Civilization, Ideology, and Informatic Control

One of the elements I find most interesting is the distinction between ideological critique and the algorithm, which Galloway, in particular, describes, but also seems to inform Friedman.

When describing playing Civilization, Galloway notes the “soft racism” and questionable God view that informs the game, like the problematic “attributes” given to civilizations–like how the Aztecs aren’t “industrial–or the absence and simplification of many civilizations. To Civilization‘s defense, subsequent additions have addressed some of these issues, like the inclusion of more civilizations, like Polynesia, and dropping essentialist attributes for more civilization-specific qualities.  But, things like the progress narrative, the valuing of military dominance, the potential simplification of ethnicities, and the role of commerce and territory still pose potential problems, ripe for ideological critiques.

Galloway moves from this into what he calls the “third level” of critique, “informatic critique,” which he describes as a “formal critique rooted in the core principles of informatics that serve as the foundation of the gaming format” (99). He asks, “whether it [Civilization] embodies the logic of informatic control itself” (101). Though I still had some trouble ultimately figuring out what Galloway meant by this, I think it reflects the way a phenomenon gets enacted by a computational system.

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ENG 730: The Game and Immersive Narrative

Watching The Game, I kept thinking of Kafka. In many of his stories, Kafka presents this looming network that always recedes as the protagonist gets closer to solving it. I think A Messenger from the Emperor puts it best:

“he is still forcing his way through the chambers of the innermost palace; never will he overcome them; and were he to succeed at this, nothing would be gained: he would have to fight his way down the steps; and were he to succeed at this, nothing would be gained: he would have to cross the courtyard and, after the courtyard, the second enclosing outer palace, and again stairways and courtyards, and again a palace, and so on through thousands of years. . .

In The Game, Nicholas, much like many of Kafka’s characters, must navigate the ever-withdrawing, seemingly omnipotent CRS. Things escalate as he goes forward, almost to an absurd degree. And at the end, instead of closure of catharsis, we get this bizarre party. As John notes, no one seems to recognize the emotional turmoil that Nicholas endured, revisiting the suicide of his father, shooting and thinking he killed his brother, and attempting suicide himself, only to stumble into a room of friends and strangers who only moments ago–he thought–were trying to kill him.

I guess my frustration stemmed from the notion of immersion and boarders that Murray discusses. As Murray writes, “Part of the early work in any medium is the exploration of border between the representational world and the actual world” (103). When immersed, much like the Holodeck example from the beginning of the book, one is caught up in a procedural, participatory medium, as Murray describes. But as she also notes, this participation is “a visit,” and we must often “actively create belief” (110). There is a border, in other words, between the illusion and the larger world in which that illusion sits.  This larger world may have its own hyperreal characteristics, but it is nonetheless distinct–or seems to be.

But the blurring of that border is what seems to make The Game and The Grasshopper examples so haunting. As John notes, Nicholas ends up no longer really playing in a way, as he thinks that he is actively fighting a real entity. For example, toward the end, the ontology of the gun is ambiguous: in the actual world, it’s a prop; in the representational world, it’s a gun. But for Nicholas, the representational world has become the actual world. The game, and all of its trappings, has become his new reality, including the gun. And, as many others have noted, the “voluntary” element of Nicholas’ participation feels murky, making this “game” all the more problematic.

Connecting it back to Kafka, I think the reason why The Trial is so haunting is that the legal system has left its boundaries. To draw from Huizinga, the court has flooded outside its magic circle and has become an existential way of life. K is guilty without his consent, and forced to solve the maze of “state sanctioned violence” as Murray calls it (131), as himself, not a player version of himself.

In a similar note, The Game shows this haunting Grasshopper-like dystopia where the representational aspect of play has permeated and supplanted actual life. But, the game ends, and this is the strangest part. As Murray points out, digital mediums have a more ambiguous ending, often created by their interactive aspect. They often end through exhaustion and not a linear progression. The same could be said for the movie.

The doctor/actor jokes at the end, for example, that if Nicholas didn’t jump, he’d have to throw him.  This raises the question on how prescriptive the game was. Jordan points out that the game maybe was not that interactive, and indeed, it’s hard to see how the game wasn’t pulling all the strings, giving CRS an almost deterministic quality that feels godlike, all driving toward this “ending.” Were there alternative endings? What if, for example, Nicholas didn’t drink the tea? What if he didn’t get the gun from his house? What other rhizomes could he follow, and would those rhizomes still lead to that party in that way?

