Trevor Paglen is an artist based in Berlin.
His work has made headlines for exploring CIA black sites,
drone warfare,
and America’s secret security apparatus.
His latest project tackles computer vision.
— On any given day, or any given minute,
more machines are analyzing images,
and seeing them and making sense of them,
than humans are.
— Entitled “The Atlas of Invisible Images,”
the work provides a window into a world of surveillance and computer analysis
that most of us just don’t think about.
— I kind of collectively call them “invisible images,”
because they’re images that are not for us—
they’re images for computers.
We don’t see them.
In many cases, we don’t have access to them.
And so, I’ve been doing this huge exploration of that,
trying to understand what the mechanics of computer vision are,
and what its implications are—
not only for image-making, but sociological and political implications
and that sort of thing as well.
— Computer vision,
training computers to recognize objects and people,
is already used for advertising, security and social media,
and will likely become even more widespread.
Paglen has trained his own A.I. much like those that are being quietly deployed elsewhere:
by feeding it thousands upon thousands of raw images.
— Where do you get all these images from?
— When you’re doing this kind of research,
in general, you’re using standardized training sets.
There’s training sets for recognizing emotions,
recognizing faces,
recognizing different kinds of objects.
And there’s even weirder ones,
like recognizing different kinds of fast food,
or different kinds of kittens, or whatever.
— Most of these training sets were compiled by universities
doing computer science research in the 1990s.
Nobody expected that they’d be the basis for nearly all image recognition 25 years later.
— And so when I’m looking into this webcam,
what’s it interpreting me as?
— It says you are a Band-Aid.
Or you might be an oxygen mask,
but you’re probably a Band-Aid.
— That was really… that was really brutal.
That was not necessary, I thought.
— It’s being a little bit racist,
it’s telling you that you’re probably a monkey now.
This one is not really trained on humans.
— While it’s awkward to be categorized as a proboscis monkey by a computer,
what’s more unsettling is how artificial intelligence arrives at such conclusions.
— For example, if you are putting an image on Facebook,
what your experience of that is, is similar to a photo album.
What a typical facial recognition algorithm would do
is take all of those images of your face that it knows are you
and combine them into a meta-image of your face.
Then it’ll take your face,
and subtract from you what you have in common with everybody else,
to arrive at what is a unique fingerprint, as it were, of your face—
what is different about your face.
So that’s an example of an invisible image that a computer algorithm invented for itself.
But there’s nothing in the world that says
you have to train A.I. on common sense objects.
— To show that what computers see is a surreal version of the world,
based on what they have been fed by their programmers,
Paglen trained his computers on images themed around Freud’s dream symbols,
American predators,
and historic metaphors for capitalism, among other things.
— I guess when you do more abstract or surrealist data sets,
you’re asking a different question than vision—
you’re asking how they think, to some extent.
— Exactly.
One of the wonderful things about humans
is that we are constantly able to redefine the ways that we make meaning.
This is one of the philosophical dangers of using widespread automation,
which is that it fixes meaning.
That’s one of the things that I’m trying to get at with this body of artwork,
is to try to point out that vision is always culturally constructed,
and constructed through politics, and constructed through history.
— Even in Berlin,
a city which is suspicious of surveillance after years of Soviet eavesdropping,
Trevor’s Atlas seemed far from an academic exercise.
All around us, people were uploading selfies—
which are often used by social media and search companies
to build their own computer vision databases.
— Really, that’s the point of my project:
I’m pulling these invisible images
because it really is our technologies and forms of seeing
that surround us, literally, all the time—
but our eyes, which are made out of flesh,
are not capable of seeing.
— What would you say to all of these people who are happily making selfies,
I presume, reasonably, oblivious of the interests that lie behind the companies?
— I would love to live in a world where all of us could make all the selfies that we wanted.
But I guess the guiding assumption that I always make with this sort of thing is that…
who stands to benefit?
Big companies benefit.
Police benefit.
Militaries benefit.
And often times,
that benefit comes at the expense of individual people.