And if you’ve now got the Pina Colada song stuck in your head after reading that, you’re probably not alone.
A lot of these inferences could be due to “statistical noise,” say the researchers – correlations that are more or less random. But what the Cambridge geeks did isn’t at all unusual. It’s called data mining, and it’s the new black.
Major retailers like Target have been mining data on their customers for years, looking for patterns that predict future buying behavior. Hence articles like “Target knows you’re pregnant before your dad does.”
Cops in several California cities use data mining for “predictive policing,” sussing out potential high-crime areas based on statistical analysis and getting there before the criminals do. (Insert obligatory Minority Report reference here.)
The success of the Obama re-election campaign was due in large part to how well the campaign crunched the enormous amount of data they had in order to determine who was likely to donate money, volunteer, and vote.
Like they say on the cop shows, your Likes can be used against you in a court of law, or – more likely and more chilling – in ways you’ll never know about.
For example, because you’re a fan of Slayer, you could be denied health coverage; after all, you’re probably a smoker. You could get turned down for a job because HR scanned your Facebook profile and discovered that you’re a member of a Harley Davidson fan page. Sorry, only the best and brightest can work there. And if you can’t get enough of Glee, forget about becoming a Boy Scout pack leader.
We are increasingly at the mercy of our algorithms, potential victims of statistical noise. You don’t need to be a genius – or to like curly fries – to see where this kind of thing can lead.
Got a question about social media or privacy? TY4NS blogger Dan Tynan may have the answer (and if not, he’ll make something up). Visit his snarky, occasionally NSFW blogeSarcasm or follow him on Twitter: @tynanwrites. For the latest IT news, analysis and how-to’s, follow ITworld onTwitter and Facebook.
Now read this: