Big data illustration (Wikipedia)

All of a sudden, a pop-up notification on my desktop spelled out in big red letters: “Warning: your account has an abnormal activity.” Underneath, a line of smaller text read “Today’s login location: Los Angeles, U.S.” and “Last login location: Yesterday, Shanghai, China” to warn me that someone else was trying to use my account.

At first this made me feel protected, but I also got a feeling that someone was watching my every move, which crept me out.

Another incident involving my QQ account happened a few years ago when I was in the U.S.

I didn’t use QQ for nearly a week; then one day my parents messaged me from Hefei, my hometown in China, saying that they got a message from me on QQ asking them to transfer $800 to an unfamiliar bank account. I freaked out and logged into my account to check my message history.

And there it was: abnormal activity warning.

Around the time that my parents received the message, my login location changed back and forth between two places that are 950 miles away from each other. I wish I had seen this warning earlier so that I would have changed my password and protected account.

So I appreciated that location tracking function, but in the meantime, I wondered how QQ knew my locations?

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Many people, like me, are having this love-hate relationship with the Internet. We love it when our phones and laptops know what we like or dislike, who we are, and what we want or need.

But we hate it knows too much, which frightens us: who is following us through those devices? What will it do with all that data? 

Big Data, as the large volumes of stored data are known, has become a huge topic among tech and business communities all over the world. It relies on advanced computing technology to sift and analyze the huge amount of information. The term Big Data refers not just to text. It also includes images, videos, audios, web logs, click stream statistics and social network content. 

We use Big Data for nearly everything, even though most people aren’t aware of it.

Supermarkets, such as Target and Walmart, use the data to predict what people need, what they will buy, when and in what quantities. Data analysts and scientists use Google statistics to predict flu pandemics. Banks use the data to track customers’ credit card activities and report abnormal behavior in order to prevent credit fraud. 

But how well does Big Data protect itself? How much personal data do the analysts have? What should we do to stop worrying about our privacy being leaked to someone we don’t trust? 

Lucas Introna and Helen Nissenbaum, authors of Shaping the Web: Why the Politics of Search Engines Matters, proposed that companies that collect and use our personal data should provide “full and truthful disclosure of the underlying rules governing (data) indexing, searching and prioritizing” and state those rules in a meaningful way to the majority of Web users.

By having this transparency and understanding the rules (algorithms), we will no longer be kept in the dark about the inner workings of mysterious Big Data.

If transparency is not enough, perhaps we could try something New York University law’s Professor Ira Rubinstein called “control shift.”

In his paper published on N.Y.U. Public Law & Legal Theory Working Papers in 2012, he describes a possible future model in business based on digital datasets: businesses shift control of Big Data to the customers who provide the data.

He argues that it is inevitable that businesses collect and use personal data with their own interests in mind, so allowing the customers to seize at least some power may help form mutual understanding. Once we have the power, we may be motivated to generate and use Big Data to create more beneficial services for ourselves without being worried.

There is reason to be worried.

As Big Data has exploded in the recent years, scandals have followed in its wake: Verizon Wireless sold out customers’ personal information to an advertiser and allowed the advertiser to use information mined from users’ visits to websites from desktop computer and market its products to their cell phones; customers of Home Depot found out their credit card information was stolen and sold by unidentified hackers, which put about 56 million cards at risk.

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Many companies, such as some credit cards companies, adopt anonymous data collection methods that collect data from clients without including their personal identities. So theoretically, even if some hackers access the data, they wouldn’t know who it belongs to.

However, this strategy has failed spectacularly. Computer scientists have demonstrated that they can often “re-identify” or “de-anonymize” individuals hidden in anonymized data with astonishing ease. Sometimes we feel safe because the companies assure us our anonymity, yet what we think is private isn’t.

If we can’t really be anonymous online, then it may be a better alternative to follow Rubinstein’s lead and let the customers realize and tame the elephant in the room: the value of Big Data from various standpoints.

In other words, the businesses can make the tools, process and content of Big Data transparent to the public, help customers control how it is collected and used and allow them to benefit from it.

Big Data finds out what song we may like to hear, what fashion style we are drawn to or what groceries we need for next week, before we know what it is. It’s not an evil thing.

Just because it has been and could be used for evil, it has made us worried. But creating a win-win strategy for both businessmen and us and executing regulations, we may keep the parts we like while feeling protected from things we don’t.

Reach Contributor Xinyi Huang here.