1s and 0s: On Binaries and Experience within BioWare’s MASS EFFECT

In Noah Wardrip-Fruin’s Expressive Processing (2009), he spends some time exploring the dialogue- and quest- trees that constitute much of the gameplay of BioWare’s Knights of the Old Republic (2004). One of the things Wardrip-Fruin wants to interrogate about the game is how we might learn from failures in its coding. KotOR is a game that feels like it is part of a fully-formed universe, not just in the spatial or astronomic sense, but also in how it constructs a series of social interactions and quests within the diegesis of the game. These interactions often feel contingent and actionable enough to approach some of the conditions of social life its players encounter out in the “real world,” beyond its textual bounds.

In addition to this, the game is addicting; Wardrip-Fruin, quoting William Huber, refers to the text as a “statistical bildungsroman” because of the particulars within the gameplay that encourage the player to continue playing, particularly how one earns experience points (or “XP”) Like many RPGs, “as characters accumulate experience they increase in ‘level’ and become more capable in the game world,” driving the player to play for “forty, eighty, or more hours,” creating an experience “more akin to a thick German novel of personal development than, for instance, a film (or even a season of television)” (Wardrip-Fruin 62). Beyond this description, KoTOR is a game about choice. As he acknowledges, what this more-basic description of the rules of the game might elide is how freely these threads of development unfurl; one can often choose the order of quests, or what order to visit given planets, or whether to adhere to the dark or light side of the force, in a way that feels somewhat freed from the linearity of some RPGs of yore.

When Wardrip-Fruin moves beyond the basic outline of the gameplay, into the game’s failures, he begins to illustrate that the underlying code of the game, which the player can often feel but not totally perceive, as it proceeds in computational, linear fashion through if/or loops. As it turns out, crafting a game with such a freedom inevitably produces nonsensical leaps within its narrative and diegetic spaces; it is impossible to write a long and complex video game with a nonlinear quest-tree logic without inevitably gumming up its novelistic or televisual qualities along the way.

For his example on the weird narrativity of KotOR, Wardrip-Fruin narrates a play-through of the game in which he completes a quest on Dantooine, proceeding through a dialogue tree with a woman whose lover has been captured by her father, agreeing to use her key to free him, then talking both families’ fathers out of an ambush and battle, through some dialogue-tree finesse. He then takes his character to the male lover’s compound, where the male lover’s father requests, on two separate visits, that the player rescue his son, the one we have already seen being taken back to the compound. Wardrip-Fruin then returns to the female lover’s estate, seeking to report on another, unrelated, quest, a death in that family, only to find that the estate has emptied out, with no unplayable characters with which to speak (63-65). Because of the computational path of the quest tree, one which can be felt but not entirely read or understood, not much makes narrative sense, although it is clear that there was some expectation, among the coders of the game, that the player would visit the male lover’s compound first. Without any intention to do so, Wardrip-Fruin shut down a tree of possibilities within the game, with no recourse to correct himself but load an old save file or play through again, with the coders’ ordering in mind. He has revealed the basic, binary structure of computing present in a game that wants to pretend such formulations do not exist; he can either do things his way, or more-linearly as the programmers intended, though to totally pursue his own path would be to close off the possibility of extra XP or a feeling of completion within the nondiegetic, external rules that a “serious gamer” might try to pursue in order to elicit a feeling of completion out of the text.

I already saved him, bro!

I already saved him, bro!

One of the things I find so interesting about Wardrip-Fruin’s narration of failure is that the if/or logic of the loop is also a logic built into the essential, intended, and basic play within KotOR. This is to say that, regardless of the invisibility of the quest- and dialogue-tree outcomes, an invisibility one might sense if she or he plays without external help, the game still unfurls within a similar if/or logic. Binarism constitutes the basic structure of KoTOR, as games within the Star Wars universe must adhere to gameplay that follows either the dark or light sides, and the future of this universe depends upon its player making a choice between these two sides. Regardless of whether a player encounters the type of glitch that Wardrip-Fruin did in his playthrough of KoTOR, she or he will explicitly understand that, by the end of the game, things will have shifted in one of these two directions, and that the game’s ending will depend entirely on the “good” or “bad” decisions made within its various dialogue-trees. The failure that Wardrip-Fruin experiences actually has much to say about the most-essential narrative structure that can be seen and felt within the game’s diegesis.

