Prediction machines : (Record no. 10092)

MARC details
000 -LEADER
fixed length control field 02816cam a2200325 i 4500
001 - CONTROL NUMBER
control field 20147040
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220527090159.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 171108s2018 mau 000 0 eng c
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 2017049211
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781633695672
Qualifying information (hardcover : alk. paper)
040 ## - CATALOGING SOURCE
Original cataloging agency MH/DLC
Language of cataloging eng
Description conventions rda
Transcribing agency MH
Modifying agency DLC
042 ## - AUTHENTICATION CODE
Authentication code pcc
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA347.A78
Item number A385 2018
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 658.0563
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Agrawal, Ajay,
Relator term author.
245 10 - TITLE STATEMENT
Title Prediction machines :
Remainder of title the simple economics of artificial intelligence /
Statement of responsibility, etc. Ajay Agrawal, Joshua Gans, Avi Goldfarb.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Boston, Mass.
Name of publisher, distributor, etc. HBR
Date of publication, distribution, etc. 2018
300 ## - PHYSICAL DESCRIPTION
Extent x, 250 pages ;
Dimensions 25 cm
505 0# - 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 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Artificial intelligence
General subdivision Economic aspects.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Decision making
General subdivision Statistical methods.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Forecasting
General subdivision Statistical methods.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Gans, Joshua,
Dates associated with a name 1968-
Relator term author.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Goldfarb, Avi,
Relator term author.
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
a 7
b cbc
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e ecip
f 20
g y-gencatlg
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection Home library Current library Shelving location Date acquired Source of acquisition Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification   Not For Loan Non-fiction Tan Tao University Tan Tao University General Stacks 10/14/2019 Gift of Asian Foundation   658.0563 AS-2019-0149 10/14/2019 10/14/2019 Books
    Dewey Decimal Classification     Non-fiction Tan Tao University Tan Tao University General Stacks 02/01/2021 Gift of the ASIA   658.0563 AS-2020-0136 02/01/2021 02/01/2021 Books

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