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This is Scientific American's 60-second. I'm Christopher in Taliatta.

Google and Facebook both do a nice job identifying your friends and photos,

a testament to how good machines have gotten at studying human faces.

But how well would an algorithm fare when pitted against a forensic facial examiner,

the experts that testify in court?

Well, it turns out that the best algorithm is comparable to the best humans.

Jonathan Phillips, a facial recognition scientist at the National Institute of Standards and Technology.

He and his colleagues presented 20 very difficult image pairs to human experts and a range of algorithms,

and the most up-to-date algorithms did indeed perform as well as the skilled humans. But when Phillips and his team

asked for input from two humans or a human and an algorithm, it was the combined judgment

of humans and machines that won out, providing near-perfect results, which suggests the pooled strengths and weaknesses

of human brains and computer code add up to superior accuracy, the studies in the proceedings

of the National Academy of Sciences. Philip says it's now up to the facial recognition community

to use these findings to improve the tests in real-world settings.

And don't worry, human recognizers won't be out of a job anytime soon.

Just because an algorithm says, I give you a high score, you don't just accept the word of that

black box, you develop ways of integrating human judgment into the decision that you get out of

...