Building on Wardrip-Fruin’s work on quest- and dialogue-trees within KoTOR, I was interested in interrogating whether Mass Effect, BioWare’s next “nonlinear” franchise, might contain corrections to the problem of broken quest-trees. I was also interested in whether Mass Effect broke from KoTOR’s binarism, where the gameplay outcomes within individual quests almost always follow one-or-the-other, if/or logic. I learned that Mass Effect, while often having the appearance of nonlinear, free choice, is rather much like its predecessor(s) in the KoTOR franchise. One can feel, see, and predict the “good” or “bad” choices they are making, to the point that certain skills you can earn within the game (“Charm” and “Vagabond,” respectively) will alert you to a moment where you will be forced to make some kind of final, binary choice.

The "good," charm-determined choice in blue, with the "bad" choice underneath

A “good,” charm-determined choice in blue, with the “bad” choice underneath.

At the same time, I find that one of the most-interesting things about this relatively unchanged gameplay is how often the narrative and quests seem to gesture towards it. The narrative of Mass Effect feels obsessed with humanist binarisms, whether between human and alien or between human and machine. This manifests itself in interesting ways within dialogue-trees. Often, if one has neither enough Charm or Vagabond points, the “bad” choice is the humanist one, while the “good” promotes interspecies peace. This plays out in funny ways throughout the game. For example, the central quest of the game eventually reveals that a “species” of machines, the Reapers, exist only to destroy all organic life in the galaxy, but that they must do so through a kind of cyborg binarism:

Saren 1 Saren 2

In the longer, “more-academic” version of this project, I attempt to interrogate not only how Mass Effect fails in similar or different fashion from KotOR, but also how it acknowledges this structure of potential failure through a cyborg narrative that seeks to make its player think seriously about the problems of binary logics or thinking. I want to examine and write through the game’s failures while also explaining how it acknowledges these failures, in a mode of narrative and gameplay-centered self-reference that might force the player to realize just how-guided their path through the game might be; while there are so many choices to be made within its narrative(s), Mass Effect also plays itself, in some ways, creating a cyborg gameplay structure where organic and cybernetic agencies must cooperate to create a meaningful narrative.

Looking back: computation and image

Hey class,

I chose to blog about computation and image. This was one of my favorite workshops of the semester and I wish we’d had more time to discuss it.

Reviewing the Processing overview that we were assigned before the workshop, I’m struck by the creators’ statement that their program is designed to “[promote] software literacy, particularly within the arts, and visual literacy within technology.” Thinking back to our early discussions in week 2, it’s worth pondering what implications computational literacy might have for the arts. A key point in Annette’s article was that the spread of literacy allowed certain types of (for lack of a better word) utterances that didn’t exist before, like contracts and signatures. The same can be said for programming in the arts. Interestingly, Aaron mentioned that he approach a bunch of different people for technical aid and, IIRC, had assistants help him program the spotlights. Strictly speaking, he might not be considered fully computationally literate, and this adds a layer of complication to questions of authorship and artistic integrity. (Of course, these questions aren’t unique to programming—in most conceptual art, the artist herself is still considered the author regardless of whether she physically put together the installation herself.) It’s conceivable that people who are totally computationally illiterate (e.g., me) are circumscribed from participating in certain genres of conceptual art that rely on computation.

