6 Abuses for Facebook Places
Facebook just added a check-in or location-sharing feature, much like the one provided by FourSquare.com. The feature is designed to accomplish three main tasks:
- Help people share where they are in a social context
- See which friends are near by
- Discover nearby places and new places through friends’ profiles
But, by default, it also allows your friends to tag and publicize your location for you. It’s like being tagged in a photo, except the other person gets to share your location instead of your picture (even if you don’t want others to know where you are, and even if you are not there).
Here are some of the rarely discussed ways that Facebook Places will be used (now or in the future) that you might want to think about before checking in:
- Facebook will sell (share) your current location and profile to stores in your vicinity so that they can server you hyper-targeted advertising (e.g., here’s a coupon for the store you are about to enter).
- Friends who aren’t actually your friends will be able to check you in to questionable Places even when you are not there (the practical jokes for the Check Friends In feature are limitless)
- Facebook will compile and analyze your Places and then sell this profile to companies that would like to have you as a customer. If you “check in” frequently while in Casinos, get ready for a healthy dose of advertising from Bally’s.
- Thieves will track your location to know the best time to rob your home. It happens every day.
- Your suspicious spouse or boss will have a handy tool to track your whereabouts when you’d rather keep it private (this could actually be seen as a positive use of Places).
- The police will be able to subpoena records of your location at the time of a crime (again, if you have done nothing wrong and can prove it, this is a great way for law enforcement to establish location).
The solution isn’t to completely avoid all use of places. It’s to customize your Facebook Places Privacy Settings so that you are in control of the flow of data.