The cliché about being hard to put down is really true here. This is about the rise and fall of Theranos, the Silicon Valley startup that claimed to revolutionize blood-testing as Apple did with phones. It's a story about an ever-escalating fraud that eventually leads to a valuation of more than a billion dollars, and it's exceptionally told by the reporter who broke the story. Full of interesting plot twists and details involving the military, the CIA, members of the Hoover Institute. Larger implications aren't drawn -- that would be a different book. But the story is incredibly engrossing. This would be a perfect book to take on vacation.

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A fascinating and very readable narrative history of advertising and media, from early 19th century until current times. Highly recommended especially if you teach marketing. Basically his thesis is that there are historical cycles governing consumer acceptance and rejection of advertising. Many interesting tidbits, like the first ad-driven newspaper which had to invent fake ads to convince advertisers of the potential merits, or that broadcast networks conceived of programming as a way to sell radios. It ties together a lot of strands in marketing and reminded me at times of Mad Men and Halt and Catch Fire.

Cover: Public Policy in an Uncertain World in HARDCOVER

A short book on causal inference, interval and bound techniques and their application to decision theory written by a leading econometrician in plain English.

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Cool book. Basically her main idea is that networked protests are an "easy come, easy go" phenomenon. Whereas the civil rights movement needed months and months to organize and coordinate the march on Washington which led to MLK's famous "I have a dream" speech, Gezi Park and Tahrir Square, her two most often mentioned protests, came about almost immediately due to Twitter and social media. Because the latter two protests didn't involve laying down the hard coordinating parts, they fell apart much quicker, there was no clear leader, etc. The book is a mix of theorizing and observation from the field. Here is an interesting interview of her with Ezra Klein:


This is a book of breathtaking ambition (or speculation): a universal law of scale applied to organisms, growth, death, cities, companies ... Read the first chapter to get an idea of the truly immense scope. There's a really neat simple elegance to his network theory that underlies the theory as applied to organisms, and the first 100 or so pages are the best in the book. I like the physicist's desire to strip out everything except the barest essentials in the model. It gets more hand-wavy as he turns to the growth of cities, and even more so as we get to companies. This is part of the Santa Fe complexity theory movement.

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A snarky review of this book is that Cass Sunstein, who complains about echo chambers here as well as in and Republic 2.0, is stuck in his own echo chamber, writing the same book over and over again. The reviewer goes on to predict future versions of this book, including Republic VR (virtual reality), among other things. There are some interesting ideas from legal theory, but they don't really amount to a persuasive solution, or even that a problem really exists.

This book documents the opioid crisis from several angles--addicts, dealers, doctors, police, community--written in highly evocative, story-telling prose. Probably the most interesting story is how dealers from this small Mexican town came to explore and create a new market in the American rural heartland. My only complaint would be its repetitiveness. A better editor could've made it more powerful by condensing. Even so, a fun read. Also, fun conversation on EconTalk

What I love about this book is the combination of "small data", following around and understanding the experiences of maybe 15 or so people over time, combined with the broader sweep of the author's academic research in this area. I come away completely impressed with the commitment of the author to his subject.

This is an eye-opening look at the dark side of big data and analytics in society. Written really as a polemic, she provides many devastating examples of the societal harms of big data algorithms, although almost all of them are for an American audience. Very thought provoking and passionately argued. At times, a little superficial. Still, this is a somewhat underrepresented view. There is a good interview of the author and discussion of her book on the EconTalk podcast. She's now a columnist at Bloomberg.

Reading this is like sitting across the table from an excited AI researcher. He creatively distinguishes five -- count 'em five -- tribes of research (symbolists, connectionists, evolutionaries, Bayesians, and analogizers). People tend to dismiss machine learning as either black box curve fitting or "old wine new label". This book gives a much more nuanced account of what this field is about. Sometimes, he overreaches for an analogy or example. Nevertheless, a thoroughly good read and overview. I learned a lot, even in the Bayesian chapter where I expected to know more.

Exquisitely written, it's the testimony of one of Britain's leading neurosurgeons on some very interesting successes and failures in his career. I like how he marvels at the mystery of consciousness arising from the billions of neurons firing away in the brain. Filled with many fascinating details.