What are the consequences, then, of “promoting software literacy” in fields that it hasn’t yet penetrated? It seems that when visual artists integrate computational media into their toolboxes, it pushes the field in an even more conceptual direction than it has already been heading. Of course, there’s also the rather vulgar argument that software literacy gives artists a marketable skill and serves as a bridge between the arts and other disciplines. I hate this line of thinking, but there is something to be said for the idea of visual artists working in a medium that is accessible to people who might not normally engage much with the arts. After all, painting is a type of technical literacy that most lay people don’t get to participate in, because of the skill required and the expense of materials. If, in 20 years, everyone has a basic level of programming literacy, then it would be arguable that programming-based art is more democratic than art made with traditional media.

Data Cleaning

Thinking about last week’s class, it seemed like it might be useful to share this resource on data preparation. We read excerpts from Trina Chiasson and Dyanna Gregory’s Data + Design in Dr. Langmead’s Digital Humanities seminar this term, and I found the chapters on “Getting Data Ready” to be both helpful and insightful. What do we do to data before we present it? Considering our conversation about the subjectivity of databases last week, I thought this might be worth a glance!

Mountainhome Endoktomus, “Atticshove”

Hey everybody,

I didn’t post about Dwarf Fortress earlier in the semester, but I’ve talked a couple times in class about my progress in the game. In what is surely a move to avoid working on my final project (and to make up for not posting earlier), I figured I’d show everybody a little bit of what I was able to accomplish. So…welcome to Mountainhome Endoktomus, better known as Atticshove!

First off, here’s a view of my fortress from above ground, using StoneSense to render it in three dimensions:


And yes, that’s a lot of vomit everywhere. But, it gives a nice view of the tower (11 z-levels tall), walls, and fortifications that I’ve built, as well as the road leading into my trading caravan entrance. That tower includes barracks and training grounds for my archers, who can then move along the parapets to shoot down at any attackers. Here’s a more conventional shot of the ground floor:


So, still lots of vomit. The Well (more on that later) and Statue Garden are all forged out of silver by my Legendary Metalsmith, so that’s pretty much what keeps everybody happy. As that “Idlers: 74” up top indicates, I’ve built up a pretty sizable population:


I’m definitely not going to run out of money or food any time soon. And out of those 198 dwarves, I have 13 nobles, though some positions overlap:


At a certain point in the game, you can meet the requirements to become the capital of your civilization, which brings with it your King. My biggest struggle lately has been trying to build quarters that are royal enough for him and his consort…


This level also shows my reservoir, which my Well draws from. I dug a channel to a river on the other side of the map so that I could have a source of water in my fortress while under siege. This was particularly important since I was digging in an area without any mud to farm in, so I needed to build an irrigation system to partially flood the ground to make mud. The next level down is just workshops:


I was planning at one point to expand my reservoir, but that project’s pretty well on hold. You can also see the continued drawbridge pit, which at some point I’ll hopefully get some poor sap stuck in. It bottoms out one more level down:


Lots of traps in case anybody drops down into the pit, plus my kitchen, butcher/fish cleaner, and dining hall. Next up, my metal industry:


And finally, the burial sites and mines:


The next 11 levels down from this look pretty much the same: lots of mining, just without the coffins everywhere. Eventually I’ll have to build royal tombs for my King and Baroness Consort, but right now I’m pretty fed up with Urist McSpoiledpants and company. I haven’t made it down to the caverns yet, or found any magma, though that’s mostly by design (I don’t want to have too much “fun” and risk what I’ve built).

So yeah, that’s pretty much the tour! As far as I’m concerned, I still haven’t even begun to scratch the surface of the game, and I definitely have yet to become “fluent in Dwarf Fortress.” That being said, my civilization has yet to die out even once, and the reservoir and above ground ramparts are fairly dwarvish megaprojects. The way things are set up, I can basically close the gates and repel any goblin siege with minimal loss of life (I’ve weathered 5 or 6 of them so far), but it’s often more enjoyable to send the military out and kill things. Only problem is that the resulting bodies tend to horrify my dwarfs, who are already pretty struck with sunsickness from never going outside, which is why I have a bit of a vomit problem (understatement). It’s probably also why one of my military squads has valiantly named themselves the “Gates of Fainting”…


It was something like 35-40 hours worth of gameplay to get this point, which is pretty insane. I really enjoyed myself, but I’m happy to say I haven’t played in a few weeks, so hopefully I’m over my Dwarf Fortress addiction. If anybody wants to see more, or has any questions about anything in the screenshots, just let me know!

