“I get really bored.” Instead, he began a new project, Duolingo, which is now the most frequently downloaded education app in the world. 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? Collectively, they were spending five hundred thousand hours every day proving to machines that they were human. By that point, people were deciphering CAPTCHA fragments two hundred million times a day, with each one taking about ten seconds. Later, while driving to Pittsburgh from a panel in Washington, D.C., von Ahn had another idea. A year after he published it, he became an assistant professor at Carnegie Mellon and won a MacArthur “genius” grant.

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. In 2006, von Ahn licensed the game to Google, which used it to improve search results for Google Images. The game wasn’t a mere diversion: computers, at the time, had difficulty tagging images, something that humans can do easily. The players couldn’t see the words their partners were choosing they won the round when their words matched. 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. 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. Within three years, a version of it had been implemented by nearly every large company on the Internet.ĬAPTCHA did not make von Ahn rich, but it did make him mildly infamous. Within two weeks, the system was up and running. (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. The program generated text, distorted it, and required users to decipher the letters correctly.

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. 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.

Back in 2000, no computer had ever succeeded. The machine passes the test if the evaluator can’t reliably decide which is which. In the most familiar version of the test, a person poses questions to two figures he cannot see: one human, one machine. 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. “That seemed just a lot more interesting.”Īt 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. “I talked to some computer-science professors and they would say, ‘Oh, yeah, I solved an open problem last week,’ ” he told me recently. He had planned to study math until he realized that many mathematicians were still toiling away over questions that had proved unanswerable for centuries. Von Ahn, who had just begun his Ph.D., liked solving problems. 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.

Duolingo incubator update 2015