The Book of Why

The New Science of Cause and Effect

By: Judea Pearl, Dana Mackenzie

Narrated by: Mel Foster

Length: 15 hrs and 14 mins

Publisher's summary

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 PDF will be available in your Audible Library along with the audio.

Download the accompanying reference guide.

©2018 Judea Pearl and Dana Mackenzie (P)2018 Brilliance Publishing, Inc., all rights reserved

Excellent book but hard to listen to as an audiobook

This book is absolutely worth a read for anyone doing data science. But, since it makes a lot of references to figures in the supplementary PDF and reads out complicated equations, it’s difficult to listen to as an audiobook.

A True Miracle

This work represents a foundational knowledge obtained by a few, desperately needed by all. Key truths to morality and agency can be gleaned by a reader interacting with the text.

I, for one, am a better person.

Great book. Worth a listen and a challenge.

Great book. Had to put my statistics thinking cap on but super interesting. Definitely worth a listen if you want to challenge yourself. And it will challenge and download the pdf to follow along with the diagrams. It is needed.

Great book, but hard to get the details over audio

Great book. Clearly written with great examples. Some parts discussing math or graphs are difficult to grasp in audio form, however.

Correlation does not imply causation...

That is he premise of the book, a concept which the author then repeats with supporting evidence throughout the book. Loosely links said ideas with the development of a.i. Says we aren’t as close to developing A.I as the general public assumes. Gives reasons why in the first and last chapter. Overall the book reads like a lecture on statistics given by a cool professor who has forgotten that her students aren’t as well versed on said topic as she is. Information presented is sometimes contradictory to earlier chapters. Great narration; listened at 3x speed and could still follow the narrator.

Start Your AI Journey Here

Judea Pearl will pop a lot of AI hype balloons and then inform a much better path (pun intended) to take going forward.

The game changer in understanding the world

This book is excellent in plainly explaining why causality is the source of paradoxes in our intuition. I loved how it was rich with examples demonstrating causal concepts, and how associative thinking can mislead us into bringing wrong conclusions.

Shouldn’t be an audiobook

I found it tough to grasp the concepts without seeing the stats, graphs and examples

On every scientist's required reading list

An excellent book on many different levels in many different fields including philosophy, science, history, mathematics, and innovation. Every aspiring scientist should read this book. The statistical formulas and language add to the text, but may be ignored by readers won simply want an understanding of the ideas that underlie causal analysis.

great book!

This is a very good book content wise, but it my not be the most friendly to listen to. There are many passages with formulas and equations, which will make casual listening harder than usual.