Oh, and one last thing:


The Weretortoise lady consort Buslá Demtamun has come! A large tortoise twisted into humanoid form. It is crazed for blood and flesh. Its eyes glow mahogany. Its sandy taupe scales are blocky and overlapping. Now you will know why you fear the night!

This game gets super weird sometimes…

Closure (n): The act of closing or shutting

In the other course I’m taking this term– Paul Kameen’s core course in rhetoric which is focused on referential language– we’re currently reading through some essays and works from poets in the 1970s and 80s, namely from the L=A=N=G=U=A=G=E movement. It was/is a movement that foregrounds play, collage (material collage, literal cutting and pasting, as well as later digitized versions and other means of appropriating texts from other sources), strangeness, and a deliberate disruption and intervention into the typical modes of close reading. Above all, the poets from this movement were invested in troubling the relationship between reader and writer, in calling to attention the reader as an equal if not majority maker of a text. Such works resist “a reading”.  In Lyn Hejinian’s exceptional essay “The Rejection of Closure,” she writes:

It is not hard to discover devices–structural devices–that may serve to ‘open’ a poetic text, depending on other elements in the work and by all means on the intention of the writer… the ‘open text,’ by definition, is open to the world and particularly to the reader. It invites participation, rejects the authority of the writer over the reader and thus, by analogy, the authority implicit in other (social, economic, cultural) hierarchies. It speaks for writing that is generative rather than directive. The write relinquishes total control and challenges authority as a principle and control as a motive. The ‘open text’ often emphasizes or foregrounds process, either the process of the original composition or of the subsequent compositions by readers, and thus resists the cultural tendencies that seek to identify and fix material, turn it into a product; that is, it resists reduction (88).

Reading Hejinian and then also Ramsay and Underwood and Sellers at the same time has me wondering, if algorithmic criticism serves to open up new critical readings across literary texts, what is the role of the “reader” of its outputs? On the one hand, the reader is maker. The reader/coder designs (or appropriates) an algorithm with which to sort through a mass of textual data, and determines what that algorithm is meant to do. It re-reads the data to assign and sort through tokens, making sure the human sense-making system of word combinations are represented by the data (e.g. “high school” becomes a bunch of “high” students at “school” if we’re not careful to assemble the singular term). The algorithm designer reads the world as much as she  reads the data, but the design of the thing makes strange before it makes sense. The reader still has to make “value” of the repetitions. To ask what it means.

This version of reading strikes me as quite similar to the request Hejinian is putting on the reader to bring themselves to the text. Her process might be idiosyncratic and not automated in the same sense that a machine algorithm is, but her texts could read like a computer-generated recombinatory text. Hers is not a poetic that is based off of “natural language”. Take this moment from My Life:

The continent is greater than the continent. A river nets the peninsula. The garden rooster goes through the goldenrod. I watched a robin worming its way on the ridge, time on the uneven light ledge. There as in that’s their truck there. Where it rested in the weather where it rusted. As one would say, my friends, meaning no possession, and don’t harm my trees.

Hejinian verbs the noun “nets,” and describes the robin’s search for food as “worming,” and gives “time” a physical location (read, perhaps, the passing of the light by the shadow of the ledge tells us the time… but that is too many words and perhaps not what is “meant”). The play with “there” and “their” in sonic spheres. The weather as something that one can be “in” apart from what happens to us. This is not natural language in the same sense that other texts are, even the poetic works of the time period Underwood and Sellers are looking at. If we determined the frequency of light to be quite common it is still “unreadable” as a figure or trope, as only context determines these things and even then the context doesn’t save you with the Hejinian poem. The language would probably flag as not latinate and more common. There’s plenty of idiom if you could have the code look for such things, but that can in no way signal a desire for “universal experience”.

