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  3. Humans are startlingly bad at detecting fraud. Even when we’re on the lookout for signs of deception, studies show, our accuracy

Humans are startlingly bad at detecting fraud. Even when we’re on the lookout for signs of deception, studies show, our accuracy

admin2018-02-17  57
问题    Humans are startlingly bad at detecting fraud. Even when we’re on the lookout for signs of deception, studies show, our accuracy is hardly better than chance. Technology has opened the door to new and more pervasive forms of fraud: Americans lose an estimated $ 50 billion a year to con artists a-round the world, according to the Financial Fraud Research Center at Stanford University. But because computers aren’t subject to the foibles of emotion and what we like to call "intuition," they can also help protect us. Here’s how leading fraud researchers, neuroscientists, psychiatrists, and computer scientists think technology can be put to work to fight fraud however it occurs—in person, online, or over the phone.
   Spam filters are supposed to block e-mail scams from ever reaching us, but criminals have learned to circumvent them by personalizing their notes with information gleaned from the Internet and by grooming victims over time.
   In response, a company called ZapFraud is turning to natural-language analytics; Instead of flagging key words, it looks for narrative patterns symptomatic of fraud. For instance, a message could contain a statement of surprise, the mention of a sum of money, and a call to action. "Those are the hallmark expressions of one particular fraud e-mail," Markus Jakobsson, the company’s founder, told me. "There’s a tremendous number of[spam]e-mails, but a small number of story lines. "
   A similar approach could help combat fraud by flagging false statements on social media. Kalina Bontcheva, a computer scientist who researches natural-language processing at the University of Sheffield, in England, is leading a project that examines streams of social data to identify rumors and esti mate their veracity by analyzing the semantics, cross-referencing information with trusted sources, identifying the point of origin and pattern of dissemination, and the like. Bontcheva is part of a research collaboration which plans to flag misleading tweets and posts and classify them by severity: speculation, controversy, misinformation, or disinformation.
What does Paragraph 1 say about fraud?
选项 A、It is very hard to crack down on.
B、It is very easy to cast doubt on.
C、It is becoming more annoying.
D、It is apparently on the decline.
答案C
解析 细节题。文章第一段“即使在诈骗迹象初现端倪时，我们就保持警觉状态，但是我们判断诈骗的准确度不比我们的运气好多少。科技为更新、更普遍的诈骗形式打开了方便之门。”[A]crack down on“镇压，制裁”文章未提及。[B]“很容易质疑诈骗”与文中意思相反。[D]与文意不符。
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