“Logical depth” refers to the paradox of apparent transparency in a medium whose processes are increasingly hidden, a point made by Thrift in his posing of software as a “technological unconscious” (‘Beyond Mediation’ 241). The quality of hiddenness also arises from computing as an essentially nonvisual medium: Cramer explains, “The internet is accessed largely by graphical browser and client programs but with the constant awareness that non-graphical codes are running underneath the system” (98).
Charles H. Bennett provides the foundational concept of hiddenness in computing with his definition of logical depth, a phenomenon that factors into a piece of information
or a solution all the calculations an originator had to do in order to arrive at it (3).17 Wendy Chun maintains that the computer is nonvisual and nontransparent, but it has fostered a primary focus on visuality and the belief that it affords more transparency than other media (“On Software” 27). Axel Fliethmann explains this seeming contradiction:
how can a medium that is all about visuality be nonvisual? He offers the reason that
“digital technology treats image and text as the same form within the opacity of its code, and can only visualize both as different forms on its surface” (55). In other words, the computer screen is the surface interface. All available information is visible on the screen and can only be seen or heard. But the code creating these seen and heard forms is text and only text – and almost always English text – which the machine has to translate into patterns of zeroes and ones.
Laura Marks relates logical depth to the Shia Islamic terms of zahir, exoteric knowledge, and batin, esoteric knowledge, and by extension to computer-generated art, which is, in cybernetic terms, about the code, not the content. Another connection is made by Frederica Frabetti, who takes up Derrida’s concept of deconstruction as a method of unpicking a conceptual system to ask, “What is it that has to remain unthought within the conceptual structure of software” (8)?
17 In algorithmic processes like those computed by a Turing machine, a logically ‘deep’ or complex object is one that requires a lengthy calculation. Bennett argues that complexity includes a kind of buried redundancy consisting of all the calculations the originator had to do in order to arrive at a valuable piece of information. He refers to the halting problem – whether a computer program will continue running forever to try to solve a problem.
Scott Dexter and Adrian Mackenzie address hiddenness as a result of the layering of functions in object-oriented softwares that result in more and more functions being hidden and inaccessible not only to the user but also to the programmer. Dexter describes Alan Turing’s experiments with mechanical computation in which Turing found that a complex calculation needs to include “disposable intermediate figures” that are just there to assist fallible human memory (‘The Esthetics of Hidden Things’ 130) − an example of Bennett’s logical depth. He goes on to recount the rise of object-oriented software that organizes information into sets as economies of memory allocation and then conceals the sets from the user and from other programmers (‘The Esthetics of Hidden Things’ 140).
This new quality of hiddenness in software – that it has layers inaccessible even to the programmer, making it possible to hide its workings, is allied with, but not identical to, logical depth. The former quality of hiddenness has resonances for Chun with a
somewhat pernicious normalizing function, a tendency to take certain assumptions for granted. Chun urges the reader to critically interrogate software, because “reducing ideology to software empties ideology of its critique of power—something absolutely essential to any theory of ideology” (44). In contrast, logical depth marks Deleuze’s possibility space, a fertile space that dwells in the virtual as opposed to the actual layer of the world (Difference and Repetition 102). Taking up Bennett’s and Turing’s
interpretation, I would argue that suppositions, beliefs, and paradigms reside there as well as calculations that are no longer needed; for Deleuze, alternate versions of historic and mythic events are in virtual space, where Caesar did not cross the Rubicon (The Fold 98), Sextus did not rape Lucretia (The Fold 61), Adam did not sin (The Fold 104), and the
labyrinth has no thread because Ariadne has hung herself, presumably with the thread (Difference and Repetition 56).
For Mackenzie, sets as devices in object-oriented programing are so ubiquitous that they are considered trivial and, as Carroll remarked about the Amish quilt, “beneath interpretation.” In a further move that references Deleuze’s multiplicity theories and software, he mentions Deleuze’s resistance to set-based thinking: “A vital multiplicity for him . . . has no parts or elements. It only has intensive differences actualizing as extended things, with boundaries, with orderings” (‘Set’ 230). Deleuze’s sentiment about vital multiplicity resonates with Elkins’ and Hays’ reflections on the subsemiotic elements of visual images, and all three can be understood in relation to elements of code that are considered “trivial.” In a passage entitled “Why Study the Paint?” Marino defends studying code critically because it is not “merely” a means or procedure, it is a text (7).
This seems to me to be a case of a writer justifying his attention to code by giving it a status of importance. I reiterate here my purpose is not to elevate pattern up above a sub-interpretive or subsemiotic level, but to go down to where it is and examine it. In so doing, I am looking for what it is in visual pattern that takes it beyond decoration or ornament, with their connotations of supplement – as I said, on its own grounds and in its own terms. Elkins, Hay, and to some extent Cramer, provide clues about where to look, and how to interpret what I sense about pattern: that its meanings are subtle, paradoxical, hidden, labyrinthian, and even slippery and evasive. Pattern hides on purpose.