In short, while perhaps in the window that Underwood and Sellers are analyzing some kinds of “closure” is possible, but feels to me to be too limited in terms of their conclusions. In the sense of most of these algorithmic criticism machines, they seem to me to be mechanisms for opening up the text to the level that Hejinian hopes her works have from the outset, but then the critic’s aim is still to close them down again. Perhaps Hejinian would say that these are new technologies at all, and that it’s actually a responsibility of the writer (or algorithm designer and executer) to leave a text open to such participation from the reader. Sense-making is not unlocked by the texts themselves but by the interaction between a text or texts and its reader. This is not a new concept. Of course we all participate in texts as readers, but as with so much we’re thinking about in this class, it’s a matter of scale. The Hejinian poem demands much more of us. These algorithmic critical programs demand much more of us. How, then, do we amplify the openness and work with the results of these programs without succumbing to reading the output through critical modes that “seek to identify and fix material, turn it into a product”?

Designing Criticism


As I read the piece by Ted Underwood and Jordan Sellers, an article that our composition reading group read slowly began entering my mind (very slowly…more like as I skimmed over my notes from reading…that is more accurate).It was an article by James Purdy called “What can Design Thinking Offer Writing Studies?” that tried to show how a concept called “design thinking” has historically infiltrated composition and rhetoric. Many of the moves made throughout the Underwood and Sellers piece reminded me of the kinds of qualities that Purdy claims that design thinking has: thinking of the future more than past problems; focusing on combination and connection more than critique; generating many diverse solutions (emphasis on quantity before quality) (Purdy 620 and 626).

This is not a perfect analogy to lay onto DH scholarship (e.g., there’s not quite a series of “users” that Underwood and Sellers are trying to tailor their product for in the same way that designers do…in some ways there arguably are, but I think it might be some kind of hybridity that lays between critique and making that makes this analogy imperfect [making, at least, in the sense of designing] ), but I think, broadly speaking, the emphasis on the future and the emphasis on testing things out and living in method more than argument aligns nicely with the kind of work that designers perform.

Much like a hypothesis, Underwood and Sellers begin by thinking in terms of possibility and the future:


This is the problem, but the problem leaves itself open for many solutions. Underwood and Sellers are only leaving it open for something “interesting” by examining “changing characteristics.” As we see throughout the rest of the piece, there are many ways to slice up these changing characteristics. There are definitely considerations of quality throughout this slicing, but it is left very open-ended and we are left with a surplus—an emphasis on quantity—of methods of using and interpretations of data throughout the piece.

After the first chart, and the subsequent teasing out of the surge in use of words that entered the lexicon pre-1150 in literary genres, they write the below with a new chart:


The picture becomes more nuanced with poetry rising, prose fiction rising (though, less so than poetry), and nonfiction declining. Underwood and Sellers further complicate this picture by slicing the data along more specific genres. They describe the issue with drama and then start to discuss the problem of viewing too absolute and certain a distinction in change of language between literary texts and nonfiction texts because of the heterogeneity of genres. Going away from a previous argument (or “solution”), this leads to looking at a new dataset in a new way here:


After debriefing this chart, and how it shows the pitfalls of wondering too much about the similarities and dissimilarities between fiction and nonfiction over time, Underwood and Sellers build a new question (more…quantity rather than quality…exploring possibilities): “What was concretely entailed in the formation of a specialized literary language?”

After surveying some other works, historical and critical, about what made poetic diction become specialized, Underwood and Sellers’ next move is to answer another distant reading done by Heuser and Le-Khac that concluded that this shift was due to a decline in words associated with abstract values and an increase in concrete words. Rather than dismiss the study outright, they use this work to suggest that this work “overlaps in great part with” their own claims. Because of this overlapping, Underwood and Sellers decide to do more digging, going beyond the aggregate of the uptick of pre-1150 English words in 19th century literature and look to see individual words and their correlation to the variations in the diction ratio. First looking at the positive correlations followed by the negative correlations, some thematics are drawn from both groups (more concrete words, and some more abstract-ish experience words; fewer words connoting social relationships). Nothing is taken as hard proof here, and Underwood and Sellers continue to undercut their claims, prompting others to possibly investigate this data more. No demystifying here, just trying to encourage looking at the data in increasingly new ways to try to find things unseen before.

