In thinking more about accessibility, pedagogy, and technology, I’ve been thinking explicitly about dis/ability and privilege and their relation to different technologies. While reading “Utopian Pedagogies” by Elizabeth Losh, I couldn’t help but feel that some of the points she was addressing were very engaging, but also possibly not fully embracing the many differences that accessibility can take.  I also wondered about how she is considering teaching from the margins specifically, given the title. However, Losh definitely addresses some interesting points around subversion and utilizing digital technologies as enabling creative and alternative forms of learning. I like her approach of subversion through digital technologies: “These are also pedagogies that draw attention to the procedural character of learning in ways that are potentially deeply subversive” (431). Although, my first question here is subversive for who? But I do agree that utilizing digital technologies has subversive potential. She continues saying, “Rather than present such procedurality as a set of predictable linear and hierarchical processes in which learning outcomes and assessment methodologies emphasize prescribed prerequisites and goals that are hard-wired into paths of sequential steps to success of failure, such pedagogies invite questions about rule-making and rule-breaking by facilitating activities that bring operational logics to the forefront.” Losh here is thinking about how technology can reorient pedagogical strategies in different directions by having students critique the very technology around them and begin to see the underlying logics functioning in these devices. And I’m particularly seeing this subversive pedagogy in connection to how access happens with these technologies. I would also definitely take her class on digital poetry.

Disability has a particularly interesting relationship to accessibility. As humans interact with the structures of materialized technology, dis/ability has a way of complicating and reassessing this relationship to it. How does the physicality of a body interact with technology? So for instance, how might someone who is blind or has low vision be able to use digital resources? What becomes of the usefulness of a screen when someone’s vision is impaired? Everyone has different ways of engaging and accessing technology, which largely goes overlooked when thinking about the physical design or structure of a website or platform. This recognition between user and platform becomes a way of also addressing and highlighting ability to then begin to possibly subvert ableist approaches to understanding digital technology.

Hastac.org has a list of different class activities, which I looked through and found one on disability (https://www.hastac.org/blogs/merylalper/2014/02/07/03-disability-and-defamiliarizing-smartphone-class-activity). The exercise is a very clever and simple way to have a class reassess their relationship to technology that they are familiar with. Meryl Alper, who designed the exercise, explains it as “Disability and Defamiliarizing the Smartphone,” where they break into small groups and explore the accessibility options on their phones. She explains that some students cut on the voiceover feature, where other students can hear their text messages, which causes them to feel very vulnerable and exposed. This exercise struck me also because the students aren’t necessarily put in a position of problematically imagining themselves with a disability, but instead are thinking about the how accessibility is structured on a device that they think they are feel familiar with, which makes them reassess their own relationship to not only technology, but their own abilities.

 

The “Failure” keyword of the Digital Pedagogy in the Humanities collection includes the “Teaching to Fail” artifact, which is derived from an essay by Edward Burger. His pedagogy is based on acknowledging, rewarding, building on, and celebrating failure in a variety of ways. In order to destigmatize–even encourage–failure in the classroom, Burger bases 5% of his students’ final grades on their “quality of failure.”  Grading students on failing throughout the semester encourages them to share their mistakes rather than hiding them–and encourages them feel free to make more mistakes in the first place.

For certain essay assignments, he instructs students to “intentionally fail–in the spirit of an industrial stress test” by first having write a first draft of an essay “very quickly and poorly” long before it’s due and also submitting their marked-up second-to-last draft with the final one.

That 5% “quality of failure” grade is based on several factors:

In the case of assessing “quality of failure,” at the end of the semester I ask my students to write a one-page reflective essay describing their productive failure in the course and how they have grown from those episodes (which might have occurred outside of class — including false starts and fruitful iterations). They conclude their essay by providing their own grade on how they have evolved through failure and mistakes (from 0 – meaning “I never failed” or “I learned nothing from failing” to 10 – meaning “I created and understood in profound, new ways from my failed attempts”). I read their narratives, reflect on their class participation and willingness to take risks, and then usually award them the surprisingly honest and restrained grades they gave themselves. To date, I’ve never had a student complain about their “quality of failure” grade.

Burger’s approach of teaching failure isn’t specifically related to dh. However, it is often impossible to learn how to use digital tools effectively without reaching failure or limit states. Rewarding failure through grading practices makes the value of failure tangible to students who might otherwise fear reaching the limits of digital tools and processes.

