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HBR guide to AI basics for managers /
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 com...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , |
| Formato: | Electrónico Audiom |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified] :
Ascent Audio,
2023.
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| Edición: | [First edition]. |
| Colección: | Harvard business review guides.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- 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.