Prediction machines : (Record no. 24900)

MARC details
000 -LEADER
fixed length control field 02767nam a22003258i 4500
001 - CONTROL NUMBER
control field 20147040
003 - CONTROL NUMBER IDENTIFIER
control field IIITD
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240501020003.0
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
040 ## - CATALOGING SOURCE
Original cataloging agency MH/DLC
Language of cataloging eng
Description conventions rda
Transcribing agency MH
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
Item number AGR-P
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Agrawal, Ajay
245 10 - TITLE STATEMENT
Title Prediction machines :
Remainder of title the simple economics of artificial intelligence
Statement of responsibility, etc by Ajay Agrawal, Joshua Gans, and Avi Goldfarb.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Boston :
Name of publisher, distributor, etc HBR Press,
Date of publication, distribution, etc ©2018.
300 ## - PHYSICAL DESCRIPTION
Extent x, 250 p.;
Dimensions 24 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 as entry element Artificial intelligence
General subdivision Economic aspects.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Decision making
General subdivision Statistical methods.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Forecasting
General subdivision Statistical methods.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Gans, Joshua
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Goldfarb, Avi
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
a 7
b cbc
c orignew
d 1
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
Koha issues (borrowed), all copies 1
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Bill No. Bill Date Cost, normal purchase price PO No. PO Date Total Checkouts Full call number Barcode Date last seen Cost, replacement price Price effective from Vendor/Supplier Koha item type Date checked out Public note
    Dewey Decimal Classification     Management IIITD IIITD General Stacks 19/06/2018 IN-5080 2018-06-13 1169.00 408-0260319-4792354 2018-06-13   658.0563 AGR-P 008922 19/06/2018 1250.00 19/06/2018 Amazon.in Books    
    Dewey Decimal Classification     Management IIITD IIITD Reference 02/04/2024 1170197 2024-03-21 945 Email2-14-03-2024 2024-03-14 1 CB 658.0563 AGR-P 012745 06/05/2024 1350 02/04/2024 Atlantic Publishers & Distributors (P) Ltd. Books 30/04/2024 DBT Project Grant
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