000 -LEADER |
fixed length control field |
03040nam a2200409 a 4500 |
001 - CONTROL NUMBER |
control field |
00004887 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
ES-MaONT |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20211006062601.0 |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
fixed length control field |
tb |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
180703s2018 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 |
024 ## - OTHER STANDARD IDENTIFIER |
Additional codes following the standard number or code |
. |
040 ## - CATALOGING SOURCE |
Description conventions |
rda |
Modifying agency |
BUS |
Transcribing agency |
CDO |
080 ## - UNIVERSAL DECIMAL CLASSIFICATION NUMBER |
Universal Decimal Classification number |
004.8 |
080 ## - UNIVERSAL DECIMAL CLASSIFICATION NUMBER |
Universal Decimal Classification number |
519.216.3 |
080 ## - UNIVERSAL DECIMAL CLASSIFICATION NUMBER |
Universal Decimal Classification number |
519.816 |
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
658/.0563 |
Edition number |
23 |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Agrawal, Ajay |
9 (RLIN) |
2650 |
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 |
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
Place of production, publication, distribution, manufacture |
Boston, Massachusetts : |
Name of producer, publisher, distributor, manufacturer |
Harvard Business Review Press, |
Date of production, publication, distribution, manufacture, or copyright notice |
[2018] |
264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
Date of production, publication, distribution, manufacture, or copyright notice |
2018 |
300 ## - PHYSICAL DESCRIPTION |
Extent |
X, 250 p. : |
Other physical details |
gráf. ; |
Dimensions |
25 cm |
336 ## - CONTENT TYPE |
Content type term |
texto (visual) |
Source |
isbdcontent |
337 ## - MEDIA TYPE |
Media type term |
sin mediación |
Source |
isbdmedia |
338 ## - CARRIER TYPE |
Carrier type term |
volumen |
Carrier type code |
nc [ |
Source |
rdacarrier] |
500 ## - GENERAL NOTE |
General note |
MSC 68Txx ; 90B50 ; 60G25 |
504 ## - BIBLIOGRAPHY, ETC. NOTE |
Bibliography, etc. note |
Incluye referencias bibliográficas (p. 225-238) e índice |
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.-- |
Assigning source |
Provided by publisher |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Tecnologías habilitadoras digitales |
9 (RLIN) |
18 |
653 ## - INDEX TERM--UNCONTROLLED |
Uncontrolled term |
Inteligencia artificial |
700 ## - ADDED ENTRY--PERSONAL NAME |
Personal name |
Gans, Joshua |
Dates associated with a name |
(1968-) |
9 (RLIN) |
2651 |
700 ## - ADDED ENTRY--PERSONAL NAME |
Personal name |
Goldfarb, Avi |
9 (RLIN) |
2652 |
856 ## - ELECTRONIC LOCATION AND ACCESS |
Uniform Resource Identifier |
<a href=".">.</a> |
Nonpublic note |
Restringido |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
|
Koha item type |
Libros |