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HBR guide to AI basics for managers
Title
HBR guide to AI basics for managers / Harvard Business Review.
ISBN
9781647824440
1647824443
9781647824433
Publication
Boston, Massachusetts : Harvard Business Review Press, [2023]
Physical Description
1 online resource.
Local Notes
Access is available to the Yale community.
Notes
Includes index.
Access and use
Access restricted by licensing agreement.
Summary
"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"-- Provided by publisher.
Variant and related titles
Harvard business review guide to AI basics for managers
AI basics for managers
Artificial intelligence basics for managers
EBSCO Harvard business publishing collection. OCLC KB.
Other formats
Print version: HBR guide to AI basics for managers Boston, Massachusetts : Harvard Business Review Press, [2023]
Format
Books / Online
Language
English
Added to Catalog
February 29, 2024
Series
HBR guides
Contents
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? / by Emma Martinho-Truswell
What Every Manager Should Know About Machine Learning : A non-technical primer / by Mike Yeomans
The Three Types of AI : First, understand which technologies perform which types of tasks / by Thomas H. Davenport and Rajeev Ronanki
AI Doesn't Have to Be Too Complicated or Expensive for Your Business : Focus on data quality, not quantity / by Andrew Ng
How AI Fits into Your Data Science Team : Get over the cultural hurdles and avoid exaggerated claims / an interview with Hilary Mason
Ramp Up Your Team's Predictive Analytics Skills : Three pitfalls your team needs to avoid / by Eric Siegel
Assembling Your AI Operations Team : A top-notch model is no good if your people can't connect it to your existing systems / by Mark Esposito, Terence Tse, Takaai Mizuno, and Danny Goh
How to Spot a Machine Learning Opportunity : What do you want to predict, and do you have the data? / by Kathryn Hume
A Simple Tool for Making Decisions with AI : Use the AI Canvas / by Ajay Agrawal, Joshua Gans, and Avi Goldfarb
How to Pick the Right Automation Project : Invest in the ones that will build your organization's capabilities / by Bhaskar Ghosh, Rajendra Prasad, and Gayathri Pallail
Collaborative Intelligence : Humans and AI Are Joining Forces : They're enhancing each other's strengths / by H. James Wilson and Paul R. Daugherty
How to Get Employees to Embrace AI : The sooner resisters get onboard, the sooner you will see results / by Brad Power
A Better Way to Onboard AI : Understand it as a tool to assist people rather than replace them / by Boris Babic, Daniel L. Chen, Theodoros Evgeniou, and Anne-Laure Fayard
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 / by Roman V. Yampolskiy
A Practical Guide to Ethical AI : AI doesn't just scale solutions
it also scales risk / by Reid Blackman
AI Can Help Address Inequity
If Companies Earn Users' Trust : A case from Airbnb shows how good algorithms can have negative effects / by Shunyuan Zhang, Kannan Srinivasan, Param Vir Singh, and Nitin Mehta
Take Action to Mitigate Ethical Risks : It starts with three critical conversations / 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
The Power of Natural Language Processing : NLP can help companies with brainstorming, summarizing, and researching. / by Ross Gruetzemacher
Reinforcement Learning Is Ready for Business : Learning through trial and error can lead to more creative solutions / by Kathryn Hume and Matthew E. Taylor.
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Harvard Business Review Press, issuing body.
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