Prediction Machines : The Simple Economics of Artificial Intelligence (Record no. 296712)

MARC details
000 -LEADER
fixed length control field 02399nam a22001697a 4500
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781633695672
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 658.0563 AGR-P
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Ajay Agrawal
245 ## - TITLE STATEMENT
Title Prediction Machines : The Simple Economics of Artificial Intelligence
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Boston, Massachusetts
Name of publisher, distributor, etc. Harvard Business Review Press
Date of publication, distribution, etc. 2018
300 ## - PHYSICAL DESCRIPTION
Extent x, 250 pages ; 25 cm
505 ## - FORMATTED CONTENTS NOTE
Formatted contents note Cheap changes everything -- The magic of prediction -- Why it's called intelligence -- Data is the new oil -- The new division of labor -- Unpacking decisions -- The value of judgment -- Taming complexity -- What machines can learn -- Fully automated decision-making -- Deconstructing workflows -- Decomposing decisions -- Job redesign -- AI in the C-suite -- When AI transforms your business -- Managing AI risk -- Beyond business.
520 ## - SUMMARY, ETC.
Summary, etc. 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.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Artificial intelligence -- Economic aspects. Decision making -- Statistical methods. Forecasting -- Statistical methods.
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Joshua Gans; Avi Goldfarb
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Book
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Shelving location Date acquired Total Checkouts Full call number Barcode Date last seen Date last checked out Price effective from Koha item type
        Dept. of Computational Biology and Bioinformatics Dept. of Computational Biology and Bioinformatics Processing Center 22/06/2018 1 658.0563 AGR-P DCB3433 26/02/2019 28/06/2018 22/06/2018 Book
        Dept. of Futures Studies Dept. of Futures Studies Processing Center 13/12/2019   658.0563 AGR DFS4287 13/12/2019   13/12/2019 Book