MIT SMR: How to Succeed With AI Augmentation

For all the remarkable things that machine learning and advanced analytics can do, there are scores of things that AI-enabled machines still can't do - at least not reliably enough on their own in the real world of business. That doesn't mean you can afford to wait to take advantage of AI. Rather, it means designing AI applications that leverage what people and machines each do best, and how they can most effectively work together. In their new book, Working With AI: Real Stories of Human-Machine Collaboration, authors Thomas H. Davenport and Steven M. Miller draw on 29 detailed examples of jobs and work settings in which humans are already working day to day with AI-enabled systems and automation.