MARC details
| 000 -LEADER |
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| fixed length control field |
02982cam a2200361 i 4500 |
| 001 - CONTROL NUMBER |
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| control field |
20147040 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20220707042131.0 |
| 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 |
22 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Agrawal, Ajay, |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Prediction machines: 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] |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
x, 250 pages ; |
| Dimensions |
25 cm |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
unmediated |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
volume |
| Source |
rdacarrier |
| 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 |
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 |
| 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 |
| Suppress in OPAC |
No |