Step One: Turn The World To Data. Step Two?

Is the public ready to accept the infinite glance of our own technology? That question springs up nearly everywhere I look these days, from the land rush in “deep learning” and AI companies (here, here, here) to the cultural stir that accompanied Spike Jonze’ Her. The relentless flow of Snowden NSA revelations, commercial data breaches, and our culture’s ongoing battle over personal data further frame the question.

But no single development made me sit up and ponder as much as the recent news that Google’s using neural networks to decode images of street addresses. On its face, the story isn’t that big a deal: Through its Street View program, Google collects a vast set of images, including pictures of actual addresses. This address data is very useful to Google, as the piece notes: “The company uses the images to read house numbers and match them to their geolocation. This physically locates the position of each building in its database.”

In the past, Google has used teams of humans to “read” its street address images – in essence, to render images into actionable data. But using neural network technology, the company has trained computers to extract that data automatically – and with a level of accuracy that meets or beats human operators.Not to mention, it’s a hell of a lot faster, cheaper, and scaleable.

Sure, this means Google doesn’t have to pay people to stare at pictures of house numbers all day, but to me, it means a lot more. When I read this piece, the first thing that popped into my mind was “anything that can be seen by a human, will soon be seen by a machine.” And if it’s of value, it will be turned into data, and that data will be leveraged by both humans and machines – in ways we don’t quite fathom given our analog roots.

I remember putting up my first street number, on a house in Marin my wife and I had just purchased that was in need of some repair. I went to the hardware store, purchased a classic “6” and “3”, and proudly hammered them onto a fence facing the street. It was a public declaration, to be sure – I wanted to be found by mailmen, housewarming partygoers, and future visitors. But when I put those numbers on my fence, I wasn’t wittingly creating a new entry in the database of intentions. Google Street View didn’t exist back then, and the act of placing a street number in public view was a far more “private” declaration. Sure, my address was a matter of record – with a bit of shoe leather, anyone could go down to public records and find out where I lived. But as the world becomes machine readable data, we’re slowly realizing the full power of the word “public.”

In the US and many other places, the “public” has the right to view and record anything that is in sight from a public place – this is the basis for tools like Street View. Step one of Street View was to get the pictures in place – in a few short years, we’ve gotten used to the idea that nearly any place on earth can now be visited as a set of images on Google. But I don’t think we’ve quite thought through what happens when those images turn into data that is “understood” by machines. We’re on the cusp of that awakening. I imagine it’s going to be quite a story.

Update: Given the theme of “turning into data” I was remiss to not mention the concept of “faceprints” in this piece. As addresses are to our home, our faces are to our identity, see this NYT piece for an overview.