Geographies of Photography

Over the last few weeks I’ve been laying out some ideas about what photography has become, and have begun to articulate some of the ways I use to think about it. In previous posts, I wrote about replacing a more conventional idea of photography with the idea of seeing machines and put forward the idea of “scripts” to begin understanding how seeing machines function, i.e. how they act upon the world. I wrote about scripts as being the range of activities that a seeing machine “wants” to do, and the range of possibilities that those “wants” facilitate, and the range of possibilities that are foreclosed. To illustrate the idea, I used the example of an Automated Number Plate Reading (ANPR) system, and tried to show how the cameras, shutters, and lenses of such as system are totally irrelevant without the “back end” of signal processing, data bases, analytics, search algorithms, and the like. All of these add up to a seeing machine that “wants” to perform a rather narrow range of tasks, and thereby sculpts the world in some very specific ways.

One of the key reasons for introducing the idea of “scripts” was to introduce a relational approach to thinking about seeing machines. In today’s post, I want to expand that relational approach and to show how scripts quickly give rise to much larger relational landscapes of seeing machines. I think of these as “geographies of photography.” To walk through the idea, we’ll briefly return to the example of an ANPR system.

Behind any seeing machine is a field of political, economic, and cultural interests. In the case of Automated Number Plate Reading (ANPR) systems, we find political interests such as intelligence and law-enforcement agencies that desire to efficiently surveil huge amounts of vehicular traffic. There are economic interests, such as city governments trying to increase revenue by automatically issuing traffic tickets to speeding vehicles, and companies like Vigilant whose business models involve selling access to their massive, privatized vehicle location databases. There are cultural aspects to ANPR systems having to do with what sorts of surveillance are normalized, and questions about the relationship between citizenry, state, information, and economy (these questions are all central to the Utah lawsuit around Vigilant I mentioned in the last post). This web of relations around a seeing machine such as ANPR forms the beginning of what I mean by “geographies of photography,” which has to do with all of the ways in which seeing machines are involved in the production of space, or how seeing machines play a role in sculpting everything from economies, law, politics, and culture to the sculpting of space and time itself. The idea of “geographies of photography” is quite huge (it deserves its own book), so I’ll only have space to sketch it out in the briefest of fashion here.

I’ll begin with the word "geography." With it, I mean something that has almost nothing to do with "cartography" or "mapmaking." Instead, geography has to do with how humans sculpt the Earth’s surface, and how humans and societies (everything from bodies to politics and culture) are, in turn, sculpted by the ways we’ve sculpted Earth’s surface. 1 I’d include orbital space and “deep” space in this understanding as well. And I don’t think that inclusion would be particularly controversial among critical geographers these days. It’s crucial to understand this as a feedback loop, or dialectic, wherein the material “stuff” of the world often plays an active role in sculpting societies. “Geographies of photography” has to do with the specific ways in which these dynamics happen through seeing machines.

“Geographies of photography” are produced through numerous dynamics, but to give ourselves a little bit of a roadmap towards analyzing them, we can loosely follow critical geographers like David Harvey, and broadly use categories like “material,” “relative,” and “relational,” as starting points. The boundaries between these three aspects of geography are extremely porous, and utterly interrelated, but nonetheless, these concepts can serve as helpful placeholders to think about geographies of photography.

I think that material aspects of photography or seeing machines are often overlooked: the light-sensitive silver halide crystals that come, in part, from mines dug deep into the earth, and which underlie nearly all “analog” photographic processes (historically, Kodak has been the world’s largest consumer of silver); the methylene chloride used to make the plastic base in film; the acetones and dioxins. These materials have specific histories, economies, politics, and ecological footprints. The “analog” film industry has had a tremendous environmental impact. For example, between 1987 and 2000, Kodak’s home of Rochester, New York, had the highest rates of carcinogenic chemical releases in the United States, with the photo manufacturer being responsible for the vast majority of that pollution. A local joke holds that you can develop film in the Genesee River adjacent to the Kodak plant.

Digital cameras are similarly grounded in the material world. Like their analog forbears, these machines used to capture, process, and display digital images have specific mineral and political histories: The tantalum, tin, and gold used in digital imaging systems, for example, come in part from mines in the resource rich areas of the eastern Democratic Republic of Congo. Mineral extraction in the eastern DRC is controlled by armed militias who use mass rape, child labor, and murder to secure power; millions have been killed in the civil wars that have been funded by these so-called “conflict minerals.” Those of us who use digital cameras carry little pieces of these minerals, and the ultra-violence that begat them, in our pockets and around our necks.

