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State and local authorities from New Hampshire to San Francisco have begun banning the use of facial-recognition technology. The
State and local authorities from New Hampshire to San Francisco have begun banning the use of facial-recognition technology. The
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2022-11-01
89
问题
State and local authorities from New Hampshire to San Francisco have begun banning the use of facial-recognition technology. Their suspicion is well founded: these algorithms make lots of mistakes, particularly when it comes to identifying women and people of color. Even if the tech gets more accurate, facial recognition will unleash an invasion of privacy that could make anonymity impossible. Unfortunately, bans on its use by local governments have done little to curb adoption by businesses from start-ups to large corporations. That expanding reach is why this technology requires federal regulations—and it needs them now.
Automated face-recognition programs do have advantages, such as their ability to turn a person’s unique appearance into a biometric ID that can let phone users unlock their devices with a glance and allow airport security to quickly confirm travelers’ identities. To train such systems, researchers feed a variety of photographs to a machine-learning algorithm, which learns the features that are most salient to matching an image with an identity. The more data they amass, the more reliable these programs become.
Too often, though, the algorithms are deployed prematurely. In London, for example, police have begun using artificial-intelligence systems to scan surveillance footage in an attempt to pick out wanted criminals as they walk by—despite an independent review that found this system labeled suspects accurately only 19 percent of the time. An inaccurate system could falsely accuse innocent citizens of being miscreants, earmarking law-abiding people for tracking, harassment or arrest. This becomes a civil-rights issue because the algorithms are more likely to misidentify people of color.
Even if someone releases improved facial-recognition software capable of high accuracy across every demographic, this technology will still be a threat. Because algorithms can scan video footage much more quickly than humans can, facial recognition allows for constant surveillance of a population.
The government needs to protect all its citizens against these kinds of measures. But existing bans on the technology create an inconsistent patchwork of regulations: some regions have no restrictions on facial recognition, others ban police from applying it, and still others prevent any government agencies or employees from using it.
Federal regulations are clearly needed. They should require the hundreds of existing facial-recognition programs, many created by private companies, to undergo independent review by a government task force. The tech must meet a high standard of accuracy and demonstrate fairness across all demographic groups, and even if it meets those criteria, humans, not algorithms, should check a program’s output before taking action on its recommendations. Facial recognition must also be included in broader privacy regulations that limit surveillance of the general population. Technologies that threaten the right to privacy must be controlled.
e word "salient" (Line 5, Paragraph 2) is closest in meaning to__________.
选项
A、identical
B、distinctive
C、common
D、weird
答案
B
解析
由题干关键词salient和Line 5,Paragraph 2定位至第二段第二句。这句话说明了面部识别系统是如何工作的:researchers feed a variety of photographs toa machine-learning algorithm,which learns the features that are most salient to matching an image with an identity(研究人员将各种照片输入到机器学习算法中,该算法记住与身份匹配的图像最……的特征),根据常识可知,我们最容易通过突出的、不同的或显著的特征发现一件物品与其他物品不同,故选项[B]distinctive“独特的,与众不同的”为正确答案。
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0
考研英语一
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