“Doomsayers never go out of business because of inherent fear of the future,” says Garry Kasparov. Kasparov rose to fame as a world champion chess player representing the former Soviet Union. In recent years, he’s become known as a leading dissident and critic of Russian president Vladimir Putin. But he’s also a champion of technology. Which explains what he was doing at The New Yorker’s annual TechFest earlier this month. “The process of adaption of new tools and disruption has been going on for centuries,” he points out. In its day, the invention of the printing press was disruptive, too, after all. His view was echoed by fellow panelist Daniela Rus . “People fall into two camps about technology, says Rus– the optimists or the “apocalyptic worrywarts.”
There’s no question which camp she belongs to given her position as director of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). “Some people ask when robots will take over their jobs. It’s important to understand what technology can and cannot do.” Robots and AI are just tools, she adds, neither inherently good nor bad. “Because of technology people are living longer, so they have more years to complain about it,” adds Kasparov. “We need to discuss these issues without anxiety.”
It’s a tall order.
Kasparov deplores the idea that there should be any dichotomy between man and machine at all. And few people have more of an appreciation of what artificial intelligence can do, having lost a famous match to IBM’s Deep Blue.
“When I lost our rematch in 1997, it was hailed by many as a momentous occasion for human technology, on par with the Wright brothers’ first flight or the moon landing,” he told Fortune , “Of course, I didn’t feel so enthusiastic about it myself, but as I licked my wounds I realized that while the era of human versus intelligent machine was ending in chess, it was only getting started in every other aspect of our lives.”
Deep Blue could look at 200 million positions per second compared to a chess master’s two or three. Today, Deep Blue would be considered outdated; a chess app on a smartphone has considerably more power.
“Today’s machines are designed to do predictable work in a predictable environment,” Rus told TechFest attendees, “They’re limited in adaptability and reasoning. AI can assimilate data and do much better at it than humans. But they can only do what they are programmed to do.” She’s quick to emphasize that artificial intelligence has built-in limitations: “What does it mean for machines to understand and act? Machines can recognize a water bottle but they can’t tell you what it contains or what it’s used for.”
On the other hand, she adds, thanks to AI, robots are now capable of acting more like humans even if they can’t think like humans – and not just humans. Rus notes that innovations in design have allowed for more flexible, lighter-weight robots like a robot fish she’s invented which can swim with a school of real fish while it monitors their behavior in real time.
But it’s robots’ increasing capacity to mimic organisms physically and cognitively that has many people scared. Although most Americans may not be apocalyptic worrywarts, they have grave reservations about automation. They’re more disposed toward driverless vehicles and robot caregivers, but there’s a limit how much innovation they’re willing to embrace.
Wall Street loves automation – it saves companies bundlers of money (think of how many bank tellers have been replaced by ATMs) — but what happens to the displaced workers?
If technological advances can’t be stopped – and few people would say they should be – then what can be done to prepare for the inevitable disruption and cushion the blow that it could cause? Nobody predicted the phenomenon of social media fifteen years ago, Kasparov says, but it resulted in the creation of hundreds of thousands of new jobs that could never have been foreseen.
In the short run, both Kasparov and Rus call for educating and retraining dislocated workers. They point out that many software jobs don’t require a college education. Even workers used to manual labor can be retrained for high tech jobs. Take, for example, [url=http://bitsourceky.com/ t=_blank]Bit Source, a Kentucky-based company which trains unemployed coal miners. Rus calls it a success. “Bit Source is teaching them how to mine data instead.”
Kasparov also advocates a radically new approach to educating kids, questioning why the teacher needs to be the central authority when “kids can now learn more with a click of a mouse.” It makes no sense “to train kids for a world in which jobs available in twenty years may not even be conceived of yet.”
How many students learned the skills necessary to become a drone operator in 1995? That means giving students the skills and tools they’ll need – coding, for example — regardless of the kinds of jobs that become available after they graduate. “Teach the how, not the what,” Kasparov says.
