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The Book of Why

The New Science of Cause and Effect

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The Book of Why

By: Judea Pearl, Dana Mackenzie
Narrated by: Mel Foster
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About this listen

How the study of causality revolutionized science and the world

"Correlation does not imply causation". This mantra has been invoked by scientists for decades and has led to a virtual prohibition on causal talk. But today, that taboo is dead. The causal revolution, sparked by Judea Pearl and his colleagues, has cut through a century of confusion and placed 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.

PLEASE NOTE: When you purchase this title, the accompanying reference material will be available in your Library section along with the audio.

©2018 Judea Pearl and Dana Mackenzie (P)2018 Brilliance Publishing, Inc., all rights reserved History & Philosophy Philosophy Science Social Sciences Data Science Artificial Intelligence Machine Learning Mathematics Computer Science
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liked the book overall.. have recommended it to friends.. but as an audiobook.. no pdf ?

no pdf means graphs described unseen

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Such a bad American voice, nice gateway book, although quite convoluted despite the chapter areas supposedly breaking it down. It doesn't transcend the sum of its parts into 'a book' for me but resembles more a collection of essays bound in a book format. it might well have just given the equations and formal diagrams and be done in a chapter rather than go on repeating cliches or the most boring anecdotes.

Moreover, the thesis of a new science where for decades science was in statistical stasis makes so little sense. On the one hand he says that causation is intuitive and precedes all other scientific endeavours but then on the other that people gathered data for association and nothing else for decades! Lacking an AI vocabulary doesn't mean causation didn't exist as a basis for pretty much all natural sciences (precluding pure mathematics).

Read David Deutsch on AI's toddling progress, also, it doesn't deliver what it promises. Made me sleepy not because of content but because it just takes so long to get to the point which is usually merely that drawing causation as a diagram is better than not.

What is most annoying, however, is the narrator. Staid American accents impair my ability to take in the information from so many good books like this, Book of Why, Steven Pinker written titles, The Secret of Our Success and so on. The way these narrators narrate it's as though they *are* a program which just reads out in a level voice without any understanding of the topic. Any other voice would have been better. Why do publishers inflict this in audio? Especially on an audience like the UK, why not Jonathan Kebble, Simon Vance, Stephen Fry, Jeremy Irons, Kate Winslet, Emma Thompson, Peter Noble, Ric Jerom or any actor able to emote and speak in a clear variable intonation for a British audience?

Is the narrator a robot?

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Thorough and well explained examples, with a good sprinkling of historical context. Impressed with how relatively easy to follow it was even in audiobook form

Great intro to causal modelling vs traditional

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this is a fascinating book but not ultimately very well suited to the audiobook format, as there is much discussion of diagrams and quite a lot of discussion of algebraic formulation. Judea Pearl is the leading scientists in causal theory field, and while it is a valiant attempt to write a a general interest book for non specialists, ultimately he gets so far into the technical details that is almost impossible to follow, at least on an audiobook. There are only so many times one can listen to sentences like "the P of Ý given du X is estimable subject to a du operator".

Starts out well but format is a challenge.

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Reader was not great, and he was reading a proof copy. - so missed some corrections (I was reading along). The pace was too fast for a technical book like this,which requires constant pauses for thought.

But I'm glad I read it, and it gives some hope for a humane implementation of AI.

Not for the general reader

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