I told the organizers that I wanted to do a project on Steampunk and Blake, but I subsequently embarked on a project that I found to be potentially more interesting for this conference. I hope you’ll forgive me in changing the presentation. I’m titling my presentation “@autoblake: repurposing Blake’s approach to critical making as a research methodology” to specifically identify my interest - which is not anything historical but is methodological. In other words, what can programers, makers, and hackers learn from William Blake and, conversely, what sorts of opportunities are critical making (and the digital humanities) making for new kinds of scholarship?
My thinking is inspired by three figures: two of them in Blake studies and a third from the emerging field of critical making. Let’s start with the middle quote. Figures like Ratto, Garnet Hertz, Jentery Sayers, Kari Kraus are starting to question what kinds of critical work can be accomplished by making objects, databases, or other creative work instead of traditional written scholarship. Another scholar that works here is Marcel O’Gorman, who advocates what he calls “Applied Media Theory.” In O’Gorman’s terms, he’d like to see creative work that “examines” and “intervenes” in digital culture. I prefer the term “critical making” because it broadens that definition to any kind of critical intervention occurring within making practices. There are other scholars that can be added to this genealogy (Gregory Ulmer and even Deleuze and Guattari), but I’d like to focus mostly on critical making itself. Two other thoughts. First, by Robert Essick whose statement about modality and Blake is essential to understanding making as a form of critical response. Is the textual article, I’d add, the most appropriate venue to respond to Blake’s works - considering their own “composite” modality? Second, Mike Goode’s recent article in Representations mentions a tendency for Blake’s work to “de-compose itself,” something Jason Whittaker and I also explore in William Blake and the Digital Humanities under the term “zoamorphosis.” The idea complicates Essick’s observation about modality, because it emphasizes just how much Blake’s words can be transported into new contexts and spaces by people interested in using made-objects or creative work as a response to him.
One of the places I see a tradition of making in Blake studies (perhaps unconsciously) is the materialist school characterized by the work of Viscomi, Phillips, Essick, Eaves, Sung, and others. In fact, Sung makes the argument in William Blake and the Art of Engraving that much of the materialist experiments by these scholars is inspired by Ruthven Todd’s association with Surrealist automatic writing exercises. I’m fascinated by the idea that a making practice, inspired by what is seen as intuitive and artistic, contributes to the scholarly discourse about Blake’s methodology. I’d like to see more scholars start producing material artifacts that give us a tactile association with Blake’s work, and have that complimenting the papers that are presented at conferences like ICR and the articles published in European Romantic Review or in books.
William Turkel, Jentery Sayers, and the other members of the MakerLab at the University of Victoria are experimenting with conceptualizing made-objects as cultural and pedagogical objects in their “Kits for Cultural History” grant funded by the Social Sciences and Humanities Research Council (SSHRC). Their goal of “foster(ing) technology-based learning through tacit engagements with media and mechanisms of the past” reveals a very different approach to history than the traditional discursive modalities that are common in the humanities. Their first project, as you can see, is the construction of a pedagogical kit for a phonograph that includes it’s material parts, an arduino microprocessor (which you can program and add to other circuits), pdfs of relevant critical and historical work associated with the object, and sound files that provide relevant music to play on the phonograph. Imagine what a Blakean could do with this kind of scholarly production. Kits could be produced to give students (and in some cases, scholars) direct, tactile access to the kinds of methodologies Blake employed in his own work.
I think it is also important, though, to emphasize creativity and not just process in critical making practices. After all, Blake himself did not copy other people’s methodologies — he invented his own, conceptualized as a critical intervention into mass printing practices during the period coupled. Methodologies, for Blake, aren’t to be simply imitated, they are to be transformed in the act of making. One of the practices in the critical making movement that has a similar transformational aspiration can be found in the act of circuit-bending. People who practice circuit-bending customize circuits to create novel (often audio) effects by probing different potential connections with a jumper wire. This is called finding a “bend,” or a completed electrical circuit that isn’t associated with the normal function of the device. A connected speaker registers the kinds of sounds produced by the bend. Lots of electronic musicians create sounds with circuit-bending, but it has also become a symbol in the critical making community for hacked, creative, or otherwise critical transformations of obsolete technology.
Blake’s been particularly honored by the maker community. The upper left image is from an article in Make Magazine, the official magazine (some would say “capitalist appropriation”) of the Maker movement. The author, Gareth Branwyn, calls Blake the “Patron Saint” of Makers, and indeed many making communities take inspiration from Blake’s working class, creative ethos. The other two images show some creative interventions into Blake’s work. The first is from the aforementioned O’Gorman on his Cycle of Dread - which involves “hardwiring a stationary bicycle to a computer so that a cyclist’s speed, distance, and heart rate control the outcome of a multilinear, animated narrative.” The power of O’Gorman’s piece lies in its challenge to the dichotomy between the physical and the digital (i.e. digital narratives are not immaterial). On the bottom, we have Jon Saklofske’s New Radial, which gives users the ability to visually manipulate different illuminated pages of Blake’s Songs. Saklofske has said he’s interested in the research possibilities of the Radial more than giving users the ability to create remixes of Blake’s work - but I’m fascinated in the way that computation (particularly) offers even more possibilities for the kinds of making interventions I’m proposing here.
