Artificial intelligence, the holy grail of computer science for decades, is becoming a reality — not Skynet nor Cylons, but as a versatile tool for some types of complex problems, the kinds of problems with which our squishy, human brains struggle. (Cue the “I, for one, welcome our robot overlords” cubicle stickers.)

In an article (free registration required) in New Scientist this week, a new way of problem-solving — one in which humans help machines — is discussed. Already widely-used examples include reCAPTCHA (the clever OCR crowdsourcer) and Amazon’s Mechanical Turk, but ambitious plans from Dafna Shahaf and Eric Horvitz (a member of the CCC Council) would create a labor pool unlike any other: part man, part machine, it would break apart tasks and efficiently distribute them, maximizing efficiency.

As a proof of principle, the pair have built a [Generalized Task Market] prototype named Lingua Mechanica that does language translation tasks. But Horvitz has more radical long-term ambitions. Imagine that a child fails to return home. A GTM’s missing-person algorithm would be activated. It might scour the web for recent images of the child’s route home. Or recruit volunteers who would act as a network of human sensors across the search region, reporting a sighting via their smartphones. Another search algorithm might read news reports and Twitter for evidence of accidents. All without a human coordinator.

 

GTMs could have an extraordinary range of uses. In the event of a disaster, such as an oil spill, a GTM might assemble experts alongside data, sensors and robots. It could even manage mega-translation projects, such as converting the whole of Wikipedia into new languages. “It will consider a large set of intelligences and weave together a mesh of people and machines to solve problems,” says Horvitz.

To learn more, click here to read the full New Scientist feature story.

(Contributed by Max Cho, Eben Tisdale Fellow, CRA)