What would you think if you met a fortune teller who told you the name of your first girlfriend, your sexual orientation and political preferences, and whether your parents separated during your childhood?
Well, those fortune tellers exist. You just haven’t met them yet. They are every data scientist mining your online data from Facebook and Twitter to find and predict your personal information.
The results of a study that shows just how much information people innocuously reveal online has been making its way around the Internet over the past few days. (See here and here, for example.)
The report, which comes from the University of Cambridge and Microsoft Research, states:
“We show that easily accessible digital records of behavior, Facebook Likes, can be used to automatically and accurately predict a range of highly sensitive personal attributes including: sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender.”
What surprised people, or at least made for good news, is that the researchers could predict personal information based on non-obvious cues. Not everyone successfully predicted to be gay, for example, had Liked “Gay Marriage.”
This should not be shocking. Knowing people’s personality, shopping habits, and predispositions is key to the online economy. Facebook’s stock rises and falls with its ability to wring out your personal information and promise advertisers effective targeted advertising. It’s even true offline: Target famously knew that a young girl was pregnant before her parents did.
What is less discussed, as pointed out by Evgeny Morozov, a scholar of the social and political implications of technology, are all the other uses that this information can be used for beyond advertising.
He gives the examples of loans. A number of startups are helping banks decide whether to extend a loan by mining social media to predict whether a person is creditworthy. This can help people get a better rate than they would receive based on their credit data – or screw someone whose social media activity suggests that (statistically) they aren’t a good bet.
Anecdotally, this author saw college students scrub any evidence of risqué behavior off their social media profiles once they realized that graduate schools and employers checked their Facebook as part of the application process. When people realize that simply “liking” a TV show or re-tweeting a political comment can have real consequences, will they stop sharing so much?
This post was written by Alex Mayyasi. Follow him on Twitter here or Google.