Notes

Chapter 3: Intention and Artifice

This particular text is on photography, and its role as representing the truth. The credibility of photographs has, after a long period of time of claiming to represent the whole objective truth, or at least representing that something happened. This criticism runs deeper than a rejection of photographs as merely objective. The idea that the camera is a viewpoint, must take a physical position, and is thus inherently subjective has been around and acknowledged. However, the photograph still stood as a proof of existence.

Mitchell is concerned with the constructability of photographs and the fact that they are subject to the same kind of artifice that any other form of evidence is.

Photographs are fossilized light: momentary interpretations that have been made permanant by their exposure on film. They can be seen as records, but like any record, they construct a system and view of reality.

Photographs have a strong connection with matters of convention, for a long while, painting was rooted in matters of convention (Ancient Egyptian figures are a good example), but photography adheres to its own conventions as well. The characteristics of shading and lighting and all of these aspects are firmly grounded in the conventions of the photographic tradition. In turn, these conventions connect with our means of reading and perceiving information from signs encoded in this convention. Mitchell cites Roman Jakobson who explains that over the course of tradition, images become ideograms which are immediately mapped to ideas, and we no longer see pictures. This idea relates again to the traditions of media gradually becoming more transparent over time.

Photographs themselves tend to be deeply connected to their subjects, though: “since photographs are very strongly linked by contiguity to the objects they portray, we have come to regard them not as pictures but as formulae that metonymically evoke fragments of reality.”

This line of reasoning also seems to connect to the ideas of simulation sublimation. Images are seen as semiotic systems, and are internalized, or are, at least, taken to denote the truth when cast as such (which is how we have approached photography culturally). It is only recently that we have begun to exhibit a kind of awareness of the artificiality of the image that we can criticize photographs as non-representative of the truth. I imagine that similar arguments can be made toward simulation, but its artificiality is generally much more apparent.

The part of the camera that lends it its authority is its mechanical nature. Because it is a machine, seemingly untouched by other values or human intervention, it mechanically must capture the truth without the factor of human error. The ramifications of the “superiority” of machine reproduction and capture are documented (for instance with Walter Benjamin), but the near autonomous power of the machine emerges in a great deal of AI criticism.

Cameras impose the existence of a subject, though. It is impossible to take a photograph of “no particular” horse or person, though it might be possible to make a picture of them. The necessity of this particular subject is the essence of the camera’s intentionality. This intentionality is also where the camera’s subjectivity comes into play, and it introduces values based on the question of framing, perspective, and choice. Mitchell explains that this forms a spectrum: “However, Scruton’s distinction between intentional and causal components in image production is helpful, particularly if we do not insist on a clear cut dividing line between paintings and photographs but think rather of a spectrum running from nonalgorithmic to algorithmic conditions–with ideal paintings at one end and ideal photographs at the other.” (p. 29)

The problem that arises in comparing this to computation is that even algorithms have biases and values.

Digital photography and photo editing blur the lines between causal and intentional images. Something which is intentional can be hidden and be made to seem a natural causal element. This perverts the authority of the mechanical process by which photographs tend to derive their legitimacy.

Reading images requires a certain interpretive labor to be undertaken by the observer, and this process is where the influence of convention comes into play. “In forming interpretations of images, then, we use evidence of the parts to suggest possible interpretations of the whole, and we use the context of the whole to suggest possible interpretations of the parts.” (p. 34)

The problem of altering images involves balancing the alteration with the requirements for consistency and coherence in the relation of parts to the whole. Beyond that, we can check for implausibility, by comparing the subjects to that which we already know to be true (or might be able to verify externally). This sort of issue pulls back and seems to reflect ideas being worked through in AI and cognition. When faced with a black box that explains something that we have no means of verifying or checking, but are grounded in a photograph-like mechanic, we have no choice but to accept the result. The examples Mitchell gives are the photographs of the astronauts on the moon, but that idea can be extended to other regions, such as simulation.

Mitchell writes of the general acceptance of images: “In general, if an image follows the conventions of photography and seems internally coherent, if the visual evidence that it presents supports the caption, and if we can confirm that this visual evidence is consistent with other things that we accept as knowledge within the framework of the relevant discourse, then we feel justified in the attitude that seeing is believing.”