Artificial intelligence (AI) promises to grow the economy and improve our lives, but along with these benefits, it also brings new risks that society is grappling with. How can we be sure this new technology is not just innovative and helpful, but also trustworthy, unbiased, and resilient in the face of attack? We talked with NIST’s Information Technology Lab director Chuck Romine to learn how measurement science can help provide answers.
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How would you define AI? How is it different from regular computing?
One of the challenges with defining AI is that if you put 10 people in a room, you get 11 different definitions. It’s a moving target. We haven’t converged yet on exactly what the definition is, but I think NIST can play an important role here. What we can’t do, and what we never do, is go off in a room and think deep thoughts and say we have the definition. We engage the community.
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Narrow AI
Narrow AI uses algorithms to automate things people used to have to learn slowly and practice manually.
Getting algorithms out of people's heads (e.g., map reading) and into software (e.g., Google Maps) makes a lot of sense. It collapses the learning curve to minutes instead of hours or days, and increases accuracy.
I've been doing this for over a decade in Six Sigma SPC software.
Big AI will do great things like facial recognition and medical diagnosis.
Narrow AI can help the novice jumpstart their learning and application. And we can do it now.
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