So, the last part of this presentation documents my own experiments with a critical form of making. I decided to create a Markov-chain enabled Twitterbot that remixes David Erdman’s The Complete Poetry and Prose of William Blake. Markov-chain Twitterbots became famous mostly due to the @Horse_ebooks Twitter account. This account was originally created as a spam Twitter account to entice people to click on possibly dubious links. It started using non-sequitor statements generated by a Markov-chain algorithm in order to avoid detection from anti-spam software and has consequently captured the imagination of many Twitter afficianados. Programmers like Mark Sample (who’s created several Markov-chain Twitter accounts like @JustToSayBot) and Moacir Pranas de Sa Pereria (who created @KarlMarxovChain) started using the Markov-chain much to generate forms of poetic expression. There’s even a bot that generates Markov Chains for Garfield called Garkov.
A Markov-chain works much like Google auto-complete by creating chains of text based upon probability. Dan Catt explains it well here. Within a given textual corpus, there’s a certain probability that one word will follow another. This probability is often determined in a Markov-chain algorithm by what’s known as Markov order. If we, for example, set the Markov order to 0, then the algorithm spits out nonsense, since it assumes that all words have the same probability of appearing next to each other. If Markov order is set to 2 or 3 (the order closer to the English language) it will assume that certain words are more often paired with each other, then search for words based upon that probability. The resulting chains are displayed as tweets. By the way, this is a introductory explanation of how Markov-chains basically work but it certainly doesn’t cover every minute detail of the theory - which is complex and is a still-developing part of the Natural Language Processing field. Autocomplete is still pretty new, and gets things wrong often. I’m no expert in Markov-chain theory. My tweets aren’t perfect yet, and I still have some learning to do - especially when constructing complete sentences as tweets. Fortunately, given Blake’s complex, sometimes incomplete, and bizarre sentences, this isn’t as much of a problem as it would be with other authors.
Here’s a look at the code I used, adopted from Megan Speir’s Markov-Tweet library in Github. Notice “But try number 2” for Markov order, showing that you can experiment with the probabalistic construction of chains. I ended up using 2.75 for my Twitterbot. Speir has commented on the program, so you can see what each set of code lines actually do. Basically, it opens the file I added to the folder (blake.txt, a txt file of Blake’s Complete Poetry and Prose), reads the text (meaning forms chains based upon Markov order), then outputs the chain, prints it (displays it), and sends that display to Twitter. You can also see a space for inputting the various keys associated with Twitter. This allows you to access the Twitter API (application program interface), in order to allow the program to automatically post tweets. I had to also set cron, a program that will initiate the algorithm every three hours. You can set it to any time you want, but that’s what I used.
Here’s what the bot looks like on Twitter. You can follow it (@autoblake). Notice that I’m still working out kinks - mostly due to stray characters and incomplete sentences. Sometimes it doesn’t matter. It “sounds” like Blake. Other times, it doesn’t work as well. Ultimately, I feel scripts like this challenge assumptions about creativity — that it is primarily a human activity. We can see that, despite the fact I’ve programmed it to do so, the computer decides what chains to display as tweets. I don’t tweet these lines. Further, I think it adds another level to what it means to “read” Blake. Can we read these tweets as having relevance to Blake’s work? Is it simply nonsense? Literally, it might be, but I feel algorithms like this one complicate some of those questions in fascinating ways.
I’d like to end by bringing up the specter of copyright. I was only able to construct this program because Erdman’s Complete Poetry and Prose is held in the public domain, something both Erdman and his estate have felt to be extremely important. It’s not as clear how the incorporation of Blake’s illuminations would work in a situation like this, even if it were currently possible to automate remixed images in the same way we can automate remixed words. Matthew Jockers makes a really interesting argument at the end of Macroanalysis, arguing that scholars should have so-called “non-consumptive” rights when it comes to copyrighted works. He says this because most text mining in the digital humanities is done by 19th century scholars, leaving most modernists and postmodernist scholars unable to perform the same kinds of analysis on their own sources. “Non-consumptive” would mean that a scholar doesn’t reproduce a text to be read by human eyes, but to be processed by a computer. So, Jockers and the co-signers of this Amici Curae (myself included) argue, it should be held by a different standard than traditional copyright law. I’d like to suggest that copyrighted images (like those held on The Blake Archive) should have a similar legal standing. If we want to enable the next generation of mining (and creative) experiments, something I feel Blake would encourage, then we need to update our copyright laws to include affordances for non-consumptive use. Thanks!