The (seemingly honest and not rhetorical) gesture toward the continuance of research is especially apparent in the last paragraph of the main essay and in the “Supporting Data and Code” section. They write that “this is a collective enterprise” and go on to acknowledge friends and critics as crucial to its making—it’s noteworthy that this is not in a separate section called “acknowledgements” but is in the main body of the text. The closing sections is filled with hyperlinks and even advice about how to filter collections of poetry to make sure the prose sections are not captured into the data. This is almost a gesture of: here’s how we did it, you try it, too. Or, make it even better. Constant invention, constant brainstorming, constant thought for the future, combination, connection. Very design-like.

Purdy, in the article on design thinking that I cited earlier, concludes his piece by writing that design thinking situates the goals of writing studies to “describe, explain, and enact the gamut of writing practices and products rather than to judge (or to dismiss) them” (632). With Underwood and Sellers, and it might be safe to say about the majority of DH scholarship, there’s a larger focus on descriptive work that is continuous and collaborative in the kind of spirit of design thinking that Purdy puts forth. There’s less critique and more testing; there’s more quantity and experiments than a Sisyphean task of finding the “best”, in kind of an Arnoldian way. Underwood and Sellers open their article by exploring what literary criticism once was: a definitive and descriptive practice. It might interesting to go back and read the New Critics and the Russian Formalists and to see if they might be designers in their own right, which might be more in degree than kind.

On Loop Aesthetics

One of the claims Hayles makes throughout her first two chapters has to do with the dialectic between the analog and the digital, where she takes the middle ground that neither category, at this point, would be particularly useful without thinking through the other. In addition to this, Hayles is interested in what we might call the organicity of language, one of the main categories that structural linguists, after Chomsky, use to cleave apart a difference between natural and “artificial,” or computational, language. The Chomskyan argument goes something like this: we acquire a thing we can call natural language, rather than learn it, and the ability to acquire language is universal among all human subjectivities. The particularities of one’s first learned language, in this system, are arbitrary, involving a kind of flipping-on of switches within an underlying universal grammar during one’s critical period (before the age of 3, certainly). Results that might be unthinkable within the grammatical rules of one’s first language, or L1, are totally possible within other languages. We might say, for example, that Hayles’s assumption about the material impossibility of a word containing 100+ syllables is a mistaken one grounded within her L1, if her L1 is English (43); while the morphological and syllabic structure of English might not allow for a 100+ syllable word, an agglutinating language like Turkish would certainly allow for it, regardless of its seeming material clunkiness in English.

Is it yet clear how overseriously I took my early undergraduate coursework in linguistics? One of the things that now bothers me about this Chomskyan, evolutionary model has to do with its overreliance on generational transmission that seems to fail to account for intragenerational changes in culture and use — any advancement related to changes in the distribution of human universals, like changes in harmonic or rhythmic sensibility in music (which is thought of just as language in this kind of structural/neurological model) would have to take place over several generations–one would not be able to see it, clearly, within their lifetime. When we look at the way digital technology interacts productively with analog convention, I simply cannot accept that this is the case.

I’m interested in the way looping technology, over the last twenty years or so, has transformed the landscape of what musicianship might mean and what musicians might be capable of doing. My interest in this proceeds from my own embeddedness within a guitarist (and guitar pedal) culture that has, to my mind, experienced a sea-change over the last couple decades.

By the late-90s and early 2000s, the amassing of an unreasonable number of unreasonably expensive guitar pedals had become a cliché of high-minded alt- and indie-rock. This leads to images like this one, of the pedalboard Kevin Shields used for the My Bloody Valentine reunion tour in the late-aughts:

shields board

Unfortunately, much of the discourse surrounding this kind of textural obsession/ridiculousness RE: guitar playing is rather poisonous (if you want that exact sound, you need that pedal).

