Facebook made $3.2 billion in advertising revenue last year, 85 percent of its total revenue. Yet Facebook’s inventory of data and its revenue from advertising are small potatoes compared to some others. Google took in more than 10 times as much, with an estimated $36.5 billion in advertising revenue in 2011, by analyzing what people sent over Gmail and what they searched on the Web, and then using that data to sell ads. […]
Material mined online has been used against people battling for child custody or defending themselves in criminal cases. LexisNexis has a product called Accurint for Law Enforcement, which gives government agents information about what people do on social networks. The Internal Revenue Service searches Facebook and MySpace for evidence of tax evaders’ income and whereabouts, and United States Citizenship and Immigration Services has been known to scrutinize photos and posts to confirm family relationships or weed out sham marriages. Employers sometimes decide whether to hire people based on their online profiles, with one study indicating that 70 percent of recruiters and human resource professionals in the United States have rejected candidates based on data found online. […]
Stereotyping is alive and well in data aggregation. Your application for credit could be declined not on the basis of your own finances or credit history, but on the basis of aggregate data — what other people whose likes and dislikes are similar to yours have done. If guitar players or divorcing couples are more likely to renege on their credit-card bills, then the fact that you’ve looked at guitar ads or sent an e-mail to a divorce lawyer might cause a data aggregator to classify you as less credit-worthy. When an Atlanta man returned from his honeymoon, he found that his credit limit had been lowered to $3,800 from $10,800. The switch was not based on anything he had done but on aggregate data. A letter from the company told him, “Other customers who have used their card at establishments where you recently shopped have a poor repayment history with American Express.”
Even though laws allow people to challenge false information in credit reports, there are no laws that require data aggregators to reveal what they know about you. If I’ve Googled “diabetes” for a friend or “date rape drugs” for a mystery I’m writing, data aggregators assume those searches reflect my own health and proclivities. Because no laws regulate what types of data these aggregators can collect, they make their own rules. […]
In the 1970s, a professor of communication studies at Northwestern University named John McKnight popularized the term “redlining” to describe the failure of banks, insurers and other institutions to offer their services to inner city neighborhoods. The term came from the practice of bank officials who drew a red line on a map to indicate where they wouldn’t invest. But use of the term expanded to cover a wide array of racially discriminatory practices, such as not offering home loans to African-Americans, even those who were wealthy or middle class.
Now the map used in redlining is not a geographic map, but the map of your travels across the Web. The term Weblining describes the practice of denying people opportunities based on their digital selves. You might be refused health insurance based on a Google search you did about a medical condition. You might be shown a credit card with a lower credit limit, not because of your credit history, but because of your race, sex or ZIP code or the types of Web sites you visit.