Much like K’s demise in The Trial, the ending in The Game feels inevitable, and I wonder–since they lied to him before, including about him not being picked to enter the game in the first place–whether the game is really over. Once you turn life into a game, it doesn’t feel easy to get out, and maybe Nick’s blithe acceptance at the end is a sort of absurdist, nihilistic acceptance of the Grasshopper’s wisdom. Worst birthday gift ever.

CCR 633: The Cherokee Syllabary and Writing Technologies

If I could summarize my main takeaway from Ellen Cushman’s Cherokee Syllabary, it would be the way it showcases–through a particular case study–how people, technology, language, and writing interact with one another and the values or worldviews of  a given context. Tracing the formation of the writing  system as a written syllabary, to typefaces, to unicode and other digital materialities, the linguistic history also aligns with nation forming through newspapers and other technological, rhetorical interventions.

Similar to other readings, Cushman’s Cherokee Syllabary shows how language doesn’t inhabit a vacuum. Like Rickert’s contention, Sequoyan and the Cherokee language feels somewhat ambient, fitting into a broader context of identity and material. As Cushman writes, describing digital teaching materials, “Students hear, see, and experience the Cherokee language and writing system as complimentary and mutually sustaining. The also learn something of the Cherokee worldview implicit in each word and phrase written in the language” (215).

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IST 700: Locating and Drawing the Boundaries of Research

A few things struck me from the reading, in particular the messy boundaries (and lack thereof) between online and offline and the difficulty of mapping and bounding digital projects. These pose significant implications for conducting online research. For now, I was mainly thinking about how some of these readings are impacting how I look at my own research project.

A map of the Internet by Wired founding editor Kevin Kelly, image via Brain Pickings.
A map of the Internet by Wired founding editor Kevin Kelly, image via Brain Pickings.

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(Post)Demographics and Trends

Until this semester, I had not encountered the term “postdemographic.” First hearing it, I assumed it referenced the more individuated way that data collection could take place, putting less emphasis on the demographic that one belonged to and more emphasis on individuals themselves and what they did. In a sense, this understadning approaches the term, but Rogers completes it: “Postdemographics could be thought of as the study of the data of social networking platforms, and in particular, how profiling is or may be performed” (153).

Rogers also stresses the shift from the “biopolitical” to the “info-political,” explaining a shift from embodied attributes, like age and race, to the information that these bodies generate and consume. This explains a shift in focus on the data. Though the sites of data collection are not necessarily limited to “social networking platforms,” these sites tend to abound and automatically collect the sorts of data that postdemographics focuses on: taste, pop culture influences, political leanings, groups, associations, and the way that these may line up with people that you know or interact with.

These are the curated ads and Amazon book recomendations. The “you-might-also-likes” and “people-who-liked-this-also-likeds.” In my case, an odd mix of books on wine, Zen philosophy, critical theory, composition theory, and research methods.

Rogers also notes that many of these spaces, particularly in platforms like Facebook,  the space itself reaches out for us to detail our preferences and network our contacts and interests through pre-set categories like books and movies that we like or more open-ended notes. It wants our data, takes that data, and constructs our experience accordingly.

That, very roughly, introduces postdemographics.

Contrasting the postdemographic with demographic, I see a complication: how do demographics impact postdemographics? As the Pew research reports note, demographic issues, like age and gender, connect with who uses a platform. For example, Pinterist users tend to be women: 42% of women online users, compared with 12% of men. Also, wealth and access still play a role in usage, which are again traditional demographic categories.

These potential considerations have both ethical and practical implications. On the more ethical side, I think it forces us to look at the dangers of essentialism and the issues of representation. Demographics may have a link to postdemographics–with certain demographics tending to prefer certain media–but this trend does not necessary make a truism. It is just a trend. And when value judgements and hierarchies enter the equation, as the often do with taste, attention to the fragility and complications of trends becomes more important. One must check assumptions and sloppy reasoning all the more, as more potential connections get put on the table and our pattern-pushing brains have more to work with.

