Description: The idea of artificial intelligence - job-killing robots, self-driving cars, and self-managing organisations - captures the imagination, evoking a combination of wonder and dread for those of us who will have to deal with the consequences. But what if it's not quite so complicated? The real job of artificial intelligence, argue these three eminent economists, is to lower the cost of prediction. And once you start talking about costs, you can use some well-established economics to cut through the hype. The constant challenge for all managers is to make decisions under uncertainty. And AI contributes by making knowing what's coming in the future cheaper and more certain. But decision making has another component: judgment, which is firmly in the realm of humans, not machines. Making prediction cheaper means that we can make more predictions more accurately and assess them with our better (human) judgment. Once managers can separate tasks into components of prediction and judgment, we can begin to understand how to optimize the interface between humans and machines. More than just an account of AI's powerful capabilities, Prediction Machines shows managers how they can most effectively leverage AI, disrupting business as usual only where required, and provides businesses with a toolkit to navigate the coming wave of challenges and opportunities.
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EAN: 9781633695672
UPC: 9781633695672
ISBN: 9781633695672
MPN: N/A
Book Title: Prediction Machines: The Simple Economics of Artif
Item Length: 23.6 cm
Item Weight: 0.38 kg
Item Height: 235 mm
Item Width: 156 mm
Author: Joshua Gans, Avi Goldfarb, A. Agrawal
Publication Name: Prediction Machines: the Simple Economics of Artificial Intelligence
Format: Hardcover
Language: English
Publisher: Harvard Business Review Press
Subject: Government, Computer Science, Management, Business
Publication Year: 2018
Type: Textbook
Number of Pages: 256 Pages