Dimitry Malioutov can’t say much about what he built.
As a research scientist at IBM, Malioutov spends part of his time building machine learning systems that solve difficult problems faced by IBM’s corporate clients. One such program was meant for a large insurance corporation. It was a challenging assignment, requiring a sophisticated algorithm. When it came time to describe the results to his client, though, there was a wrinkle. “We couldn’t explain the model to them because they didn’t have the training in machine learning.”
In fact, it may not have helped even if they were machine learning experts. That’s because the model was an artificial neural network, a program that takes in a given type of data—in this case, the insurance company’s customer records—and finds patterns in them. These networks have been in practical use for over half a century, but lately they’ve seen a resurgence, powering breakthroughs in everything from speech recognition and language translation to Go-playing robots and self-driving cars…
Source: Human and Artificial Intelligence May Be Equally Impossible to Understand
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