Safety in Numbers?
Um artigo
publicado na Frieze, março 2014.
www.frieze.com/issue/article/safety-in-numbers/
Algorithms, Big Data and surveillance: what’s the
response, and responsibility, of art? Jörg Heiser asked
seven artists, writers and academics to reflect.
Trevor Paglen, They Watch the Moon, 2010
TREVOR PAGLEN
Something fundamental is changing in the world of
images, and in the landscape of seeing more generally. We are at the point
(actually, probably long past) where the majority of the world’s images are
made by-machines-for-machines. In this new age, robot-eyes, seeing-algorithms
and imaging-machines are the rule, and seeing with the meat-eyes of our human
bodies is increasingly the exception.
Machines-seeing-for-machines is a ubiquitous
phenomenon, encompassing everything from infrared qr-code readers at
supermarket check-outs to the Automatic Number Plate Recognition (ANPR) cameras
on police cars and urban intersections; facial-recognition systems conduct
automated biometric surveillance at airports, while department stores intercept
customers’ mobile-phone pings, creating intricate maps of movements through the
aisles. Beyond that, the archives of Facebook and Instagram hold hundreds of
billions of photographs, which are trawled by sophisticated algorithms
searching for clues about the behaviours and tastes of the people and scenes
depicted in them. But all of this seeing, all of these images, are essentially
invisible to human eyes. These images aren’t meant for us: they’re meant to do
things in the world; human eyes aren’t in the loop.
All of this is new. Although Guy Debord’s spectacle
society has certainly not gone anywhere, the advent of ‘operationalized’
images is upon us. The 21st-century landscape of images and seeing-machines
directly intervenes in the surrounding world. Seeing-machines do
things-in-the-world not through the subtle ideologies of visual mythmaking and
fetishism, but through quantification, tracking, targeting and prediction.
How do we begin to think about the implications on
societies at large of this world of machine-seeing and invisible images?
Conventional visual theory is useless to an understanding of machine-seeing and
its unseen image-landscapes. As for art, I don’t quite know, but I have a
feeling that those of us who are interested in visual literacy will need to
spend some time learning and thinking about how machines see images through
unhuman eyes, and train ourselves to see like them. To do this, we will
probably have to leave our human eyes behind. A paradox ensues: for those of us
still trying to see with our meat-eyes, art works inhabiting the world of
machine-seeing might not look like anything at all.
Trevor Paglen is an artist.
