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A review by davidr
Prediction Machines: The Simple Economics of Artificial Intelligence by Joshua Gans, Avi Goldfarb, Ajay Agrawal
4.0
This is a pretty good book about how artificial intelligence (AI) can be applied to businesses. It is not a technical book--you won't find any details about the wide range of technologies being used for machine learning. Instead, you will find many ingenious ways to put AI to use, as well as all the business ramifications. Three professionals from Toronto's Rotman School of management collaborated to write this book. The book is unified, and reads as if it were written by a single person. However, it is not a particularly engaging book. There is no entertainment value here, definitely no humor. It is a no-nonsense book--almost in the style of a textbook, with good summaries at the end of each chapter. But, the book is not dry, and is easy to read. It is filled with interesting stories and anecdotes.
The basic premise of the book is that the cost of prediction is dropping. Prediction is at the heart of decision-making, so decisions should, overall improve. And, as decisions improve, so should productivity.
The pitfalls of prediction machines are also described. I just love the story about a chess-playing machine during the early days of AI. The machine was fed games from the great grandmasters of chess. The machine successfully analyzed static board positions and suggested good moves. Then, when the machine was programmed to play complete games, something strange happened. Early in its games, it often would sacrifice its queen with no apparent benefit. It turns out the grandmasters occasionally would sacrifice a queen when a masterful quick checkmate could follow. But, the machine could not see that sacrificing a queen without comparable reward was not a good move.
The basic premise of the book is that the cost of prediction is dropping. Prediction is at the heart of decision-making, so decisions should, overall improve. And, as decisions improve, so should productivity.
The pitfalls of prediction machines are also described. I just love the story about a chess-playing machine during the early days of AI. The machine was fed games from the great grandmasters of chess. The machine successfully analyzed static board positions and suggested good moves. Then, when the machine was programmed to play complete games, something strange happened. Early in its games, it often would sacrifice its queen with no apparent benefit. It turns out the grandmasters occasionally would sacrifice a queen when a masterful quick checkmate could follow. But, the machine could not see that sacrificing a queen without comparable reward was not a good move.