In part III of this series, we’ll be looking at the role of data cleanliness, data models, and process governance. The tools and techniques required for the management of intelligent tools at scale are still in their infancy.
This is part II in a series that started last week. “The one thing to keep in mind with early experiments is that improving a single process with an intelligent machine is profoundly different from managing at scale.” - John Sumser
“From an operations perspective, the most important thing to know about intelligent software is that the narrower the problem, the better it works. As a result, a good deal of energy is spent in development trying to break big problems into tiny little pieces.” - John Sumser
There is a path to realize the full potential of AI and intelligent software but it isn’t one made with technology ideas engineered for a different time and reality.
“How to present predictive information and user interface is also changing. The essence of traditional interfaces is a deep emphasis on clarity (or intuitiveness). One look at the interface tells you what to do. That doesn’t work with likelihoods.” - John Sumser
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