Category: Readings

As a NON-photographer, it was really useful for me to get this history lesson from “Photography and Observation,” to learn how the “purpose” of photography has sort of co-evolved with its capabilities over the last couple centuries. There’s a lot to unpack here, but I’ll mainly focus on:

1. the concept of “objectivity” and “reliability” in these evolving methods
2. how this plays out in typology

Objectivity & Reliability

I like the way this reading describes the shift from photography as a (extremely cumbersome) way of capturing what we see, to a way of allowing us to see new things entirely. In other words, a shift from photography as a method for documentation to a method of perception. By showing us the “un-seeable” we are forced to reconsider entire philosophical frameworks about what is “real” and what is “fake.”

My background in cognitive science makes me particularly interested in the ways in which all of human perception is essentially a lesson in experimental capture – everything we see, feel, hear, smell is an image, passed through the “lenses” on the skin and in the brain into something we can understand. What we experience is not the “real thing” (and many philosophers argue that there is no “real thing” anyway). Lots of people think this is scary. I think this is awesome.

Capture & Typology

In the latter half of the reading, the author begins to talk about photogrammetry and stitching images together, and then arrives at breaking images apart. This is where typologies really come in.

“The use of the strobe or spark for instance, when applied to photography… is a powerful tool for the isolation of single elements in the stages of motion.” 

“[The arrival of] high-speed photography…broke human and animal motion down into finely distinguished moments.

I love this idea of typologies as a way to break something down into more digestible pieces. We see Muybridge’s “Animal Locomotion” of the running horse. This also reminds me of the Time Magazine examples from class, where the artist blacked out everything but the faces on the front page.

This deliberate break-down of gestures, events, and interactions usually taken for granted is an opportunity to reveal things “too small, too fast, too comples, too slow and too far away to be seen with the eye.” I’m curious how this idea can continue beyond the obviously visual and break into our other senses.

 

I like how the reading ends. It brings us full circle, describing how “x-ray photography arrived at a time when the reliability of photography was acutely questioned.” This was a time when the impression of photography as an “objective” source of truth was “beginning to wear thin” due to photo editing, staged events, etc. Are we not in a similar place today?

X-rays in this way reconnected the world with the dominant Western, scientific, truth-seeking discourse of the time. We are in an era today where politics, technology, etc. have likewise disconnected us from that discourse. Will we as a society find a “new x-ray” to cling back to that fleeting vision? Or is the discourse simply changing for good (and maybe for the better)?

The medium of capture can substantially influence a typology since different aesthetics and data can be depicted which can influence a viewers interpretation of the image. For example, choosing a medium which captures an image using infrared will expose different data and could possibly reveal information about a typology that would differ if images were captured with a DSLR camera.  To a certain extent I believe photography is objective and can be scientifically reliable; however, I still believe that the operator of a medium of capture has to make decisions which can influence what is depicted in the image. Different exposures, lighting conditions, and angles are just a few examples how even just one medium of capture can have images of a single subject that significantly vary in their aesthetics. Though they may all reveal the same data about a subject, their is still room for alterations, different aesthetics, and different impacts from the images; therefore, I believe contemporary captures are a partially subjective medium. Choosing different mediums of capture, such as film, digital, x-ray, etc., is a choice by the operator; however, one would argue that the expected result is predictable and scientifically reliable in this situation. To this extent photography and capture can be reliable, but there are still choices made, sometimes not even registered as choices, when capturing an image that can influence the result which consequently contribute to this medium being partially subjective.

“Cameras that use ML have the potential to both automate existing functions of the camera as a tool for human use and extend its creative possibilities far beyond image capture.” 

The relationship between a user and cameras that make choices on their own, changes the task of the user from one who captures to someone who creates the situation for the camera to capture. Machine learning cameras turn photographers to curators or installation artists. Authorship would still lay with the user since without their input there would be no system. Although these cameras can “do” more, the expectations of these cameras would be no different than developing film. A captured situation is still present, yet the type of outcome can not be absolutely guaranteed. Cameras, like Google Clips, or systems, like Pinterest’s Lens, are sifters. They go through information to choose what may be wanted. Taking a hundred photos and choosing a couple manually is the same process. The camera is still a tool unless it can form or embed itself in the situations in which it captures. The tools presented just take a familiar process and put it in an unfamiliar vessel.

