Superintelligence

The Prospect of Superintelligence

At Dartmouth College in the summer of 1956, a group of scientists sat down to chart a new course for humankind. They began with the notion that machines could replicate aspects of human intelligence. Their effort evolved in fits and starts. Rule-based programs, or “expert systems,” flourished in the 1980s, and the promise of artificial intelligence (AI) seemed bright. Then progress waned and funding receded. In the 1990s, with the advent of “genetic algorithms” and “neural networks,” the idea took off again.

One measure of the power of AI is in how well specifically designed machines play games like chess, bridge, poker Scrabble, Jeopardy and Go. A machine with effective algorithms will prevail over the best human Go player in about a decade. From games, AI’s applications extend to hearing aids, speech and face recognition, navigation, diagnostics, scheduling, inventory management and an expanding class of industrial robots.

Despite AI’s growing popularity and uses, signs of its limitations are emerging. In the “Flash Crash” of 2010, algorithmic traders inadvertently created a downward spiral that cost the market a trillion dollars...