To counter some of the comments here, I absolutely loved the book and went on to recommend it to all my scientist friends. While it may get a bit technical for the lay audience, it should be within reach for a typical scientist or IT person. I wish our society had a better understanding of causality—that would raise the level of many important discussions.

Being a long-time fan of Gelman (and having studied his Bayesian Data Analysis textbook), I am baffled and disappointed that he doesn't seem to understand Pearl's ideas. In his linked 2009 post[1], he wrote: "I’ve never been able to understand Pearl’s notation: notions such as a “collider of an M-structure” remain completely opaque to me." I wonder if, after reading this book accessible even to non-statisticans, he still doesn't understand it.

[1]: https://statmodeling.stat.columbia.edu/2009/07/05/disputes_a...