Parsing the Languages of the 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.

“The most likely reason modern media has discrete levels is because it emerged during the Industrial Revolution… Not surprisingly, modern media follows the logic of the factory.”

The argument here suggests that the way new media objects implement computer code is a product of the industrial mindset, with the implication that the values of industrial division of labor, specialization, and standardization led to the modern computer. This suggestion involves a complex set of interrelations between the thought processes introduced by industrialization, the structure of computers, and how these thought processes interact with the structure of computers when people create new media objects.

New media objects are conceived of as collections of discrete, indivisible units, such as pixels; and this conception presupposes a contradistinction to traditional media — such as sculpture or chemical photography — where surface properties vary with continuous and arbitrary degrees of detail.

The use of “discrete” here connotes precision, while “continuous” connotes imprecision: however accurately one attempts to measure the height of a bronze sculpture, for example, changes in temperature will cause the metal to expand or contract slightly on different days, contributing to an inherent imprecision in one’s measurement; a digital picture file, however, will always have the same number of pixels no matter on what day one decides to make a tally.

As it is a central feature of industrial mass production that one be able to manufacture large numbers of precisely identical objects, there are a number of superficial reasons why computers might seem to be the product of an industrial mindset: industrial fabrication techniques facilitated computers coming into widespread use, the individual components of computer hardware are in many respects both standardized in their construction and specialized in their function, and the binary code used by computers very much resembles an idealization of industrial order and production.

These congruences aside, however, the aforementioned argument as presented in The Language of New Media involves a number of substantial problems. Most obviously, the written alphabet is a system of discrete symbols: letters came into use long before industrialization, are just as indivisible as pixels in a digital image, and type set in a monospaced font falls into a grid not unlike the arrangement of pixels on a computer screen. Moreover, letters can be assigned numerical meanings: Hebrew is one example of an alphabet that does this.

There are also historical problems with attributing the discrete operations performed by computers to an industrial mindset. The history of computing machines reaches back to antiquity, and its early history can be found in such relics as the Antikythera mechanism. It could be argued that it was “the logic of the factory” that spawned the invention and design of digital computing machines, but it was, rather, a theological motivation that compelled Gottfried Leibniz in the late 1600′s to formalize the system of binary code used by today’s computers; Leibniz furthermore envisaged machines that would perform calculations using his binary system. Although it may be the case that industrialization substantially helped such computing machines in becoming a material reality, their conception lies very much apart from the industrial mindset.

While consumer use of computerized media might in many respects seem to follow “the logic of the factory” — especially as numerous commercial websites profit from user-generated content, which transforms the consumer into a type of specialized producer — the formal and material qualities of modern computerized media follow from a quite different logic.

“Beginning with the basic, ‘material’ principles of new media — numeric coding and modular organization — we moved to more ‘deep’ and far-reaching ones — automation and variability.”

The medium-specific analysis in The Language of New Media attempts to philosophically ground discussion in a material sense apart from relatively subjective cultural factors: the medium is understood primarily as the properties and behaviors of a material thing. While the language of the analysis draws upon diverse concepts in computer science and mathematics, history, behaviorist and cognitive psychology, economics, and aesthetics, missing is a definition of what “a medium” actually is, such that one might consider a given object as being properly discussed in the terms of a given medium.

Given the scholarly tradition towards which The Language of New Media is oriented, it might seem natural to assume that Lev Manovich’s understanding of “a medium” falls somewhere near Marshall McLuhan’s; yet two of McLuhan’s important conclusions — that electronic media would make cultural habits more tribal and more aural — are at odds with central features of The Language of New Media, which holds that cultural habits have been becoming more industrially-influenced and more visual.

Although an approximate understanding of “a medium” for the purposes of discussion might be generally acceptable, the task of distinguishing new media from traditional media on the basis of qualities which both, in important respects, hold in common presents certain difficulties. To resolve these difficulties, one might accept a more informal and broadly-defined understanding of “a medium.” To do so would, however, imply a different philosophical grounding than that used methodologically in The Language of New Media.