Building Intelligent Machines

Cautionary review of intelligent machines.   Are they thinking like people, or just with people?  And what are the implications for value and bias?

AI savants, recognizing bias, and building machines that think like people

Despite impressive advances, three speakers at EmTech Digital show how far there is to go in the AI world.  by David Rotman  March 26, 2018  in MIT Tech Review.

Even with all the amazing examples of progress in artificial intelligence, such as self-driving cars and the victories of AlphaGo, the technology is still very narrow in its accomplishments and far from autonomous. Indeed, says Oren Etzioni, chief executive officer of the Allen Institute for Artificial Intelligence, today’s machine-learning systems are “AI savants.”

Etzioni, speaking today at MIT Technology Review’s annual EmTech Digital conference in San Francisco, explained that self-driving cars and speech recognition are based on machine learning. And even today, he said, 99 percent of machine learning is based on human work.

Etzioni pointed out that machine learning needs large amounts of data, all of which needs to be labeled: this is a dog; this is a cat. And then people need to supply the appropriate algorithms. All this relies on manual labor.  ... "