How Artificial Intelligence Can Change Higher Education
Sebastian Thrun, winner of the Smithsonian American Ingenuity Award for education takes is redefining the modern classroom
- By Tom Vanderbilt
- Smithsonian magazine, December 2012, Subscribe
(Page 2 of 2)
Thrun believes online education is at the same sort of transitional moment self-driving cars were a decade ago—a moment that plays to his own problem-identifying strengths. Chris Urmson, the engineering head of Google’s self-driving car program, describes Thrun as someone “who has the insight to see when something needs to happen” but “isn’t purely visionary—he has the drive and execution to go and actually do it. Seeing the two mix in one person is rare.” (Thrun’s dual nature might be seen in the cars he drives: a Chevy Volt, the quintessence of quiet, left-brained efficiency, and a Porsche, that splashy emblem of ego, adventure and risk.) And Udacity speaks to another Thrun obsession: “For me, scale has always been a fascination—how to make something small large. I think that’s often where problems lie in society—take a good idea and make it scale to many people.”
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Long before he was trying to tackle large, complex problems, Thrun tackled small, complex problems as a teenager in a small town near Hanover, Germany. On a Northstar Horizon computer, a gift from his parents, he tried writing a program to solve Rubik’s cube. Another program, to play the board game peg solitaire, involved what’s known in math as an “NP-hard problem”—at each step the time-to-solve grows exponentially. “I started the program, waited a week, it didn’t make any progress,” he says. “I realized, wow, there’s something profound, deep, that I don’t understand—that a program could run for millennia. As a high-school student, it’s not in your conception.”
At the University of Bonn, Thrun studied machine learning, but dabbled in psychology—“My passion at the time was people, understanding human intelligence.” In 1991, he spent a year at Carnegie Mellon under the tutelage of the AI pioneers Herbert Simon and Allen Newell, building small robots and testing his theories about machine learning. But even then, he was thinking beyond the lab. “I always wanted to make robots really smart, so smart that I wouldn’t just impress my immediate scientific peers, but where they could really help people in society,” he says.
He actually became an adjunct professor of nursing while developing robotic nurses at a Pittsburgh elderly-care home. Another early effort, a robot named Minerva, was a “tour guide” that welcomed visitors to the Smithsonian National Museum of American History. It was, says Thrun, a learning experience. “What happens if you actually put a robot among people? We found problems we never actually anticipated.” Visitors, for example, tried to test the robot’s ability. “At some point, people lined up like a wall, and hoped the robot would drive into an area where it didn’t know how to operate, like a nearby cafeteria,” he says. “And the robot did.”
In 2001, Thrun went to Stanford, where the Silicon Valley spirit hit him like a revelation. “In Germany there’s just many questions you’re not allowed to ask,” he says, “and for me, the core of innovation is for very smart people to ask questions.” In the United States, and particularly Silicon Valley, he found an “unbelievable desire” to ask questions, “where you don’t just go and proclaim something because it’s always been this way.” He wishes, he says, “that Silicon Valley wasn’t 2,500 miles away from Washington, D.C.,” that societal innovation could keep up with technical innovation. “We can’t regulate our way out of problems,” he argues, “we need to innovate our way out.”
It was in that spirit that he plunged into work on an early version of the car that would eventually make its way to Google. In 2007, he took a year’s leave from Stanford to help develop Streetview, Google’s 360-degree mapping feature. “It became an amazing operation, the biggest photographic database ever built at the time.” Then he assembled an AI dream team to make the self-driving car a reality (a version named Stanley, which won the 2005 DARPA Grand Challenge for driverless vehicles, is held by the American History Museum) and founded Google X as a skunkworks for developing products like the augmented-reality “Google glasses.”
Udacity may seem rather a departure for Thrun, but Urmson, his Google colleague, says that while it’s different on a “purely technical axis,” it shares with his other work the “opportunity to have this transformative impact.” There are other parallels. Thrun seems intent on hacking education the same way he hacked driving, drilling it down to its component parts, testing and retesting. “We do a lot of A/B testing,” he says, describing the technique, popular in Silicon Valley, for comparing two different versions of a web page to see which is more effective. “We have lots of data. We use it strictly for improving the product.” (He jokes that he even runs scientific tests on his 4-year-old son: “I gave him infinite access to candy the first day; the second, suddenly he didn’t like it anymore.”)
In his statistics course, he occasionally puts out some theorems that are “way too hard.” But he wants to see how many people will make the effort (60 percent, it turns out). While some have complained that his courses are too easy because they give students an endless number of chances, he says he’s inspired by Khan’s notion that different students learn at different speeds. “In the beginning, I was the typical professor, saying you get exactly one chance,” he says. “A lot of students complained: ‘Why do you do this? Why do you deprive at the moment where I’m actually succeeding?’”
This time, he realizes, he may be the one getting it wrong. “We’re starting from scratch,” he says. “I’m the first one to realize we haven’t figured out how to do it right. We really have to be humble and realize that it’s just the beginning.” He wants to redress “this bizarre imbalance” in education “between the value paid and the services rendered.”
As Norvig argues, “This idea that you go to school for four years and then you’re done—that’s not going to cut it. Ten years from now you’re going to be doing something that you weren’t trained in in college because it’s not a career that existed ten years ago. So you’re going to need continual training.” He now teaches at Udacity.
At Google Thrun had the latitude and money to work on projects like Streetview, where “you couldn’t really tell what it was good for, other than that it was kind of cool,” he says. His investment in Udacity is more personal. He likes to quote Regina Dugan, former head of DARPA: “What would you do if you knew you couldn’t fail?”
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Comments (2)
I happen to like recorded lectures, it's not boring at all if you compare to most websites that have just text pages. So lets not pretend we need voice overheads and magic hands with problem solving and that recorded lectures would be bad, that is the wrogn approach to try adn kill something off that is jjust now starting to be widely available. Also, I took some of the AI course and I was actually annoyed by all the breaks in the presentation of the theory, "now solve this" all the time, it was disruptive !
Posted by PL on February 7,2013 | 03:50 AM
he is awesome!
Posted by Dominiq on January 7,2013 | 02:04 PM