This is one of the most complete books I've read in a long time. Filled with wisdom, insight, philosophy, wit, curiosity. And, most importantly, humility.
I felt that each chapter could be a book unto itself. I felt that some insights were exceptional, while others gave me pause. Perhaps one of the reasons is that the book covers so much ground in such a short time and in doing so passes over vasts amounts of scholarly research (glosses over them, randomly picks through it perhaps). In some of the subjects where I was familiar with the scholarly literature, I was thoroughly impressed by his ability to take complex ideas, summarize them, synthesize them, and pack them into a short chapter.
On the other hand, I was also a little worried about how much certain debates were left on the cutting-room floor.
In cases where I wasn't as familiar with the scholarly literature or in chapters where I think he is dealing with new theoretical territory, I wish he would have slowed down and thoroughly explained the assumptions that were leading his insights. Typically, I like concise books and light on citations; but in this case, I found myself missing the thick list of notes and citations at the end. For this reason, I would like to thoroughly interrogate the ideas of the book again at a slower pace.
One of the key ideas of the book -- that revolutions in biotech and infotech (AI especially) might lead to algorithms that are better decision-makers than humans -- is an insight that contradicts my own findings regarding computer-led decision-making. In short, what I've found in my reading "black box" decision-making tools, even ones that bake in a lot of data, have tendencies toward catastrophic blow ups when they try to predict human behavior.
The most dramatic example of this was 1998's Long Term Capital Management which used a computer model for investing and almost blew up the world economy. One of the designers of the model, Nobel prize winner Myron Scholes, afterward suggested that if they had simply baked in more data they would have been fine. (Here is a link to Long-Term Capital Management history on Investipedia: https://www.investopedia.com/terms/l/longtermcapital.asp). My guess is that it would have simply delayed the blow-up and made it perhaps more catastrophic.
An attempt by google to use an algorithm to predict the outbreak of flu cases was another example of a prediction algorithm that was well-behaved for a while and then fell apart. (You can read about that one here: https://www.wired.com/2015/10/can-learn-epic-failure-google-flu-trends/).
Of course, Long-Term Capital Management was more than 20 years ago. AI, algorithms, and machine learning, I'm sure, have significantly improved and will improve, as the author's own research suggests. I don't doubt his insight that humans will increasingly come to rely on algorithms. But I was concerned that he didn't address the problem of randomness in human action that often leads these models to be catastrophically wrong.
The point is that he covers so much so fast that there are probably a lot more of these gaps that need to be examined.
I think that the book both in its message and its design makes the case for more of this kind of writing by scholars. Since the 21st century moves fast and upends your preconceived notions fairly quickly, perhaps scholars should also try to move fast, even if it means throwing some caution to the wind. I have mixed feelings about this. For a long time, even early in the twentieth century, people have suggested that scholars need to engage more in public discourse -- be unafraid of the pundits and punditry world. They should engage in the often messy debates that mark and scar our imagination on TV, radio, and newspapers (and now Youtube and social media).
For me, punditry is a four-letter word. It's actually pronounced ****ing punditry. Their priority is ratings and relevancy: thus attention-grabbing and entertainment are a priority. The scholar's greatest resource is his or her ability to be irrelevant: to play around with ideas that aren't sexy or exciting. Scholars have entered the punditry world before and the results I believe have not always been happy ones. Those who fight monsters need to be cautious that they do not become one (Friedrich Nietzsche I believe, but its origin is perhaps far older). This book, written quickly, tackling big problems, making big assertions, may come close to that dirty four-letter word. It is certainly more relevant for it. Certainly the kind of book that I would not hesitate to recommend to a high-level high school student or college freshman. (Still too scholarly I'm afraid for a barroom chat). But for that reason, it also warrants my caution -- and another read.
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Pure Writerly Moments 2 (Short Stories, Essays, Book Reviews, and More)
Fiction généraleWhat is the connection between artistic expression and the joy of living? How can one best live a literary life? This book is a collection of small word-projects. Each examines a book, a moment, a story that helps to deepen the author's literary adv...