撰文/播音 拉里·格林迈耶（Larry Greenemeier）
翻译 陈芳玮
审校 潘磊
When you install an app on your smartphone, you’re often asked whether you’d like to share your list of contacts with that app. That might be a convenient way to connect with friends and family likewise using, say, Instagram or Whatsapp, but it also means you’re giving away their personal information to the app developers.And that personal info could end up being used to create so-called “shadow profiles” of your contacts—even if they don’t use that app or social media service.
安装一款手机软件时，你通常会被问到，是否允许它访问你的通讯录。如果你允许的话，就能方便快捷地联系上同样使用这款软件的亲朋好友。但是，这也意味着你将联系人的私人信息提供给了软件的开发者。这些私人信息可能会被做成所谓的“隐藏档案”，即使档案中的人并未使用这款软件。
Shadow profiles emerged as a potential problem in 2011 when an Ireland-based advocacy group accused Facebook of gathering information on nonusers, including names, email addresses, phone numbers and physical addresses.
2011年，伴随着一个爱尔兰组织对Facebook收集非用户群体的信息（包括姓名、邮箱、电话和住址）的指控，“隐藏档案”的问题浮现于公众视野。
The following year researchers showed that social network companies such as Facebook could use machine learning to pretty accurately predict whether two nonmembers known by the same member also know one another. Not exactly Big Brother, but a recent study in the journal Science Advances raises the stakes.
随后一年，有研究者表示，像Facebook这样的社交网络公司可以利用机器学习技术精确地预测两个认识同一用户的非软件用户者是否认识。这还不完全构成《一九八四》中的“老大哥在看着你”情形，但最近发表在科学进步期刊（Science Advances）上的一项研究指出了风险所在。
In that work, David Garcia, chair of systems design at the sci-tech university ETH Zürich, used a social network member’s personal information to infer relationship status and sexual orientation of the members’ contacts who did not have their own user accounts on that social networking site. [David Garcia, Leaking privacy and shadow profiles in online social networks]
在这项研究中，大卫·加西亚（David Garcia），苏黎世联邦理工学院（ETH Zürich）的系统设计主席（chair of systems design），选择了一名社交网络用户，使用他的个人信息来推断这名用户通讯录中联系人的情感状态和性取向，而那些联系人并不是社交网站的用户。
He was able to do that using, of all things, data from the now defunct Friendster social networking site. He says he chose those two attributes—relationship status and sexual orientation—because they can carry important privacy consequences and were both available in the Friendster data set.
他使用了来自Friendster网站（现已倒闭）的数据。据他所说，他之所以选择这两个属性——情感状态和性取向，是因为它们包含了重要的个人隐私信息，并且确实都能从Friendster网站的数据库中获取。
Garcia is careful to point out that he didn’t prove that shadow profiles exist, just that they can be created. His work also reminds us how much we wind up revealing online—about ourselves and about the people in our lives.
加西亚谨慎地指出，他没有证明“隐藏档案”的存在，只是证明它们能被制造出来。他的工作提醒我们，我们在网络上的一举一动正在泄露隐私——我们自己的隐私和身边人的隐私。
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