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Computers Go Head-to-Head with Humans on Face Recognition

Google and Facebook both do a nice job identifying your friends in photos—a testament¹ to how good machines have gotten at studying human faces. But how well would an algorithm fare, when pitted against a forensic² facial examiner… the experts that testify in court?

谷歌和脸书都做了一份不错的工作，在照片上识别你的朋友，这证明了机器在研究人脸方面是多么优秀。但是，在法庭上作证的专家们，在法庭上作证时，这种算法的效果又如何呢?

"Well it turns out the best algorithm is comparable to the best humans." Jonathan Phillips, a facial recognition scientist at the National Institute of Standards and Technology.

“事实证明，最好的算法可以和最好的人类相媲美。”Jonathan Phillips是美国国家标准与技术研究所的面部识别科学家。

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.

他和他的同事向人类专家，提出了20个非常困难的图像配对，以及一系列的算法。最先进的算法，确实表现得和熟练的人类一样好。

But when Phillips and his team asked for input³ from two humans, or a human and an algorithm, it was the combined judgment⁴ 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 study is in the Proceedings⁵ of the National Academy of Sciences.

但是，当Phillips和他的团队要求，从两个人或一个人和一个算法中输入信息时，这是人类和机器的组合判断，结果是近乎完美的结果。这表明，人类大脑和计算机代码的综合优势和弱点，叠加在了更高的精确度上。这项研究结果发表在《美国国家科学院院刊》.

Phillips says now 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.

Phillips说，现在已经到了面部识别社区，他们可以利用这些发现，来改善现实世界的测试。别担心:人类识别器很快就会消失的。

"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 you get out of an algorithm itself." After all someone—preferably, a human—still has to explain the findings in court.

“仅仅因为一个算法，我给了你一个高分，你不只是接受那个黑盒子的单词……你开发了把人的判断，融入到你从算法本身中得出决定的方法。”毕竟，一个人最好还是在法庭上解释这些发现。