MARC details
| 000 -LEADER |
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| fixed length control field |
05728cam a2200457 i 4500 |
| CONTROL NUMBER |
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| control field |
22736080 |
| CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20250610123353.0 |
| FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
220723s2023 mau b 001 0 eng |
| LIBRARY OF CONGRESS CONTROL NUMBER |
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| LC control number |
2022030290 |
| INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781647824433 |
| Qualifying information |
(paperback) |
| INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| Canceled/invalid ISBN |
9781647824440 |
| Qualifying information |
(epub) |
| CATALOGING SOURCE |
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| Original cataloging agency |
MH/DLC |
| Language of cataloging |
eng |
| Description conventions |
rda |
| Transcribing agency |
DLC |
| Modifying agency |
DLC |
| AUTHENTICATION CODE |
|---|
| Authentication code |
pcc |
| LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
HD30.2 |
| Item number |
.H325 2023 |
| DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
658.4038 |
| Item number |
HAR/H |
| TITLE STATEMENT |
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| Title |
HBR guide to AI basics for managers / |
| Statement of responsibility, etc. |
Harvard Business Review. |
| VARYING FORM OF TITLE |
|---|
| Title proper/short title |
Harvard business review guide to AI basics for managers |
| VARYING FORM OF TITLE |
|---|
| Title proper/short title |
AI basics for managers |
| VARYING FORM OF TITLE |
|---|
| Title proper/short title |
Artificial intelligence basics for managers |
| 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 |
[2023] |
| PHYSICAL DESCRIPTION |
|---|
| Extent |
xiii, 252 pages ; |
| Dimensions |
23 cm. |
| CONTENT TYPE |
|---|
| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent |
| MEDIA TYPE |
|---|
| Media type term |
unmediated |
| Media type code |
n |
| Source |
rdamedia |
| CARRIER TYPE |
|---|
| Carrier type term |
volume |
| Carrier type code |
nc |
| Source |
rdacarrier |
| SERIES STATEMENT |
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| Series statement |
HBR guides |
| GENERAL NOTE |
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| General note |
Includes bibliographical references and index. |
| FORMATTED CONTENTS NOTE |
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| Title |
Three Questions About AI That Every Employee Should Be Able to Answer : How does it work, what is it good at, and what should it never do? / |
| Statement of responsibility |
by Emma Martinho-Truswell -- |
| Title |
What Every Manager Should Know About Machine Learning : A non-technical primer / |
| Statement of responsibility |
by Mike Yeomans -- |
| Title |
The Three Types of AI : First, understand which technologies perform which types of tasks / |
| Statement of responsibility |
by Thomas H. Davenport and Rajeev Ronanki -- |
| Title |
AI Doesn't Have to Be Too Complicated or Expensive for Your Business : Focus on data quality, not quantity / |
| Statement of responsibility |
by Andrew Ng -- |
| Title |
How AI Fits into Your Data Science Team : Get over the cultural hurdles and avoid exaggerated claims / |
| Statement of responsibility |
an interview with Hilary Mason -- |
| Title |
Ramp Up Your Team's Predictive Analytics Skills : Three pitfalls your team needs to avoid / |
| Statement of responsibility |
by Eric Siegel -- |
| Title |
Assembling Your AI Operations Team : A top-notch model is no good if your people can't connect it to your existing systems / |
| Statement of responsibility |
by Mark Esposito, Terence Tse, Takaai Mizuno, and Danny Goh -- |
| Title |
How to Spot a Machine Learning Opportunity : What do you want to predict, and do you have the data? / |
| Statement of responsibility |
by Kathryn Hume -- |
| Title |
A Simple Tool for Making Decisions with AI : Use the AI Canvas / |
| Statement of responsibility |
by Ajay Agrawal, Joshua Gans, and Avi Goldfarb -- |
| Title |
How to Pick the Right Automation Project : Invest in the ones that will build your organization's capabilities / |
| Statement of responsibility |
by Bhaskar Ghosh, Rajendra Prasad, and Gayathri Pallail -- |
| Title |
