We are not talking simply of constricted and restrained Web 2.0 applications that are limited to consenting/opt-in users, such as maybe Picasa or currently Facebook tagging. We are talking about the world where anyone in the street could in fact recognize your face and make these inferences, because the data is really already out there, it is already publicly available.

So, what will our privacy mean in this kind of future, in this augmented reality future? And have we already created a de facto ‘Real ID’ infrastructure? Although Americans are against Real IDs, we have already created one through the market place.

Google recently started allowing pattern based searches for images, but not faces yet

As I move on to describing the actual experiments that we ran to debate these questions I put here, I want to stress some of the themes I have already highlighted, because I really hope that what will remain after this talk will not be simply the numeric results of these experiments but what they imply for the future. Because I feel that what we are presenting is in a way a prototype, is a proof of concept, but five or ten years out this is really what is going to happen.

So key themes are – your face is a conduit between online and offline world, the emergence of personally predictable information, the rise of visual and facial searches where search engines allow the search for faces. Next key themes are the democratization of surveillance, social network profiles as Real IDs, and indeed the future of privacy in a world of augmented reality.

So let me talk about experiments. We did three experiments. The first one was an experiment in online-to-online re-identification. It was about taking pictures from an online database, which was anonymous or, let’s say, pseudonymous, and comparing it to an online database which was ostensibly identified – and seeing what we get from the combination of two. The second was offline-to-online: we started from an offline photo and we compared it to an online database. And the last one, the last step was to see if you can go to sensitive inferences starting from offline image.

In the first experiment, we mined data from publicly available images from Facebook, and we compared it to images from one of the most popular dating besthookupwebsites.org/escort/fort-worth/ sites in the U

The online database which is identified, which we have used across our experiments was Facebook profiles. Why did we use Facebook profiles? We could have used others, you know, LinkedIn profiles often, but not always, have images and names. Facebook in particular is interesting because if you read the Privacy Policy of Facebook, it really tells you that “Facebook is designed to make it easy for you to find and connect with others. For this reason, your name and profile picture do not have privacy settings”, meaning that you cannot change how visible your primary profile photo is. If you have a photo of yourself as your primary profile photo, anyone will see it, you cannot change it.

And in fact, most users do use primary profile photos which include the photos of themselves. Not only that: many users, according to our estimate – 90% use their real first and last name on Facebook profile. So you see where I am going, the story of the Real ID, de facto Real ID.

S. The recognizer that we used for this is an application I mentioned earlier – it’s called PittPatt. It was developed at Carnegie Mellon University and has been acquired by Google recently. It does two things: first is face detection, and then face recognition. Detection is finding a face on a picture. Recognition is matching it to other faces according to some matching scores.