As smart as computers may seem, they can’t match humans in certain tasks: describing the contents of an image, rating the quality of Web search results, or transcribing and translating text from another language, to name a few. Tapping into human expertise to tackle problems that computers struggle with is also a growing business: Google lets customers refine its search results, and Amazon uses a system called the Mechanical Turk to off-load all manner of simple tasks to humans around the world; people will work on these tasks, even for pennies.
Now Nathan Eagle, a research fellow at the Santa Fe Institute, in New Mexico, is launching a project similar to Amazon’s Mechanical Turk but that distributes tasks via cell phones. The goal of his project, called txteagle, is to leverage an underused work force in some of the poorest parts of the world.
Eagle says that distributing questions to participants in such developing countries via text messages or audio clips could make certain tasks more economical, such as the translation of documents into other languages, or rating the local relevance of search results. It could also provide a welcome source of income for those involved.
“We’re trying to … tap into a group of people to complete these tasks who haven’t been tapped before,” says Eagle. “And we’re using mobile phones, which have a high penetration rate. More people are mobile-phone subscribers in developing countries than in the developing world, so we can get a user base of billions of people.”
The Finnish cell-phone company Nokia is a partner in the project, and Eagle says that it provides a good example of a Western company that could benefit from txteagle workers. Eagle explains that Nokia is interested in “software localization,” or translating its software for specific regions of a country. “In Kenya, there are over 60 unique, fundamentally different languages,” he says. “You’re lucky to get a phone with a Swahili interface, but even that might be somebody’s third language. Nokia would love to have phones for everyone’s mother tongues, but it has no idea how to translate words like ‘address book’ into all of these languages.”
Another application is the transcription of audio recordings: a user would listen to a short clip, write it down by hand, and then copy it into an SMS reply. Eagle’s studies have shown that this task can be completed in less than two minutes, and he believes that a proficient user could earn about $3 an hour doing the work, which would be 60 percent cheaper than today’s transcription rates.