I don’t necessarily intend to bake failure into my syllabus. However, crafting assignments so that students are not just set up to fail but intend to fail seems very productive to me. I don’t want to toy with my students. Kobayashi Maru style tricks are against my teaching philosophy, but desmystifying writing and critical practices is very much part of it. Making “failure” –something that students are conditioned to avoid more than anything else — a part of the classroom conversation in a positive way seems deeply productive.

In thinking of DH projects as “instruments,” it was a pleasant surprise to see a presentation that envisioned DH tools as literal digital musical instruments that can be manually created through Dr. Berdahl’s “Synth-a-modeler” tool. Unlike existing synthesizer software, Edgar Berdahl’s toolset is more focused on the creation of musical instruments and the physical quality of their sounds.

The idea is that through a digital interface, one can create musical instruments through manipulating a simulacra of their physical components and recreate these sounds physically through 3D printing. Dr. Berdahl argues this process boasts interdisciplinary uses, mentioning specifically its uses in archaeology and physics. He also reiterated this project’s open-ended design philosophy, capable of being used to create experimental music or usable as a pedagogical device in the classroom.

There are a few issues with Dr. Berdahl’s project that deserve to be raised. 1.) The project seems to lack an apparently consistent language of databasing tools created in this software. While the tuning capabilities of the interface is very-well arranged by physical properties, the metadata does not seem to be a visible factor this early in the project’s development. This is a setback, but could become problematic in the future.

2.) The physical nature of the project’s interface is not fully “worked out.” Dr. Berdhal showed a few examples of physical peripherals that would work with the program, but did not discuss in detail alternatives to the “sliding device” he had on him. Further, it was unclear beyond the possibility of 3D printing peripherals could become available in the future.

These issues aside, Dr. Berdahl ended his lecture with a very important question, that I feel encapsulates a vital issue in Digital Humanities projects: “How do you create interdisciplinary knowledge that is interesting for all fields involved?” Such a question’s answer, I feel, depends on the question being asked and how pertinent it can be made to each fields through the communication of all fields involved with one another. However, this can only dent the surface of such an important question.

Tara McPherson’s argument in “Why Are the Digital Humanities So White?” is that the 1960’s moments in racial politics and computer software development “coconstitute one another, comprising not independent slices of history but instead related and useful lenses into the shifting epistemological registers driving U.S. and global culture in the 1960s and after.”

 

In another part of her essay, she puts it like this:

 

“I will argue that the difficulties we encounter in knitting together our discussions of race (or other modes of difference) with our technological productions within the digital humanities (or in our studies of code) are actually an effect of the very designs of our technological systems, designs that emerged in post-World War II computational culture. These origins of the digital continue to haunt our scholarly engagements with computers, underwriting the ease with which we partition off considerations of race in our work in the digital humanities and digital media studies.”

 

A bit later, in moving from a discussion of the UNIX operating system to “modularity in the social field,” she reframes the argument like this:

 

“The push toward modularity and the covert in digital computation also reflects other changes in the organization of social life in the United States by the 1960s. For instance, if the first half of the twentieth century laid bare its racial logics, from ‘Whites Only’ signage to the brutalities of lynching, the second half increasingly hides its racial ‘kernel,’ burying it below a shell of neoliberal pluralism.”

 

I want to start with a summary of McPherson because her argument illustrates an interesting problem in theorizing computation—in effect, theorizing a machine. Her argument relies on a very complicated set of analogies and metaphors situated somewhere between the notions of causality and correlation. She goes to lengths to head off objections that she’s offering a causal argument. At one point she claims merely to be “highlighting the ways in which organization of information and capital in the 1960s powerfully responds—across many registers—to the struggles for racial justice and democracy,” saying “it seems at best naïve to imagine that cultural and computational operating systems don’t mutually infect one another.”

 

But at other times McPherson seems to tip her hand with a kind of metaphorical/symbolical equation between a computer’s operating system, humanist critical philosophies, and socioracial zeitgeist, muddying her disavowals of causal argument. Here are a couple examples:

 

“UNIX is widely understood to embody particular philosophies and cultures of computation, ‘operating systems’ of a larger order that we will return to.” [Referring to the “philosophies and cultures of computation” embodied in UNIX as “operating systems.”]

 

“Critical theory and postructuralism have been powerful operating systems that have served us well…They are also software systems in desperate need of updating and patching. They are lovely, and they are not enough. They cannot be all we do, but that is not to say that they are not of any value.”

 

[And, from the earlier example, implicitly equating digital computing’s basis of discrete mathematical logic to the 20^th century “logics” of “‘Whites Only’ signage and the brutalities of lynching,” referring to racist policy/violence as a “racial ‘kernel’”—the most basic component of an operating system.]

