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.
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