Manovich’s most basic principle of new media language is based on its programmability, defined and manipulated entirely with mathematical functions, what the author terms numerical representation. There’s nothing new about representational media—early examples include 30,000 year-old cave paintings found in France and Spain, and grave goods dating to the Middle Paleolithic period. What’s relatively new are the technologies capable of rendering images, sounds, and texts that predate digital programmability into algorithms. Manovich describes some “old” representational media as the rendering of continuous action that carves a defined composition from a larger medium, such as chipping away stone with hammer and chisel or framing light through aperture and exposure. New media linguists (artists and/or programmers) convert continuous data into numerical units by first translating it into discrete units, a process called sampling, then rendering the data mathematically, called quantification. Manovich assumes that most post-Industrial Revolution representational media have facilitated digitalization by combining continuous and discrete data. As one who writes (sometimes), I was immediately sold on the miraculous benefits of word processing, e.g., cutting and pasting, editing on the fly… OK, word processing didn’t necessarily speed up the writing process for me (I’m the slowest writer on the planet), but I like to think it has improved the product.
Manovich’s second principle describes the modularity of sampled and quantified data, as new media objects are made up of smaller parts that can be manipulated separately using various software applications. Another example of modularity the author cites is the World Wide Web itself, made up of countless web pages, each of which can be viewed independently of the rest. The analogy can also be extended to operating systems, which are composed of code modules that carry out discrete functions in given sequences; however, the analogy breaks down on consideration that an operating system won’t run if a module is removed or corrupted, as Microsoft Windows users can attest. I’ve seen modularity’s significance most pointedly in my experience using online platforms to put together and teach online courses. Again, online platforms didn’t necessarily make teaching easier—in fact, I think teaching online is more difficult than face-to-face—but I like the increased access and flexibility it offers students.
On the basis of the first two principles, which Manovich describes as “material,” Manovich derives three “logical” principles characteristic of new media objects (48). The first of these are lower-level automated operations used to generate or manipulate media objects in word- and image-processing software, and higher-level automated functions that drive artificial intelligence (AI) engines in simulation, virtual-reality, and gaming applications. While it’s intriguing to think of computer-generated characters learning and adjusting strategy in a game, Manovich points out that programmers accomplish this level of AI through severely restricting the types of interaction a user has with the characters. Such careful control of the user’s experience is reminiscent of stringent belief systems that predetermine users’ expectations in interacting with predefined tenets, producing self-contained logical loops. I’m not an online gamer so I haven’t experienced AI in that regard, but I have used publication software extensively in my periodic bouts with professional writing and editing, and the automated operations available in programs like Quark and Acrobat beat the hell out of manual typewriters. Another aspect of automated operations that has been incredibly useful in my editing work is online research. Again—the technology is nothing short of miraculous.
The second logical principle characterizing new media objects is variability. As opposed to old media representations that are fixed and immutable, new media objects can be changed by virtue of their modularity. Access to databases through a variety of customizable interfaces further facilitates the elasticity of media objects, as do hyperlinking elements and downloading periodic software updates. Scalability is another aspect of variability; the example Manovich cites is zooming in and out on maps and other images, which often induces changes in resolution as well. Along with increasing users’ power to create distinct representations, these aspects of changeability also increase the responsibility of users’ own decision making in the process of creating and manipulating digital media objects. While the increased responsibility may intimidate some users, I assume many more welcome it. A similar dynamic in the class room comes to mind—what we call collaborative learning methods that shift the burden of the instructor transferring knowledge through lecture to students working together to reach a deeper understanding of the concepts at hand. As for my personal experience with variability, one platform that comes to mind is Google Earth, which I love. My most memorable excursion was revisiting my very favorite spot in the Sierras where I used to backpack and camp and fish with my dad!
Manovich qualifies his purpose, audience, and genre in his discussion of his third logical principle, transcoding old and new representations. To me, this is the most interesting part of the chapter, in which the author identifies two distinct sets of dimensions—those of culture and computer—and constructs the theoretical framework for describing what happens when the two sets merge, and each layer influences ongoing variability in the other. This is where the author’s computer-programming background comes to the fore, and he sets his course by the guiding concepts of programmability, Interface, and database to explore the “more general process of cultural reconceptualization” (47). I love how he contextualizes new media with the old (specifically, cinematic), demonstrating dramatically that the new didn’t appear magically in a vacuum ca. 1990, and I found Manovich’s historical background (“How Media Became New”) especially fascinating.
I have to admit that I approached the book skeptical that our culture’s computerization would change us in any appreciable way other than speeding up the cycle of cultural trends, but I find the author’s approach balanced and credible, and while I’m still skeptical, I’m willing and able to keep an open mind while we see where all this is headed. Are we witnessing a redefining of what it means to be human? Does our capacity to sample and quantify quotidian behaviors obviate humans who excel at quotidian behaviors? How far do we want to see artificial intelligence represent human experience? To what extent can neural biochemical reactions be sampled and quantified? Are we prepared to see the erstwhile abortions through?
I join you in skepticism regarding whether human kind will change fundamentally because of digitization. While the cultures of the world have varied and changed drastically over time, I think, in the end, that we'd still recognize the fundamental "human-ness" in previous generations and future generations, just as much as we recognize it in our current generation.
ReplyDeleteI do think that Manovich is right about the dramatic cultural shift that computerization has caused, however. While growing up with computers and in the midst of computer-transforming culter hasn't made me any less human or any less biological than other generations, it has influenced my habits, my language, my concepts of reality, how I understand myself, and how I expect the world around me to function. In that sense, I think computerization and digital media has sleepily infiltrated our culture. And now that it's there, it extends its reach and defines the edges of the generations born into it.
I enjoyed reading your analysis of Manovich's text. Your summaries helped me cement my own understanding of his points.