HBR guide to AI basics for managers
(eAudiobook)

Book Cover
Average Rating
Contributors
Miller, Rich, narrator.
Kay, Cindy, narrator.
Harvard Business Review Press, issuing body.
Published
[Place of publication not identified] : Ascent Audio, 2023.
Format
eAudiobook
Edition
[First edition].
ISBN
1663722595, 9781663722591
Physical Desc
1 online resource (1 audio file (4 hr., 59 min.))
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Language
English

Notes

Participants/Performers
Read by Rich Miller, Cindy Kay.
Description
Get up to speed on AI-and start reaping the benefits now. 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; and work better with your AI experts and data scientists. Arm yourself with the advice you need to succeed on the job, with the most trusted brand in business. Packed with how-to essentials from leading experts, the HBR Guides provide smart answers to your most pressing work challenges.

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Citations

APA Citation, 7th Edition (style guide)

Miller, R., & Kay, C. (2023). HBR guide to AI basics for managers ([First edition].). Ascent Audio.

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

Miller, Rich and Cindy, Kay. 2023. HBR Guide to AI Basics for Managers. Ascent Audio.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

Miller, Rich and Cindy, Kay. HBR Guide to AI Basics for Managers Ascent Audio, 2023.

MLA Citation, 9th Edition (style guide)

Miller, Rich,, and Cindy Kay. HBR Guide to AI Basics for Managers [First edition]., Ascent Audio, 2023.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.

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3ddbe7ee-2453-bfe6-676e-60eea3744959-eng
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Grouped Work ID3ddbe7ee-2453-bfe6-676e-60eea3744959-eng
Full titlehbr guide to ai basics for managers
Authorharvard business review
Grouping Categorybook
Last Update2024-09-06 16:31:08PM
Last Indexed2024-09-25 02:46:42AM

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First LoadedSep 7, 2024
Last UsedSep 23, 2024

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First DetectedJul 29, 2024 04:08:04 PM
Last File Modification TimeSep 06, 2024 04:53:59 PM

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5050 |t 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? /|r by Emma Martinho-Truswell --|t What Every Manager Should Know About Machine Learning : A non-technical primer /|r by Mike Yeomans --|t The Three Types of AI : First, understand which technologies perform which types of tasks /|r by Thomas H. Davenport and Rajeev Ronanki --|t AI Doesn't Have to Be Too Complicated or Expensive for Your Business : Focus on data quality, not quantity /|r by Andrew Ng --|t How AI Fits into Your Data Science Team : Get over the cultural hurdles and avoid exaggerated claims /|r an interview with Hilary Mason --|t Ramp Up Your Team's Predictive Analytics Skills : Three pitfalls your team needs to avoid /|r by Eric Siegel --|t Assembling Your AI Operations Team : A top-notch model is no good if your people can't connect it to your existing systems /|r by Mark Esposito, Terence Tse, Takaai Mizuno, and Danny Goh --|t How to Spot a Machine Learning Opportunity : What do you want to predict, and do you have the data? /|r by Kathryn Hume --|t A Simple Tool for Making Decisions with AI : Use the AI Canvas /|r by Ajay Agrawal, Joshua Gans, and Avi Goldfarb --|t How to Pick the Right Automation Project : Invest in the ones that will build your organization's capabilities /|r by Bhaskar Ghosh, Rajendra Prasad, and Gayathri Pallail --|t Collaborative Intelligence : Humans and AI Are Joining Forces : They're enhancing each other's strengths /|r by H. James Wilson and Paul R. Daugherty --|t How to Get Employees to Embrace AI : The sooner resisters get onboard, the sooner you will see results /|r by Brad Power --|t A Better Way to Onboard AI : Understand it as a tool to assist people rather than replace them /|r by Boris Babic, Daniel L. Chen, Theodoros Evgeniou, and Anne-Laure Fayard --|t Managing AI Decision-Making Tools : Humans still need to be involved : This framework will help you determine when and how /|t by Michael Ross
5050 |a And James Taylor --|t Your Company's Algorithms Will Go Wrong : Have a Plan in Place : An AI designed to do X will eventually fail to do X /|r by Roman V. Yampolskiy --|t A Practical Guide to Ethical AI : AI doesn't just scale solutions -- it also scales risk /|r by Reid Blackman --|t AI Can Help Address Inequity -- If Companies Earn Users' Trust : A case from Airbnb shows how good algorithms can have negative effects /|r by Shunyuan Zhang, Kannan Srinivasan, Param Vir Singh, and Nitin Mehta --|t Take Action to Mitigate Ethical Risks : It starts with three critical conversations /|r 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 /|r by Jonathon Reilly --|t The Power of Natural Language Processing : NLP can help companies with brainstorming, summarizing, and researching. /|r by Ross Gruetzemacher --|t Reinforcement Learning Is Ready for Business : Learning through trial and error can lead to more creative solutions /|r by Kathryn Hume and Matthew E. Taylor.
5110 |a Read by Rich Miller, Cindy Kay.
520 |a Get up to speed on AI-and start reaping the benefits now. 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; and work better with your AI experts and data scientists. Arm yourself with the advice you need to succeed on the job, with the most trusted brand in business. Packed with how-to essentials from leading experts, the HBR Guides provide smart answers to your most pressing work challenges.
5880 |a Online resource; title from title details screen (O'Reilly, viewed January 10, 2023).
650 0|a Artificial intelligence.|0 http://id.loc.gov/authorities/subjects/sh85008180
650 0|a Management|x Technological innovations.
650 0|a Business enterprises|x Information technology|x Management.
650 0|a Industrial management.|0 http://id.loc.gov/authorities/subjects/sh85065889
650 0|a Success in business.|0 http://id.loc.gov/authorities/subjects/sh85129589
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7001 |a Kay, Cindy,|e narrator.|0 http://id.loc.gov/authorities/names/no2019162136
7102 |a Harvard Business Review Press,|e issuing body.|0 http://id.loc.gov/authorities/names/no2011025585
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