that picture has appeared, or provide “visually similar images” that have the same coloring

and composition. The leading search engine in Russia, called

Yandex, has reverse image search too but it doesn't work the same way. It's not looking

for visually similar images. It's looking for similar faces, the same face.

The difference between these search engines is that Google hasn't switched on facial recognition

and Yandex has. On Google, you can enter a name and look for a face. But on Yandex, you

can enter a face and look for a name. And that distinction represents a potentially

enormous shift in our offline lives, where we usually decide who we introduce ourselves

to. Now that computer scientists have created

tools that can turn faces into nametags, it's worth reflecting on how we got here and what

we stand to lose.

A computer's facial recognition system has broadly the same components as your own facial

recognition system. You see someone with your eyes, your mind processes the features of

their face, and recalls their identity from your memory.

Now imagine if you could have eyes in lots of places and could download and store memories

from other people, then you have something more like the automated version of facial

recognition, which has only come together in the past 5 years or so.

Its eyes are digital cameras, revolutionary machines that turn light into data. "It's

a state of the art digital model, which records images on memory chips instead of photographic

film." Digital imagery arose in the early 2000s, which coincided with the arrival of

the social internet. So right when we were able to take an unlimited number of pictures,

Facebook, Flickr, Youtube, and other sites told us our images had a home online.

"100 million photos are being tagged every day on Facebook."

Professional photography also went up on websites, news articles, and photo libraries, and Google's

web crawlers gathered them into Image Search. And then the computer vision researchers went

to work. The millions of digital photos posted to the internet, like the Facebook pictures

where we tagged our friends or Google image results of celebrities-- they were used to

build the “mind” of facial recognition systems. That mind is made up of a series

of algorithms. They locate faces in an image, map facial

features to correct for head rotation, and then take over 100 measurements that define

that individual face. Those measurements are usually described as

the distance between the eyes, the length of the nose, the width of the mouth. But the

truth is, nobody knows exactly what's being measured. That's determined by a deep learning

algorithm looking for correlations in raw pixel data.

To train that algorithm, engineers give it sets of triplets: an anchor photo, another

photo of the same person, and a photo of a different person. The algorithm is tasked

with deciding what to measure so that the statistical difference between the two matching

photos is as small as possible while the distance between the non-matching photos is as large

as possible.  These algorithms are refined through millions

of examples, but they still don't perform equally well on all types of people or on

all types of photos. That hasn't stopped them from being packaged

and distributed as ready-to-use software. But whoever uses that software won't be

able to identify you until you're in their database of known faces. That's the “memory”

of the system - and it's separate from the training images.

In the case of the iphone's faceID, it's a database of one - you volunteer to store

your face on your device in exchange for easily unlocking your phone.

Companies like Facebook and Google also keep databases of their users. But it's governments

that typically have access to the largest databases of names and faces, so facial recognition

significantly expands the power of the state. They collected these images for other reasons

and now they're repurposing them for facial recognition without telling us or obtaining

our consent, which is why several US cities have banned government use of facial recognition.

Retail stores, banks, and stadiums can create or buy watchlists of known shoplifters, valued

customers, or other persons of interest, so they're notified if one of those people

shows up. And then there's another source of labeled

photos. Those are the ones we've been labeling ourselves by setting up profiles on social

media networks. It's typically against the terms of use

to program bots that can download faces and names from Linkedin, Twitter, of Facebook,

but it's doable. And what's at stake is something that most

of us take for granted: our ability to move through public spaces anonymously.

"So we typically think of public and private as being opposites. But is there such a thing

as having privacy when we're in public?" "I would like to think so."

Evan Selinger is a professor of philosophy who argues that facial recognition is a threat

to “obscurity,” Which is the idea that personal information is safer when it is hard

to obtain or understand. "So We have natural sort of limitations in

what we can perceive and what we can hear. Even the human mind has a sort of basic limits

in how much information it can store. So one of the things that technologies do

is they reduce the transaction costs of being able to find information, being

able to store information, being able to share information, and being able to correctly interpret

information. And so facial recognition is probably the most obscurity-eviscerating technology

ever invented."

We don't have to imagine how this could play out. It's already happening with photos from

the Russian social media network VK. Aric Toler, a journalist who covers Europe

for Bellingcat, showed me how it works with a random video of Russian soccer fans picking

fights in Poland. "There's about 10 or so of these soccer hooligans

in this video and for every single one of them you can find their profiles on VK. OK

I'll get this guy in the background. Let me save him. OK so here's the first result. This

guy. So if you click the photo here it will take you directly to the photo's link. And

here he is. I think he's wearing I think he's wearing the same shirt. Yeah he's wearing

the same shirt even. This is him too. So this is probably like his buddy who uploaded a

photo. Yeah. So this is this guy's profile and here's his buddy right here. Yeah so here

he is during a baptism, probably." "And the photo you uploaded is not particularly clear

or high resolution." No "not at all, right, it's just a 200 by 100. So it does feel weird

when you do this and you have access to way more information than you should, is what

it feels like. But also we only publish what we're like one thousand percent sure of

and if possible we maybe dont include the names of the people."

How you feel about this technology probably depends on how much you sympathize with the

person being identified. Bellingcat has used these tools to find identify

people linked to the attack on flight MH17 in Eastern Ukraine. It's also been used

to doxx police officers accused of brutality, anti-corruption activists protesting against

Vladimir Putin, random strangers as part of an art project, and sex workers, porn performers,

and others who have posted anonymous photos online.

"The way that we share our images and our names on social media, LinkedIn Twitter, Instagram,

it seems to suggest that we don't want to be obscure or we're not really looking to

be anonymous. Are we allowed to want to share and connect with other people online and still

be able to expect not to be recognized when we're offline in our regular lives?"

"I would say absolutely. In fact I would go further and say if we ever create a society

where that's not a reasonable expectation, a lot of the things that are fundamental to

being a human being are really going to be compromised.

Having any individuality requires experimenting in life and experimenting requires the protections

of some obscurity. But also intimacy requires obscurity. Right. If you want to be able to

share different parts of your life with different people, and I think most of us do right. We

don't want to come into work and behave the same way we do with our friends. We don't

want to treat our partners in the same way we do acquaintances. And the concern, when

you lose too much obscurity, is that these domains bleed into one another and create

what's called context collapse. And it doesn't mean that one is more real or one is more

authentic. Leading a rich life requires us to be able to express ourselves in these diverse

ways." The photos we took to share with friends,

or document history, or simply get a government ID have been used to build and operate a technology

that strips away the protections that obscurity has always provided us. It's nothing less

than a massive bait-and-switch. One that could change the meaning of the human face forever.