Collaborative Intelligence : Humans and AI Are Joining Forces : They're enhancing each other's strengths / |
| Statement of responsibility |
by H. James Wilson and Paul R. Daugherty -- |
| Title |
How to Get Employees to Embrace AI : The sooner resisters get onboard, the sooner you will see results / |
| Statement of responsibility |
by Brad Power -- |
| Title |
A Better Way to Onboard AI : Understand it as a tool to assist people rather than replace them / |
| Statement of responsibility |
by Boris Babic, Daniel L. Chen, Theodoros Evgeniou, and Anne-Laure Fayard -- |
| Title |
Managing AI Decision-Making Tools : Humans still need to be involved : This framework will help you determine when and how / |
| -- |
by Michael Ross and James Taylor -- |
| -- |
Your Company's Algorithms Will Go Wrong : Have a Plan in Place : An AI designed to do X will eventually fail to do X / |
| Statement of responsibility |
by Roman V. Yampolskiy -- |
| Title |
A Practical Guide to Ethical AI : AI doesn't just scale solutions - it also scales risk / |
| Statement of responsibility |
by Reid Blackman -- |
| Title |
AI Can Help Address Inequity - If Companies Earn Users' Trust : A case from Airbnb shows how good algorithms can have negative effects / |
| Statement of responsibility |
by Shunyuan Zhang, Kannan Srinivasan, Param Vir Singh, and Nitin Mehta -- |
| Title |
Take Action to Mitigate Ethical Risks : It starts with three critical conversations / |
| Statement of responsibility |
by Reid Blackman and Beena Ammanath -- How No-Code Platforms Can Bring AI to Small and Midsize Businesses : Three features to look for as you consider the right tool for your company / |
| -- |
by Jonathon Reilly -- |
| Title |
The Power of Natural Language Processing : NLP can help companies with brainstorming, summarizing, and researching. / |
| Statement of responsibility |
by Ross Gruetzemacher -- |
| Title |
Reinforcement Learning Is Ready for Business : Learning through trial and error can lead to more creative solutions / |
| Statement of responsibility |
by Kathryn Hume and Matthew E. Taylor. |
| SUMMARY, ETC. |
|---|
| Summary, etc. |
"From product design and financial modeling to performance management and hiring decisions-artificial intelligence and machine learning are becoming everyday tools for managers at businesses of all sizes. But the rewards of every AI system come with risks-and if you don't understand how to make sense of them, you're not going to make the right decisions. Whether you want to get up to speed quickly, could just use a refresher, or are working with an AI expert for the first time, HBR Guide to AI Basics for Managers will give you the information and skills you need. You'll learn how to: understand key terms and concepts; identify which of your projects and processes would benefit from an AI approach; deal with ethical issues before they come up; hire the best AI vendors; run small experiments; work better with your AI experts and data scientists"-- |
| Assigning source |
Provided by publisher. |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Artificial intelligence. |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Management |
| General subdivision |
Technological innovations. |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Business enterprises |
| General subdivision |
Information technology |
| -- |
Management. |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Industrial management. |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Success in business. |
| ADDED ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
Harvard Business Review Press, |
| Relator term |
issuing body. |
| ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Online version: |
| Title |
HBR guide to AI basics for managers |
| Place, publisher, and date of publication |
Boston, Massachusetts : Harvard Business Review Press, [2023] |
| International Standard Book Number |
9781647824440 |
| Record control number |
(DLC) 2022030291 |
| SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Harvard business review guides. |
| LOCAL DATA ELEMENT F, LDF (RLIN) |
|---|
| a |
7 |
| b |
cbc |
| c |
orignew |
| d |
1 |
| e |
ecip |
| f |
20 |
| g |
y-gencatlg |
| ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Books |
| Classification part |
658.4038 |
| Item part |
HAR/H |
| Call number prefix |
658.4038 |
| Call number suffix |
HAR/H |