At the same time, a single feature on a single pedal, the Line 6 DL4, has substantively changed the way musical composition occurs in such highfalutin musical settings. It looks like this, goes for ~$150 used, and most touring guitarists seem to have one, or a pedal like it:

The loop sampler function, which becomes engaged when the user switches the left-most knob to the 6 o’clock position, is the function embedded within this pedal that most interests me. It turns the pedal into a live sampler that transforms its input(s) into a recorded digital output meant to be layered-over by the performer — in essence, the top-down studio view of music as modular and digital, in Hayles’s sense, which looks like this:

maxresdefaultcan now be controlled by one’s foot, in real time; I would argue there is a sense of democratization of this kind of top-down understanding of musical composition implicit to the use of the DL-4. Here is an example of the sampling function of the pedal in live use:

Here we see the live-loop logic, co-opted from hip hop and DJ culture away from the the human body by digital studio convention, brought back into more-dynamic relation with such a body (though I would hesitate to remove the particularities of racial history from this technical history).

I would argue that guitarist culture, or musical culture generally, has moved away from a textural logic, present in the infinite-pedal dream of 90s alt-rock, to a logic of meter and rhythm through the sampling of loops. I would admit this has created a sometimes silly state of affairs, where for example the late-aughts Animal Collective were almost unrecognizable from earlier “folk”-based iterations, having the appearance of just pressing buttons and turning knobs over and over (for better or worse):

At the same time, we can also see how this kind of digital, loop-based thinking might provide altogether new possibilities for musical composition. I remember being floored by the sense of melodic and rhythmic simultaneity created by Thom Yorke’s rearrangement of his song, “The Clock,” on a single acoustic guitar, when the original had had a very rhythmic, loopy bleep-bloop feel to it:

(here is the original for comparison:


I believe that the question of productive interaction between digital and analog processes can be seen in recent developments in music technology, and wonder what will come next, though it seems clear that any sense of analog virtuosity (be it guitar shredding or pedal-collecting) has given way to much more-streamlined interactions between the human and the digital.

Mr. Polemic or: Techno-Comprehension and Limited Retention

Please approach my response to this weeks reading with a grain of salt (I’m pseudo-serious, but I know I’m wrong). I start this post with multiple questions I have at the forefront (if you rather respond to one of these, by all means do so) before diving in:

First, What is code, In Katherine Hayles’ chapters, I’m left with a very vague and nebulous feeling that the phenomena of “code” signifies an empty signified, making this abstraction too theoretically detached from an independent artifact of analysis.

Second, Is the academic move to treat language as a monolithic subject divorced from its current programming utilization?

Third, how does technological optimism frame the discussion of computation?

Fourth, Literacy and Code imply a looking-in/regulatory functions that feels very violating of communities that don’t want to be revealed.

These gestures were all focal points that I originally wished to write about, and think that there is much to be discussed, albeit this post takes a different direction.

Computation, Hayles identifies, “connotes far more than the digital computer, which is only one of many platforms on which computational operations can run” (p. 17),  unpacking hardware onto social systems (via langue) and complex modes of interaction and being. In chapter two, Hayles attempts to critically delineate the limits/operations of “speech, writing, and code” (p. 39). She argues that, “we cannot afford to ignore code or allow it to remain the exclusive concern of computer programmers and engineers. Strategies can emerge from a deep understanding of code that can be used to resist and subvert hegemonic control by megacorporations (p. 61)”.  My concern is that theorizing a concept of “code” literacy need not (re)articulate itself from speech and writing, but should be embedded within pragmatic interpretations of language proper.


