Humans Plus Computers Equals Better Crowdsourcing
If computer scientist Panagiotis Ipeirotis were to write a profile of himself, he’d start by hiring people online to summarize the key concepts in his published papers. Then he’d write a program to download every word in his 187 blog entries and examine which posts visitors to the site read most. Ipeirotis, an associate professor at New York University’s Stern School of Business, would do all that because his research shows that pairing computer and human intelligence can unearth discoveries neither can find alone. Ipeirotis, 35, is an expert on crowdsourcing, a way to break down big projects into small tasks that many people perform online. He tries to find ways, as he puts it, of using computer databases to augment human inputs.
Ipeirotis describes a recent real-world success with Magnum Photos. The renowned photo agency had hundreds of thousands of images scanned into its digital archive that it couldn’t search because they weren’t tagged with keywords. So Magnum hired Tagasauris, a startup Ipeirotis co-founded, to begin annotating. As Tagasauris’s online workers typed in tags, its analytical software queried databases to make the descriptions more specific. For example, when workers tagged a photo with the word “chicken,” the software tried to clarify whether the worker meant the feathery animal, the raw meat, or the death-defying game.
The system also links different photos from one roll of film, since one image provides only a slice of potential context. Noticing that workers had tagged images of George Lucas, Ron Howard, Richard Dreyfuss, and Mackenzie Phillips in separate photos from one shoot, the system again dove into databases to see what those people had in common. One answer came up: the film American Graffiti. Tagasauris found nearly two dozen previously lost photos taken on the film’s set. “Computers couldn’t ID humans in the photo,” Iperiotis says, “but humans couldn’t know the context.”
Ipeirotis has been tinkering with computers since he was a kid growing up in his native Greece. In college he had a tech-support gig where he’d help customers figure out what was wrong with their PCs by scouring computer companies’ websites. (This was pre-Google.) He realized there had to be a way to get these customers and these websites to speak the same language—and has pondered human-machine cooperation ever since. Ipeirotis says some big tech companies have asked him to improve their crowdsourcing efforts. (He won’t name names.) Ultimately, his goal is getting technology to help people do more meaningful work. “People are much better at jobs that require them to think, rather than mindless tasks,” he says.