 

 

Okay, my goal is not to hate on McPherson—trying to pin down what I found confusing about her article has opened up the area I want to explore in my paper. My goal will be to explore exactly what can be meaningfully said or discovered by examining computers—as both engineered objects and social tools—in light of a particular idea, theory, etc.

 

The problem, at one level, has to do with the validity of metaphor. It’s sort of metaphysical. Bridging the gap from apparent similarities in complexity and hierarchy (such as those between an operating system and a society) to concrete realities/outcomes requires a lot of heavy lifting. In a 2003 essay, Nick Bostrom made the argument that, most likely, humans are living in a computer simulation; part of his argument relied on the concept of “substrate independence.” He states:

 

“Provided a system implements the right sort of computational structures and processes, it can be associated with conscious experiences. It is not an essential property of consciousness that it is implemented on carbon-based biological neural networks inside a cranium: silicon-based processors inside a computer could in principle do the trick as well.”

 

In other words, the concept of “thought” is not a priori fused to the concept of “carbon.” We might justifiably call the electrical transactions of a silicon processor—one sufficiently similar to a brain—“thought.” The substrate—the material conducting the electric impulses—is, maybe, not the point.

 

McPherson seems to subscribe to a similar idea. She implies that the different substrates—whatever you call them—of the abstractions “operating system” and “theory” and “society” are immaterial, and that by observing trends, functions, operations, etc., of these structurally similar systems, we can draw useful observations—and that, moreover, the systems themselves do share a kind of substrate, not a physical one, but a more abstract, ideological one. In short, McPherson seems to say, these systems occupy one substrate—you could call it human conception, or a socially constructed worldview—and that changes in these structures/substrates “mutually infect on another.”

 

Okay. Whether you believe this is valid or not, it would seem that really connecting these substrates would require a whole bunch of finely-tuned, dense arguing. You would have to be clear about what aspect of what structure is doing what to which other aspect, and so on. Part of what I found frustrating about McPherson’s article was the implication of causation without anything beside, what seemed to me, vague gestures toward specificity. She gave isolated examples of computing software and what certain people wrote at certain points and by innuendo linked them to very broad trends in 1960’s culture and called it a day. Which brings me, finally, to the subject of my paper. Proposal: I want to find a concrete way of linking the structures and uses of computing to a theory about how and why they work in the world.

 

One possible way I’ve found of making this jump is in Gerd Gigerenzer’s (great name) concept of tools-to-heuristics. Gigerenzer talks about theories of discovery in cognitive psychology. He argues that accounts of discovery as probabilistic induction (from data), lucky guesses, and eureka! moments do not suffice in explaining where discovery comes from. He proposes a model where scientist’s tools “shape theories of mind”—how “analytical and physical tools” turn into “metaphors of mind.” Gigrenzer states it outright:

 

1. New scientific tools, once entrenched in a scientist’s daily practice, suggest new theoretical metaphors and concepts.
2. Once proposed by an individual scientist (or a group), the new theoretical metaphors and concepts are more likely to be accepted by the scientific community if the members of the community are also users of the new tools.

 

I see this as both (a) fairly reasonable on its surface and (b) a crucial theoretical link that can help organize thinking about the concrete aspects of computing and their theoretical implications. I think McPherson was really using this kind of logic, but didn’t do it in a very clear way. Further, I think she was guilty of at least a little reverse engineering—taking her theoretical prejudices and trying to cram notions of computational development into a shape that would support her views. (Not to say that her observations, hunches, and insights weren’t necessarily valid.) My goal in my paper will be to try a little more of a materialist (in the Marxist sense) progression from the physical realities of computer architecture to a theory of what they are and what they do. Since this is such an admittedly large and complex vista, I’ll proceed in the form of a few isolated case studies of particular digital structures and concepts to see what they imply and how they affect what the engineer, programmer, and end-user think/feel/do.

 

I, of course, have my own prejudices and areas of interest, and I won’t try to hide what my ideological goals are. I believe computers are an extremely complex manifestation of underlying capitalist logic. And while I will try to be more forthright and clear than McPherson (at least as I understood her), I do nonetheless have an axe to grind.

 

All that being said, the most clear and concise summary of what I hope to be up to is:

 

I want to perform a few theoretical case studies of digital-computational concepts—possibly including the structure of digital memory, the “slave/master” nomenclature of computer peripherals, the functions of registers and caches, and the reality of vertical software abstraction—in the context of Marx’s critique of capital. The goal will be seeing to what extent, and in what ways, computers represent, reflect, and enforce capitalist logic.

 

If you have read this far, I bow respectfully.