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Certain types of photograph are challenging for’s age detection. “Women who are stars tend to look younger than they really are,” says Hersch, “but this is consistent with how people judge age, because we relied on them to average the truth when we trained the system.”’s technology may never be as good at determining age as a person, but Hersch says that in many cases, just knowing the approximate age is useful enough. “Marketers, 90 percent of them are only into the range anyway,” says Hersch.

One possible way to improve the accuracy would be to teach the system to recognize certain lighting conditions that affect how it gauges age, says Hersch. For example, strong light from above accentuates shadows around a person’s eyes and may lead to their being guessed as older than they really are.

“I think this has tremendous potential for contextual advertising, as you can pull out the right advertisements for that category of users,” says Qiang Yang, a professor at Hong Kong University of Science and Technology. Yang previously developed a way to serve ads based on what the images on a page depict. “These features coupled with textual features on a page could paint a very good picture of the person [viewing a page],” says Yang. “If this is a teenage girl, we will be able to show different ads from those for a middle-aged man.”

Facial-recognition technology often raises privacy concerns, although it has become a standard feature of Facebook, which uses it to make it easier for users to tag their friends in photos, and in photo management software such as Google’s Picasa and Apple’s iPhoto.

Hersch says the service he offers simply allows websites and mobile apps to offer more to their users. “This provides more value out of photos,” says Hersch. “We’re unearthing data that’s really there, but just not available.”

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