Why did I love this book?
When our descendants look back and ask, “Which scientist’s work changed the way we think, around the year 2000?”, I am prepared to bet that Judea Pearl will be top of the list. Before Pearl, statisticians refused to allow any model of the world into their analysis, thinking it wise to say “correlation does not imply causation,” while remaining scrupulously blind to the reasonableness of some models over others. But the fact that cockerels crow at dawn really is evidence that sunrise causes crowing, and does not constitute any kind of evidence that crowing causes sunrise.
By including such background knowledge in a systematic, graph based manner, Pearl has developed an operational definition of “causation”. This helps to clarify what big data can and cannot deliver, and provides a methodology for establishing the strength of causal connections where we cannot conduct blind trials (like with smoking, or exercise). A very readable, popular science guide to an epoch-defining set of insights.
6 authors picked The Book of Why as one of their favorite books, and they share why you should read it.
'Wonderful ... illuminating and fun to read'
- Daniel Kahneman, winner of the Nobel Prize 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 have redefined the term "thinking machine"'
- Vint Cerf, Chief Internet Evangelist, Google, Inc.
The influential book in how causality revolutionized science and the world, by the pioneer of artificial intelligence
'Correlation does not imply causation.' This mantra was invoked by scientists for decades in order to avoid taking positions as to whether one thing caused another, such as smoking…