Hayles argues, “Speech, writing, and code: the three major systems for creating signification interact with each other in millions of encounters every day” (p. 38).  When treating “code” as an external system (la langue), it becomes a privileged technical system exterior to and insulated from speaking and writing. When the technique of coding becomes it’s own techne it removes itself from the basic supposition that coding is writing. She argues, “Now that the information age is well advanced, we urgently need nuanced analyses of the overlaps and discontinuities of code with the legacy systems of speech and writing, so that we can understand how the processes of signification change when speech and writing are coded into binary digits” (p. 38). In a logically positivist manner, she situates code as the next phase of learned knowledge, understanding, and development, because, “Computers are no longer merely tools (if they ever were) but are complex systems that increasingly produce the conditions, ideologies, assumptions, and practices that help to constitute what we call reality” (p. 60).  Tension emerges when treating the computer as both simplistic tool and complex machine (which is latent in this last quotation itself), pinning down the mechanistic process/capabilities in it’s fluidity need not serve analysis for the artifice proper. In less congested terms, selectively deciding how to theorize code/computation/digital in it’s relationship to speech/word/written functions as a self serving mode of interpretation further externalizing computational literacy, instead it creating an additional layer of literacy making it harder to teach “non-programmers” its utilization.


Hayles argues that, “Code is not the enemy, any more than it is the savior, Rather code is increasingly positioned as language’s pervasive partner. Implicit in the juxtaposition in the intermediation of human thought and machine intelligence, with all the dangers, possibilities, liberations, and complexities this implies” (p. 61). What is problematic in this “parternship metaphor” is that code is part of language and a non-external device. Computer code is not a partner to language, but computer code is itself language. If the goal is to create a public that is literate and capable of understanding “computer code” (my criticism is more so of the concept of code rather then the computer itself), we need a public that is literate (with code). If knowledge of the digital becomes apart of learning language itself, then language inherently becomes what it was always/already, code.


Digital language need articulate itself through discourse at earlier stages of development, both to show its utility and to deny the magical effect it has, once it becomes insular  to language (Eliza effect was the title I believe the other author called it – need fact checked). For instance, at the Elementary educational level, if computational language was taught (we can easily scrap cursive, etc…) computer “code” would not be a foreign entity but part of our basic system of understanding and literacy. As Hayles’ notes, computation and code is a “metaphor pervasive in culture” (p.20), the ultimate task is to change the metaphor into something more attainable at the literacy stage.

Arriving at more questions

I was pleased to work on a topic modeling project in Thursday’s workshop, as I have been learning about and practicing topic modeling for Alison Langmead’s digital humanities seminar this semester. In my own project, I am using the command line interface tool Mallet with a poetry corpus, experimenting with the tool’s ability to model figurative language. Any suspicion that the quantitative methods of topic modeling replace more humanist hermeneutics has been more or less erased as I have grappled with the interpretative questions necessary in “training” the model. Throughout the process I have also returned again and again to the question that is often asked about algorithmic textual analysis: is this generating anything meaningful? In my own project, I truly can’t say yet. In Thursday’s workshop, the example provided us with a list of topics that demonstrate what I think may be a more useful application of topic modeling.

I have been inspired by Lisa Rhody’s assertion that “topic modeling poetry works, in part, because of its failures.” (She also provides a very nice produce-based analogy to explain how topic modeling works; I find food to be a helpful point of entry for any subject.) Rhody’s explanation of her use of topic modeling in studying ekphrastic poetry, for me, echoes Ramsay’s statement that “in literary criticism, as in the humanities more generally the goal has always been to arrive at the question.” The models provide alternate means of exploration, not answers. Between my own project and our workshop, I have been able to imagine some scenarios in areas more closely related to my actual research in which topic modeling (or potentially other data mining methods) could provide a useful way to begin asking questions about a large body of work. But again, I see this merely as a way to get started. When it comes to the digital humanities, one of my concerns is whether or not there is too much of a learning curve or technological barrier to tools that simply allow us to prepare data for interpretation. It does seem that this work requires a dedication to computational methods themselves, beyond dedication to the interpretation of the content, which may be a (very reasonable) barrier for many researchers.