THE INFORMATION AGE IS ONLY BEGINNING:

Since machines can process superhuman amounts of data, you can see why they might drive more safely than people in most circumstances, and why they can vanquish Go champions. It's also why computers are getting even better at things that are outright impossible for people, such as correlating your genome and dozens of other biological variables with the drugs likeliest to cure your cancer.

Even so, all this is a small part of what could reasonably be defined as real artificial intelligence. Patrick Winston, a professor of  AI and computer science at MIT, says it would be more helpful to describe the developments of the past few years as having occurred in "computational statistics" rather than in AI. One of the leading researchers in the field, Yann LeCun, Facebook's director of AI, said at a Future of Work conference at MIT in November that machines are far from having "the essence of intelligence." That includes the ability to understand the physical world well enough to make predictions about basic aspects of it--to observe one thing and then use background knowledge to figure out what other things must also be true. Another way of saying this is that machines don't have common sense.

The computer that wins at Go is analyzing data for patterns. It has no idea it's playing Go as opposed to golf.

This isn't just a semantic quibble. There's a big difference between a machine that displays "intelligent behavior," no matter how useful that behavior is, and one that is actually intelligent. Now, let's grant that the definition of intelligence is murky. And as computers become more powerful, it's tempting to move the goalposts farther away and redefine intelligence so that it remains something machines can't yet be said to possess.

But even so, come on: the computer that wins at Go is analyzing data for patterns. It has no idea it's playing Go as opposed to golf, or what would happen if more than half of a Go board was pushed beyond the edge of a table. When you ask Amazon's Alexa to reserve you a table at a restaurant you name, its voice recognition system, made very accurate by machine learning, saves you the time of entering a request in Open Table's reservation system. But Alexa doesn't know what a restaurant is or what eating is. If you asked it to book you a table for two at 6 p.m. at the Mayo Clinic, it would try.

Is it possible to give machines the power to think, as John McCarthy, Marvin Minsky, and other originators of AI intended 60 years ago? Doing that, Levesque explains, would require imbuing computers with common sense and the ability to flexibly make use of background knowledge about the world. Maybe it's possible. But there's no clear path to making it happen. That kind of work is separate enough from the machine-learning breakthroughs of recent years to go by a different name: GOFAI, short for "good old-fashioned artificial intelligence."

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