Prediction machines the simple economics of artificial intelligence

The idea of artificial intelligence--job-killing robots, self-driving cars, and self-managing organizations--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 art...

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Bibliographic Details
Main Authors: Agrawal, Ajay (Author), Gans, Joshua, 1968- (Author), Goldfarb, Avi (Author)
Format: Books Print Book
Language:English
Published: Boston, Massachusetts : Harvard Business Review Press, [2018]
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100 1 |a Agrawal, Ajay,  |e author. 
245 1 0 |a Prediction machines :  |b the simple economics of artificial intelligence /  |c Ajay Agrawal, Joshua Gans, and Avi Goldfarb. 
264 1 |a Boston, Massachusetts :  |b Harvard Business Review Press,  |c [2018] 
300 |a x, 250 pages :  |b illustrations ;  |c 25 cm 
336 |a text  |b txt  |2 rdacontent 
337 |a unmediated  |b n  |2 rdamedia 
338 |a volume  |b nc  |2 rdacarrier 
386 |m Occupation/field of activity group:  |n occ  |a University and college faculty members  |2 lcdgt 
386 |m Gender group:  |n gdr  |a Men  |2 lcdgt 
504 |a Includes bibliographical references and index. 
520 |a The idea of artificial intelligence--job-killing robots, self-driving cars, and self-managing organizations--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. --  |c Provided by publisher. 
505 0 0 |t Introduction: Machine Intelligence ;  |t Cheap changes everything --  |g Part One:  |t Prediction.  |t Prediction machine magic ;  |t Why it's called intelligence ;  |t Data is the new oil ;  |t The new division of labor --  |g Part Two:  |t Decision Making.  |t Unpacking decisions ;  |t The value of judgment ;  |t Predicting judgment ;  |t Taming complexity ;  |t Fully automated decision making --  |g Part Three:  |t Tools. Deconstructing workflows ;  |t Decomposing decisions ;  |t Job redesign --  |g Part Four:  |t Strategy.  |t AI in the C-suite ;  |t When AI transforms your business ;  |t Your learning strategy ;  |t Managing AI risk --  |g Part Five:  |t Society.  |t Beyond business. 
650 0 |a Artificial intelligence  |x Economic aspects. 
650 0 |a Decision making  |x Statistical methods. 
650 0 |a Forecasting  |x Statistical methods. 
700 1 |a Gans, Joshua,  |d 1968-  |e author. 
700 1 |a Goldfarb, Avi,  |e author. 
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