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Modern field guide to security and privacy

Nicole Wong on how big data could change the way we live

After stints at the White House, Google and Twitter, Wong understands the promise and peril of big data.

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    While working for Google, Wong testified at a Senate Judiciary Committee hearing on Internet freedom in 2008.
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This is an excerpt of a story from Passcode, the Monitor's forthcoming section on security and privacy. Read the full article here.

Nicole Wong is a founding columnist for Passcode, the Christian Science Monitor’s soon-to-launch section about security and privacy in the digital age.

After working as a senior legal executive at Twitter and Google, Wong came to the White House in June 2013. It was a critical time. Edward Snowden’s leaks about government surveillance had thrust online privacy into the forefront, and in the wake of public backlash, Wong helped to author a highly anticipated report on how the massive collection of personal data online could affect the way people live and work. Here’s what she learned.

Passcode: What’s the most important thing you found out putting together the White House report?

NW: When we were talking to people in the early set of meetings and workshops, we’d ask them, "Describe your privacy concern with the collection of big data." When you started to scrape the surface of their responses … their answer really was, "I don’t want people to use the data to make unfair decisions about me, I don’t want them to use data to limit opportunities presented to me or change my choices."

Passcode: So you found people’s concerns with big data isn't just limited to personal privacy?

NW: Personalization has made the Web really successful. Usually websites, for instance, try to show you ads that are more personalized to you ... presented in the language you speak, personalized to your location, or your interests. We are now going to have data about people where we can personalize all kinds of offers or opportunities: What kinds of loans you should be offered, what kind of educational opportunities should be offered.

In the future, hypothetically speaking, imagine you are a high school student, and you’re looking at college opportunities. It matters a lot what types of opportunities are even presented to you. It makes a lot of sense to personalize it in some ways, but there’s also the possibility of it for closing opportunities. What if you don’t see certain colleges, because whoever made that algorithm didn’t think you were interested in them because of your past academic performance, or what’s on your Facebook page? If everyone on your social network, for instance, went to a certain tier of school — maybe it will presume you only want to see schools in a certain tier.

That’s what people are worried about: that the algorithm will presume what people want, in a way that closes off opportunities for them. That there are opportunities they will simply never see.

Those questions about fairness and opportunity are not privacy questions. To some degree, these are discrimination questions, but also equity and access questions. I’d like to see the White House, federal government, and technologists using this data really bear into those issues, also from ethical standpoint — what’s the way I use data, [and] what is the right public policy outcome to use the data?

This is an excerpt of a story from Passcode, the Monitor's forthcoming section on security and privacy. Read the full article here.

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