan

    Failed revolutionIn 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 ...

  • Alex Telfar

    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...

  • Terran M

    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 vil...

  • Gary  Beauregard Bottomley

    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 sho...

  • Nilesh

    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 maste...

  • Ryan Sloan

    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) determin...

  • Andy

    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...

  • Thiago Marzago

    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 ...

  • Emre Sevin

    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 wh...