But just as the production of seeing machines involves digging great mines shafts into the earth – a process that is both political and geomorphic – and sculpting the earth’s surface, seeing machines are tools with which to bend and reconfigure space and time itself. Seeing machines create noncontiguous spatial and temporal geometries. They collapse the near into the distant, and the present into the past and future. To illustrate these “relative” geographies of seeing machines, I’ll use the example of a Reaper drone. What exactly is a Reaper drone? In essence, it’s a camera attached to a remote-controlled airplane. Sometimes it carries missiles. What’s particular about a Reaper drone (and other drones in its larger family, including the Predator and the Sentinel) is that airplane, pilot, navigator, analysts, and commander don’t have to be in the same place. The aircraft might be flying a combat mission in Yemen by a pilot based in Nevada, overseen by a manager in Virginia, and supported by intelligence officers in Tampa (geographer Derek Gregory has written about what he calls “Drone Geographies.”) The drone creates its own “relative” geographies, folding several noncontiguous spaces around the globe into a single, distributed, “battlefield.” The folding of space-time that the Reaper drone system enables is a contemporary version of what Marx famously called the “annihilation of space with time,” i.e. the ability to capitalize on the speed of new transportation and communications technologies to bring disparate spaces “closer” together, relatively speaking. Photography has been a part of this space-time annihilation from the start, which is one of the subjects of Rebecca Solnit’s book about Muybridge and technology, River of Shadows (full disclosure: my all-time favorite book on photography).

Although seeing machines have played a part in the “annihilation of space with time” since the 19th century origins of the phrase, they are increasingly playing a role in creating new relative temporal geographies, perhaps something akin to an “annihilation of time with space.” Emerging “persistent surveillance,” systems from automated license plate readers to more advanced imaging platforms like the Defense Advanced Research Project’s (DARPA) Argus-IS system allow continuous monitoring and image-making, and are capable of collecting staggering amounts of visual information. What’s more, as the cost of indefinitely storing data rapidly diminishes and the algorithms to search and process that data improve, it’s becoming more and more possible to “see through time” – to produce colossal databases that allow users to “rewind” time to specific points and to see a moving snapshot, and associated metadata, of a particular interval of time. With predictive algorithms, analytic algorithms attempt to predict the future based on past and present patterns (the case of retailer Target identifying pregnancies before family members is a well-known example). There’s every reason to suspect that if the 19th Century saw the annihilation of space with communication and transport technologies, then the 21st Century may see a similarly dramatic reconfiguration of time through persistent monitoring, storage, and analytic technologies that can “reach into the past” in unprecedented ways. Of course the ability to bend time through photography also goes back to the 19th Century, albeit on a far more modest scale, most obviously in phenomena like post-mortem and spirit photography.

If “geographies of photography” have to do with the production of material and relative geographies, a third aspect of them is the production of relational geographies. “Relational geographies of photography” is itself an enormous subject, having to do with the cultural, economic, political, and social space produced through seeing machines. On the cultural side, we find a veritable “greatest hits” of photography theory questions: indexicality, spectacle, mythology and so on, i.e. questions about the various kinds of cultural “work” done through images, photographic technologies, and relations among people as modulated by photographic technologies. But there are numerous other aspects to the relational geographies of seeing machines. To sketch out the beginnings of what a relational geography of a seeing machine looks like, let’s use the example of an American spy satellite, which is really nothing more than an advanced camera in orbit.

Creating a secret camera in orbit means creating a relational geography of a truly astonishing scale. From the get-go, creating a secret camera/satellite means creating a secret aerospace industry – companies like Lockheed Martin, Boeing, and Northrop Grumman – to develop, deploy, and often operate the spacecraft. The secret aerospace industry has to be funded, which means creating a classified economy of military spending worth billions of dollars annually – money that underpins the economies of various regions in the US including much of Southern California, Silicon Valley, and Northern Virginia. But there are also political aspects to the secret industry and economy that spy satellites require: secret spending means creating a so-called “black budget,” an entire sector of the American military budget that is exempt from Congressional and public oversight, a serious distortion of the political system and consolidation of power in a small number of hands. What’s more, a secret multibillion dollar aerospace industry means hundreds of thousands of workers who must be compelled not to speak about what they do, which means creating a vast security-clearance industry, classification systems, laws to enforce silence, and so on. And we haven’t even got to the more cultural and epistemological questions about the actual images taken by spy satellites’ “view from above” (Laura Kurgan’s recent book Close Up at a Distance is about this). The point is that the spy satellite/orbital camera is produced by and, in turn, productive of an enormous relational geography with political, economic, legal, social, and cultural aspects.

It seems to me that most people who spend their time thinking about images would not dispute the notion that images help actively sculpt the world. From Robert Mapplethorpe challenging hetero-normative depictions of gender, to McDonald’s using images to colonize the minds of children, it goes without saying that images strongly shape the way humans make sense of the world. But I’m suggesting that there’s a harder edge to this as well. The production of images doesn’t just move cultural attitudes and norms, it literally moves mountains.

The various aspects of a “geography of photography” that I’ve sketched out (material, relative, and relational) are utterly entwined. It’s almost absurd to discuss silver or tungsten without accounting for the environmental and political consequences of its mining. But that’s really the point – thinking about “geographies of photography” in terms of material, relative, and relational geographies is useful to me because it is a way to continually remind ourselves that images, photographs, cameras, or seeing machines are not autonomous things that can be easily separated from the role they play in actively sculpting the world.