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jasonfurman's review against another edition
5.0
An excellent book on the economics of Artificial Intelligence. Steeped in both economics and AI/ML, this book steers clear of hype (or anti-hype), applying standard economic concepts to a rapidly emerging phenomenon. The book is geared to business readers not economists or policymakers but it has a lot to offer to everyone.
At the heart of the book is the concept that AI/ML is a "prediction machine" that is dramatically lowering the cost of making predictions, which will lead to making it cheaper to engage in existing practices but also will open up new possibilities. The authors mostly focus on what businesses need to do in order to take advantage of those opportunities but with a some broader social/political/policy context.
Highly recommended.
At the heart of the book is the concept that AI/ML is a "prediction machine" that is dramatically lowering the cost of making predictions, which will lead to making it cheaper to engage in existing practices but also will open up new possibilities. The authors mostly focus on what businesses need to do in order to take advantage of those opportunities but with a some broader social/political/policy context.
Highly recommended.
sbnich's review against another edition
2.0
Good, but rather useless unless you want just the why and not the how. Nothing earth shattering.
jimsfekas's review against another edition
3.0
This was a really mixed bag. On the positive side, it's an interesting exploration of the economic implications of improvements in prediction. I think they well overshoot the technical possibilities, but it points in some interesting directions for how things might change as AI advances. But those overshoots are a major flaw. In their world, AI will always work perfectly for the job and not suffer from any limitations once it has the training data it needs. They barely even consider the possibility that there will be other technical limitations. Their own favorite example, Tesla's Autopilot functionality, points to the flaws in the book. To the authors, Autopilot is a beautiful example of the possibilities of AI, once it has enough real world data to train on. But we have enough news stories about Autopilot failures that we know their version is lacking nuance. It's too bad - they have some good points lurking in the middle of it all, if only they could have tempered their predictions.
garybake's review against another edition
5.0
Explains the economics of AI in a really clear and informative way.
adrianhon's review against another edition
3.0
More of a 3.5 stars. If you aren't familiar with AI, this is probably a very good introduction, although the examples will date very quickly and some of them are plain incorrect (e.g. face tags now sync across Mac and iOS). The point about prediction being a central part of AI is well-made and important, but like most popular economics books, they take this new insight rather too far and with too much confidence.
jumbleread's review against another edition
3.0
Good book for people who have no idea what AI does and how it is part of their life already. I found it to be repetitive. It does give glimpses into possible career choices that one can make and how to think about AI in one’s current career.
leaton01's review against another edition
3.0
As a book to breakdown the potential business opportunities, the authors do a good job of painting the sky in technicolor delights and getting CEOs salivating about how they could leverage artificial intelligence to improve profits. While it explains how AI works, it does not really give much lead and direction on how to implement it into business and the like; it's one of those situations where one must already vested in high-end programming within a business in order to see how to get there from here. If a reader is already part of or adjacent to the Silicon Valley-type companies, then much of this will make sense but if they sit outside that, they are less likely to find much of this book valuable beyond just learning about AI. Written from the lens of economists, the book also largely whitewashes over the problems that AI may inevitably create. They acknowledge them near the end but largely sweep them under the rug, admitting that many of the problems will be unforseen and not explainable; another way of saying they will cause harm first and then someone may decide to fix them, which seems irresponsible, but then again, social responsibility isn't often a priority for certain types of economists. Ultimately, the book works from the preface of "Why you should" and pays lip service to "What bad things may happen if you do". It's solid as an introduction to possibilities of AI so long as the reader knows they are likely being sold the sunny side. For more useful and critical understandings of AI, one would be better off reading [b:Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor|34964830|Automating Inequality How High-Tech Tools Profile, Police, and Punish the Poor|Virginia Eubanks|https://images.gr-assets.com/books/1499698329s/34964830.jpg|56239838] or [b:Algorithms of Oppression: How Search Engines Reinforce Racism|34762552|Algorithms of Oppression How Search Engines Reinforce Racism|Safiya Umoja Noble|https://images.gr-assets.com/books/1492944248s/34762552.jpg|55962260] or [b:The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity|41717507|The Big Nine How the Tech Titans and Their Thinking Machines Could Warp Humanity|Amy Webb|https://images.gr-assets.com/books/1541337629s/41717507.jpg|65073587].
vinayak's review against another edition
4.0
A nice introduction to Artificial Intelligence. A good read for those interested in this field.
bookmarkedatmidnight's review against another edition
5.0
If you want to understand better machine learning and what it entails, this is the book for you! It’s written in a way that a business person with no technical background would understand clearly the concepts. If you are a transitioner or beginner in tech, this book can help you build a path for your learning, following the prediction model’s structure pf elements.
Overall I find this book well written and I like the cover illustration :)
Overall I find this book well written and I like the cover illustration :)