Review: Prediction Machines: The Simple Economics of Artificial Intelligence
My rating: 3 of 5 stars
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 Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor or Algorithms of Oppression: How Search Engines Reinforce Racism or The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity.
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