Data-Mining App Tracks People And Predicts Their Locations Melissa Block talks to Steve Henn about events in the world of high technology that are forecast to occur this week. Henn talks about a social data mining program called "Riot" that was developed by Raytheon.
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Data-Mining App Tracks People And Predicts Their Locations

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Data-Mining App Tracks People And Predicts Their Locations

Data-Mining App Tracks People And Predicts Their Locations

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From NPR News, this is ALL THINGS CONSIDERED. I'm Robert Siegel.


I'm Melissa Block. And we end the hour with All Tech Considered.


BLOCK: As always, we kick things off with a look ahead at the week in tech. The big story this week comes from defense contracting giant Raytheon. It has developed data-mining software that tracks people and predicts their future locations using posts to social networks.

NPR's Steve Henn joins us to talk about a software called RIOT, which stands for Rapid Information Overlay Technology. Steve, first, how did RIOT come to light?

STEVE HENN, BYLINE: Well, for years now, the federal government has been pretty open about its desire for software that could help law enforcement sift through social media sites like Facebook. RIOT looks like it was developed to meet some of those needs, but it captured the limelight this week because a reporter at The Guardian newspaper in England got a hold of a video that demonstrates exactly what the software can do.

BLOCK: And what is that? What can it do?

HENN: Well, quite a bit, actually. In the demo video, Brian Urch, from Raytheon, shows off how it can piece together a pretty detailed map of where someone has traveled over time by analyzing posts on sites like Facebook, Foursquare and Twitter. In the video, Brian's guinea pig is a co-worker of his named Nick.

BRIAN URCH: One of the things we've noticed is that when people take pictures and post them on the Internet using their smartphones that the phone will actually embed the latitude and longitude into the exit header data of that image. So we're going to take advantage of that by bringing down all the pictures where Nick has checked in and then placing those on Google Earth.

HENN: What they got was a pretty fine-grained look at how Nick was moving around the country and the city where he lives. And with a tiny bit of analysis, they found patterns in his behavior like when he was most likely to work out.

URCH: 6 a.m. appears to be obviously the most frequently visited time at the gym. So if you ever did want to try to get a hold of Nick or maybe get a hold of his laptop, you might want to visit the gym at 6 a.m. on Monday.

BLOCK: So, Steve, that's the video for this data-mining software. I'm a little confused about how this is revolutionary, if it is. I mean, it's basically just consolidating a lot of information that's out there on these social networks that you mentioned - Foursquare, Facebook and Twitter.

HENN: Yeah. That's right. That's what it does. And independent hackers built very similar software several years ago to try to demonstrate to people that this would be possible. I think what's been alarming to some is that it's a defense contractor that's making the software. And that if it is distributed and used widely, which it is not, yet, it would allow law enforcement to run these kinds of analyses over large groups of people very quickly all at once. It's sort of stalking at scale.

And the other thing that's alarming about this is because we're all putting our information on these social networks voluntarily, there are very few checks built into the law that would prevent any organization from doing that. We're basically writing little newspaper columns about what we do every day. And so if someone builds software that aggregates all that information and analyzes it across thousands or even millions of people, it's technically pretty easy to do, but it gives them a lot of insight and actually a lot of predictive ability about how any of us are going to behave or where we might be or what we might do.

BLOCK: OK. NPR's tech correspondent Steve Henn. Steve, thanks so much.

HENN: My pleasure.

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