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　　►An Amazon facial recognition tool has wrongly identified 28 members of the US Congress as police suspects.

　　一亚马逊的脸部识别工具错误地将28名美议员识别成了警方嫌疑犯。

　　The American Civil Liberties Union (ACLU) compared official photos of the politicians with a database of public arrest photos.

　　美国公民自由联盟(ACLU)将政客的官方照片与公开逮捕嫌犯照片的数据库进行了比较。

　　Amazon took issue with the findings，saying the system needed to be set at 95% accuracy not the 80% used by ACLU.

　　亚马逊对调查结果表示不满，称该系统需要设置为95%的准确度，而不是ACLU使用的80%。

　　But the civil rights group said it highlighted the inadequacy of facial recognition technology.

　　但民权组织表示，它凸显了面部识别技术的不足之处。

　　"Our test reinforces that face surveillance is not safe for government use."said Jacob Snow，ACLU’s technology and civil liberties lawyer.

　　“我们的测试强调了政府使用面部检测是不安全的。”ACLU的技术和公民自由律师Jacob Snow说。

　　"Face surveillance will be used to power discriminatory surveillance and policing that targets communities of colour，immigrants，and activists. Once unleashed，that damage can't be undone."

　　“面部监视将用于推动针对有色人种，移民和激进分子的歧视性监视和治安。一旦释放，这种伤害就无法撤消。”

　　In response to the test，a spokesperson for Amazon Web Services told the BBC："We remain excited about how image and video analysis can be a driver for good in the world，including in the public sector and law enforcement."

　　亚马逊网络服务的一位发言人在接受测试时对BBC表示：“我们仍然对图像和视频分析能永久地应用到世界上驱动因素而感到兴奋，这包括公共部门和执法部门在内的领域。”

　　"With regard to this recent test of Amazon Rekognition by the ACLU，we think that the results could probably be improved by following best practices around setting the confidence thresholds."

　　“关于ACLU最近对亚马逊Rekognition的测试，我们认为可以通过遵循设置置信度阈值的最佳实践来改善结果。”

　　Rekognition is touted by Amazon as being useful for a range of things，from detecting offensive content to identifying celebrities.

　　亚马逊宣称Rekognition对于从检测攻击性内容到识别名人等一系列事情是大有用处的。

　　It is also working with some US local law enforcement agencies to implement the system for identifying criminals.

　　它还与一些美国当地执法机构合作，来实践识别罪犯的系统。

　　The 80% accuracy range used by ACLU is the system’s default setting but a spokeswoman for Amazon Web Services told Reuters that，for identifying individuals， it recommended setting a threshold of 95% or higher.

　　ACLU使用的80%准确度范围是系统的默认设置，但亚马逊网络服务的发言人告诉路透社，它建议在识别个人时设置成95%或更高的阈值。

　　According to ACLU，nearly 40% of the system’s false matches were for black Congress members，even though they make up only 20% of the legislature.

　　据ACLU称，该系统近40%的错误匹配是针对黑人国会议员的，尽管他们只占立法机构的20%。

　　Among those being wrongly identified was civil rights leader John Lewis，who is a member of the Congressional Black Caucus.

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