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Prediction machines : the simple economics of artificial intelligence / by Ajay Agrawal, Joshua Gans, and Avi Goldfarb.

By: Contributor(s): Material type: TextTextPublication details: Boston, Massachusetts : Harvard Business Review Press, (c)2018.Description: 1 online resource (x, 250 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781633695689
Subject(s): Genre/Form: LOC classification:
  • TA347 .P743 2018
Online resources: Available additional physical forms:
Contents:
Introduction: Machine Intelligence -- Cheap changes everything -- Prediction -- Prediction machine magic -- Why it's called intelligence -- Data is the new oil -- The new division of labor -- Decision Making -- Unpacking decisions -- The value of judgment -- Predicting judgment -- Taming complexity -- Fully automated decision making -- Tools. Deconstructing workflows -- Decomposing decisions -- Job redesign -- Strategy -- AI in the C-suite -- When AI transforms your business -- Your learning strategy -- Managing AI risk -- Society -- Beyond business.
Subject: 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.--
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Item type Current library Collection Call number URL Status Date due Barcode
Online Book (LOGIN USING YOUR MY CIU LOGIN AND PASSWORD) Online Book (LOGIN USING YOUR MY CIU LOGIN AND PASSWORD) G. Allen Fleece Library ONLINE Non-fiction TA347.78 (Browse shelf(Opens below)) Link to resource Available on1030607642

Includes bibliographies and index.

Introduction: Machine Intelligence -- Cheap changes everything -- Prediction -- Prediction machine magic -- Why it's called intelligence -- Data is the new oil -- The new division of labor -- Decision Making -- Unpacking decisions -- The value of judgment -- Predicting judgment -- Taming complexity -- Fully automated decision making -- Tools. Deconstructing workflows -- Decomposing decisions -- Job redesign -- Strategy -- AI in the C-suite -- When AI transforms your business -- Your learning strategy -- Managing AI risk -- Society -- Beyond business.

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.--

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