Medium Specificity and New Media

See page 10 in The Language of New Media

“I scrutinize the principles of computer hardware and software and operations involved in creating cultural objects on a computer to discover a new cultural logic at work”

Lev Manovich, as he sketches out his approach to a criticism of new media, here alludes to the art-critical philosophy of medium specificity, popularized in the early 20th Century by Clement Greenberg and others.

A basic tenet of this approach holds that art should be evaluated in relation to how it addresses itself to what are often taken as the material properties of a given medium. The original impetus behind this approach was an attempt to reconcile the lack of traditional aesthetic features in Modernist art with the recognition on the part of the public and art institutions that the Modernists were, in fact, making art.

A stretched canvas that appears to be uniformly painted white is an often-parodied example of the artistic genre medium specificity was designed to address. In the context of a medium-specific analysis, one might consider the material application of white paint to the canvas from a number of different perspectives: how the artist behaved while applying the paint, how light affects the texture of the paint, or how on close inspection minor imperfections in the pigmentation affect what one sees.

However, the products of computerized media are not always amenable to such an analysis, especially in the absence of very specific types of qualifications.

Computers store information, and though art understood as computerized information can be understood materially, the material explanation required by such an understanding involves physical descriptions of space and time on a scale beyond what we readily perceive. Information theory is mathematically related to thermodynamics, but we do not readily apprehend the mechanical details of thermodynamic flows as well as we understand what happens when a glass is knocked off a table.

The scale of a computer’s physical operation involves components such as transistors which are too small for us to see. In using plain language to describe new media in terms of such components, we must rely on descriptions made by analogy, or on descriptions of how computers behave as formal systems. If the formal relationships governing the behavior of either side of an analogy are not carefully taken into account, we run the risk of making inferences that hold for one side but not the other. Such inferences might make logical sense in terms of the plain-language sentences used to describe them, but the descriptions that follow from the vocabulary of one side of the analogy might contradict with what is mechanically probable in the other side. If, when talking about sports, we assume that “Whoever has the highest score wins,” such a supposition might prove helpful when making an analogy between basketball and football, but would prove to be a problem when comparing tennis to golf.

An example of this difficulty can be found in the First Principle of New Media identified in The Language of New Media. The First Principle of New Media holds that new media objects are represented numerically. It is assumed that this numerical feature of new media objects is of fundamental importance to both the design of computer hardware and software; yet numerical features are not what we perceive when watching a montage sequence in digital cinema. Rather, we see juxtapositions of forms and objects; it may well be possible to describe these forms and objects in numerical terms, but that does not mean such descriptions are perceptually meaningful, or of fundamental importance to explaining what we see. We do not perceive objects to be “even” and “odd” the same way we perceive numbers as such; we might say a physical surface is “even” or a color palette is “odd,” but these words are not used in the same sense as when they refer to numbers.

The linguistic consequences of this conceptual problem occur at various points throughout the text, detracting from both the value of the methodology and the validity of the conclusions.

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