In the fall of 2000, as the first dot-com bubble was bursting, the Guatemalan computer scientist Luis von Ahn attended a talk, at Carnegie Mellon, about ten problems that Yahoo couldn’t solve. Von Ahn, who had just begun his Ph.D., liked solving problems. He had planned to study math until he realized that many mathematicians were still toiling away over questions that had proved unanswerable for centuries. “I talked to some computer-science professors and they would say, ‘Oh, yeah, I solved an open problem last week,’ ” he told me recently. “That seemed just a lot more interesting.”
At the talk, one particular problem caught his attention: millions of bots were registering for Yahoo accounts because the company couldn’t distinguish them from human beings. What the company needed was a rudimentary variation on the Turing Test, which the English mathematician Alan Turing had proposed, in 1950, as a way of determining whether machines could credibly imitate human beings. In the most familiar version of the test, a person poses questions to two figures he cannot see: one human, one machine. The machine passes the test if the evaluator can’t reliably decide which is which. Back in 2000, no computer had ever succeeded.
In college, von Ahn had read a book by the philosopher Douglas Hofstadter in which Hofstadter points out that computers can’t recognize text unless it’s standardized. With this in mind, von Ahn and his adviser, Manuel Blum, created a program called CAPTCHA: the Completely Automated Public Turing test to tell Computers and Humans Apart. The program generated text, distorted it, and required users to decipher the letters correctly. (Other researchers came up with similar proposals around the same time.) Von Ahn and Blum reached out to Yahoo, and gave the company the code free of charge. Within two weeks, the system was up and running. Within three years, a version of it had been implemented by nearly every large company on the Internet.
CAPTCHA did not make von Ahn rich, but it did make him mildly infamous. When people learn about his role in the program’s creation, he told me, they say, “Oh, you came up with that? I hate you.” This makes him feel bad, he said, but it didn’t deter him. A few years after developing CAPTCHA, von Ahn created the ESP Game, which randomly paired online players, presented them with an image, and asked them to give it a one-word label. The players couldn’t see the words their partners were choosing; they won the round when their words matched. Ten million people played. The game wasn’t a mere diversion: computers, at the time, had difficulty tagging images, something that humans can do easily. In 2006, von Ahn licensed the game to Google, which used it to improve search results for Google Images.
The game was also part of von Ahn’s dissertation, which he titled “Human Computation,” coining a term for what we now generally refer to as crowdsourcing. A year after he published it, he became an assistant professor at Carnegie Mellon and won a MacArthur “genius” grant.
Later, while driving to Pittsburgh from a panel in Washington, D.C., von Ahn had another idea. By that point, people were deciphering CAPTCHA fragments two hundred million times a day, with each one taking about ten seconds. Collectively, they were spending five hundred thousand hours every day proving to machines that they were human. What if, von Ahn wondered, he could channel all that unwitting microlabor toward something useful—the way, as he saw it, he had done with the ESP Game?
Several teams had recently begun working to digitize the world’s books, and it occurred to him that replacing CAPTCHA’s computer-generated text with little pieces of actual publications would speed those efforts along. He delivered a talk about the idea, and, shortly afterward, he was approached by executives from the Times, who had a hundred and fifty years’ worth of archives they wanted to put online. Von Ahn proposed that they pay him forty-two thousand dollars per year of old newspapers to digitize the archives. (This, he calculated, was a third of what it would cost to have humans type them by hand.) But Carnegie Mellon resisted the idea: making money off a research project could jeopardize the school’s nonprofit status. So von Ahn started a company, reCAPTCHA, to monetize his method of digitizing text. In 2009, he sold it to Google for a sum that he said was sufficient to insure that neither he nor his future children would ever need to work.
Von Ahn briefly considered retirement. “But only for a second,” he told me. “I get really bored.” Instead, he began a new project, Duolingo, which is now the most frequently downloaded education app in the world. Originally, he envisioned it as another Janus-faced project—a Web site that would help people learn foreign languages while simultaneously using their work to translate online texts. It evolved into something else, a smartphone app that offers language lessons as a series of bright, colorful, addictive games. But it remains, under the hood, an exercise in human computation. Like all of the work von Ahn is known for, it is an investigation into not only what we can learn from machines but also into what machines can learn from us.
Von Ahn is forty-four. He has button eyes, quizzical eyebrows, and a faint trace of stubble, visible mainly on the outer edges of his mustache. Although he now runs a company with a valuation in the billions, and keeps a schedule as rigid as a stationmaster in Mussolini’s Italy, he retains a comically eager quality. Describing his swift morning routine, he told me, “I set the bar of soap in the place where it’s easiest to access. I set everything up like that.” He talks fast, with an upbeat cadence, like a man on a mission that he’s thoroughly enjoying. He used to watch TV and read at the same time. (“I’m not doing that anymore,” he said, “but I was.”) When I asked him about the day-to-day grind of running a company, he said, “For me, this is very fun. Except for the people problems. Those are no fun.”
Duolingo got started after von Ahn began discussing a potential project focussed on education with his research assistant at Carnegie Mellon, a Swiss Ph.D. student of his with the improbable name Severin Hacker. Von Ahn had funding from the National Science Foundation, and he had earmarked some of his MacArthur money for the project, too. He and Hacker, who is now Duolingo’s chief technology officer, decided to zero in on language learning, von Ahn told me, because, in most countries, knowledge of English boosts earning potential. “I love math,” he said. “But just knowing math doesn’t make you more money. Usually, it’s, like, you learn math to learn physics to become a civil engineer. It’s multiple steps. Whereas with knowledge of English—you used to be a waiter, and now you’re a waiter at a hotel.”
Von Ahn grew up in a middle-class neighborhood in Guatemala City with his mother and his grandmother. His mother, Norma, was the youngest of twelve children, and also one of the first women in Guatemala to earn a medical degree. After Luis was born, she worked part time as a pediatrician, but spent most of her time, von Ahn said, “making sure that I got a good education and also making sure I was a hypochondriac.” She now lives with her son in Pittsburgh.
Von Ahn’s father was a well-known orthopedic surgeon who had been his mother’s professor in medical school. Von Ahn saw him from time to time, but he told me he didn’t know the story of his origins until his aunt offered him an explanation: his mother, she said, had “found the smartest person she knew and convinced him to have a child.” He added, “I don’t know how one does that, but this is the story I’ve been told.” It struck me that this was either a powerful example of how the stories we learn as children stay with us or a somewhat tender expression of a fundamental innocence. Possibly both.
When Luis arrived, Norma continued with her program of optimization. “I spoke to him from the time he was born,” she told me. “I think people don’t realize how important this is, but that’s how they acquire language.” By the age of two, she said, Luis spoke perfect Spanish, so she started to speak to him in English. She sent him to a Montessori school. His teachers told Norma that Luis liked to walk around the classroom explaining things to other kids.