The Clips camera system makes me pessimistic about human’s developing relationship with artificial intelligence. If photography is an expressive outlet, or a way to communicate perspective, what purpose does this system serve in terms of capturing humanity? We have all of these tools that let us take photos, which have been developed to be “easier” to use, but this only serves to eliminate the control that a person has over the tool (even though there is still control over where the camera is pointed, although they would probably eliminate that too if it was possible).  I think a system like Clips also strengthens cognitive barriers hindering our ability to consider our senses from beyond themselves. It’s designed to deliver a product that most closely resembles how something would look if you saw it in person, so the user never has to consider the media as a result of real, physical processes, only a reflection of they expect. Not only that, but it decides what is significant content, preventing the user from having to consider what’s real that makes content significant. Thinking of the future, if everything we do is aided by artificial guides and standard parameters, what will we all be doing that’s so important to photograph beyond the state’s interest in surveillance?

The Pinterest Lens works in a similar way, and I don’t think it’s as offensive because it’s not a photography tool. It seems to serve more as a search engine that uses image data to associate concepts and things. In other words, this system would work similarly if seeing the photos was removed from the process altogether. You are pointing a device at an object or space, and finding posts about similar objects or spaces.

Bruce Sterling’s concept of future imaging as only computation is intriguing, and similarly unsettling. The implication is that this system of cloud computing is aware of the physical arrangement of matter, meaning whoever controls this system can observe any event taking place, no matter how private. It also means that they can observe people’s dreams, ideas, and feelings via the arrangement and activation of neurons in the brain. Similar things are already being implemented using machine learning to reconstruct a subject’s radiated brainwaves into the image that is being seen by the subject.

In some of the speculative cameras described in the article, the user/operator and cameras/sensors relationship moves very much away from the traditional relationship that point-and-shoot cameras had between their user and camera. One way in which this seems to be happening is along the lines of agency of the situation. In more traditional photo camera’s the agency of the capture is at the behest of a user’s specific action and choice to engage with the camera – simply having access to the device does not allow for a capture to occur.  In some of the situations discussed by Ervin, the question of agency changes to one where the action switches over to one where the agency is at the beginning of the situation where the terms for a potentiality of photographic situations to occur are created. If one has a camera that can take pictures on its own, learn from its actions, an is always operating then the last opportunity for the agency of the capture (in the 20th century sense of the photographic capture) occur at the onset instead of the moment of the performative ‘click’ of the camera. So here we have a situation where the device is always performing at the user’s initial request, and performing on its own in a way that the used to require a union of performative relations between person and machine.

This question of the performative agency happening at the beginning of the situation opens up larger questions about the relationship to agency amidst  the user/operator and cameras/sensors relationship as cameras out in public begin to take on the computational qualities described by Ervin. What happens to the relationship when the consent of situational agency is removed by increased proliferation of these devices in an unregulated manner that arises out of the conditions of America’s late capitalism? When will this capture performance start? What is the Amazon Ring gonna do to us (performatively)?

This article makes clear that traditional notions of the camera break down when the machine is given “its own basic intelligence, agency, and access to information.” The labor divide between photographer and camera, human and machine becomes blurred and inconsistent. Examples such as GoogleClips and automatic image manipulation technologies suggests that taking photos or using a camera becomes a more scaffolded activity. It may seem that the increasing ‘agency’ of the camera results in a reduced sense of agency for the user of the camera — the machine is doing more, and the human is doing less — but is it also possible that the singular authorship associated with our notion of the camera is a myth? The agency of the operator — perhaps the individual who presses the button — might be more limited, but there are other people behind each camera — users, designers, engineers, scientists, business interests — who decide which realities are chosen and how they are captured and rendered. Any system of machine intelligence follows policies, and most of the times the policies are defined by human beings. Someone had to define what a “well-composed candid picture” means when designing GoogleClips. Portrait filters are based on transient standards of beauty.

Maybe, the labor model of the camera today should be one that recognizes the multiplicity of authorship involved in creating an image. Instead of emphasizing giving agency to an individual user of the camera, what would happen if we begin to emphasize a more transparent, and collaborative relationship between the multiple decision-makers behind the capture and creation of images?