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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