The Great AI Paradox

by  Brian Bergstein,  MIT Technology Review

Don’t worry about supersmart AI eliminating all the jobs. That’s just a distraction from the problems even relatively dumb computers are causing.

Concerns about artificial intelligence (AI) making jobs or even humans obsolete distract from the need to assume more responsibility for the impact of current automation and addressing the concentration of power in the technology industry.

To really see what’s going on, we have to be clear on what has been achieved—and what remains far from solved—in artificial intelligence.

The most stunning developments in computing over the past few years—cars that drive themselves, machines that accurately recognize images and speech, computers that beat the most brilliant human players of complex games like Go—stem from breakthroughs in a particular branch of AI: adaptive machine learning. As the University of Toronto computer scientist Hector Levesque puts it in his book Common Sense, the Turing Test, and the Quest for Real AI, the idea behind adaptive machine learning is to “get a computer system to learn some intelligent behavior by training it on massive amounts of data.”

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.

For example, 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.

Although experts contend common sense is still beyond AI, which limits the likelihood that machines one day actually will think. Other scientists believe the arrival of truly intelligent machines is inevitable, given computers’ tendency to improve exponentially.

Despite these predictions, far more pressing are issues of things going awry with current AI and computers, such as automated cyberattacks and computerized decision-making that is based on biased and discriminatory data. Technology publisher Tim O’Reilly makes the argument that companies increasingly automate simply to save money and maximize returns for investors, with resultant savings not poured back into job creation, which goes against long-term corporate interests.  This is an intriguing discussion of issues in AI and its future.

DCL: I was a graduate student at MIT when McCarthy and Minsky were starting out. We had endless seminar discussions on the topics mentioned in this article 65 years ago!  In the 1950’s Alan Turing proposed the question “Can Machines Think” in his article “Computing Machinery and Intelligence”. We still don’t have an answer!