This points to larger issues of big data and postdemographic data more generally. Though “the garbage in garbage out” caveat is common when it comes to the data itself, it also has some connection to our interpretations. When making claims and synthesizing findings, research requires self-critical analysis of our own thinking and transparency in our reasoning. One can easily see connections that a correlation may draw, but as often noted, correlation does not equal causation.

In a similar way, similar interest does not mean similar postdemographic–or demographic. Just because I like Doc Martin doesn’t mean I like Dr. Who. And just because people who like classical music may have similar browsing habits, values, or memberships does not mean I do.

On the one hand, this is obvious. But its obviousness should not detract from its importance.

Narrative Numbers

[T]hey fancied that they could detect in numbers, to a greater extent than in fire and earth and water, many analogues of what is and comes into being—such and such a property of number being justice, and such and such soul or mind , another opportunity , and similarly, more or less, with all the rest—and since they saw further that the properties and ratios of the musical scales are based on numbers, and since it seemed clear that all other things have their whole nature modeled upon numbers, and that numbers are the ultimate things in the whole physical universe.

-Aristotle, Metaphysics, Book 1, 985b

Much of what interests me in data mapping and data extraction in light of network maps, concept modeling, vector space modelling, etc., is that they are not only methods, but also metaphysics.

Dealing with a corpus is a bit like the Pre-Socratics trying to find the underlying something that comprises reality.  The big ideas–or Big Idea–that connects or threads the works together. The corpus may have alcoves and pockets, islands and peninsulas, but unity and commonality exists. Patterns exist.

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Networked

When I first grew self-conscious that friends come and go–breakups, fights, forgotten phone calls a part of life–I found Nietzsche’s short aphorism in The Gay Science called “Star Friendship” helpful. In it, possibly alluding to his rift with Wagner, Nietzsche describes, “We were friends and have become estranged.” Even more, they are now “earth enemies.”

Yet, as Nietzsche also writes, “There is probably a tremendous but invisible stellar orbit in which our very different ways and goals may be included as small parts of this path — let us rise up to this thought! But our life is too short and our power of vision too small for us to be more than friends in the sense of this sublime possibility.”

So it’s a question of scale. At the one level, chance meetings, fights, or enduring partnerships exist in a certain way. We experience and name them with a certain vocabulary. But further up, in some “invisible stellar orbit,” these connections gain a different timbre or pattern. Like looking at a character map of Middlemarch, certain once-tangled relationships and social shifts emerge  with network forces affecting broader social cohesion.

For example, a meeting may bring together two distinct groups that were independent before, forming a “huge component” to use the language of Easley and Kleinberg. Or, as Merton describes, the “Matthew effect” might shift the circulation of a text, with a well-known scientist getting more coverage than a newbie simply through his or her tug in a network.

And with current technology, both in terms of data mining and visualization, we can get a better sense of that “stellar” perspective. I think the question remains, however, with what to do with it and how we understand it. In particular, I think it should shift the way we look at agency, moving it from an egosystem to an ecosystem, i.e. thinking of ways that we fit into broader networks and can influence them in a networked way and not in a purely self-based way.

I guess a way you could phrase it is this: how much agency do I have as a node and a collection of nodes?

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Archive, bro

I’m still a newbie to the world of digital humanities (DH), gradually wading into its tide of terms and tensions. At this stage, as I stand ankle-deep, I couldn’t help but think that some of the contention surrounding terms like “archive” come from the many uses it has.

As Trevor Owens points out, the word itself is already stretched and multivalent, ranging from tape decks on a bottom shelf to a specific philosophy of preservation and presentation, a philosophy that Kate Theimer explains eloquently.

But even more directly in the realm of DH scholarship and work, “archive” serves multiple meanings and plays off similar terms, like “database” or “collection” in different ways. More generally, it seems to serves as both repository and tool. In other words, it is a place to  preserve texts and contexts, drawing from a variety of sources, like the Walt Whitman Archive, but it also must present this information through coding, interfaces, and an effective use of metadata.

In particular, the potential that this presentation allows distinguishes DH archives from more traditional archives, in that it brings in both human and nonhuman participants into rather intimate, hybrid contact. Done effectively, it echoes the sort of “ice-skater’s dance” that Alan Liu describes in “The Meaning of the Digital Humanities,” in which human and machine can co-construct and co-discover knowledge  together. But done poorly, a digital archive is rather like a grandparent’s attic, filled with a wealth of fascinating odds and ends, but buried and scattered.

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