Daniel Punday reviews Andrew Klobucar’s edited collection of essays, The Community and the Algorithm: A Digital Interactive Poetics.
Current debates about the coming impact of generative artificial intelligence have focused primarily on the role of these algorithmic systems in individual creative and professional activities. The instances that come to mind most frequently are a student generating a term paper, or a visual artist being made obsolete by AI’s ability to quickly generate stock images. Such algorithms are offered as a fundamentally new intervention of technology into human life. As Matthew Kirschenbaum has written about the “textpocalypse,” “Our relationship to the written word is fundamentally changing” and “It is easy now to imagine a setup wherein machines could prompt other machines to put out text ad infinitum, flooding the internet with synthetic text devoid of human agency or intent: gray goo, but for the written word.”1See also Davin Heckman’s commentary on Kirschenbaum for ebr, “Thoughts on the Textpocalypse.” Even those commentators who have defended these systems as a productive contribution to their own work, like Farhad Manjoo explaining in The New York Times the way that he uses generative AI to overcome writer’s block, have tended to adopt this focus on individual creative practices. At my own university, debates about possible policies on the use of AI in the classroom have drawn on the analogy to the role of the calculator in the college class. When first introduced, the story goes, teachers banned them and forced students to do calculations by hand; today such an approach seems absurd. So, too, many have concluded, AI will be an inevitable tool to generate content of all sorts, and we’re better off thinking about ways to integrate these systems into our professional and academic lives than to fetishize the equivalent of the slide rule.
It is this widely shared but narrow perspective on the algorithm that makes Andrew Klobucar’s edited collection of essays, The Community and the Algorithm: A Digital Interactive Poetics, so welcome. Contributors include a wide variety of university faculty and practicing digital artists all interested in exploring how algorithmic thinking can be expanded—especially in the classroom. By shifting attention towards the potential for algorithmic activities in creative communities, this collection makes clear how limited the terms of the debate have been. Klobucar’s collection intervenes into this widespread mixture of panic and celebration about algorithms by challenging three fundamental assumptions we see in popular conversations: the unstated premise that the algorithm is uniquely contemporary, a technology-driven phenomenon; the focus on individual professional or creative activity; and the assumption that algorithms ultimately are in conflict with human agency.
Klobucar’s introduction to the volume does an admirable job tackling the first issue, dedicating the very first sentence to the surrealist writing exercise of “exquisite corpse” (xiv). He notes that the game requires “the barest of tools: a single sheet of paper and enough pens or pencils for each player to use,” explaining the simple rules that players must follow: “In one version, each collaborator adds to a composition in sequence, either by following a generic syntax template, such as ‘article adjective noun adverb verb preposition article adjective noun’” [...]. Other versions allow each subsequent contributor to work directly from the last two or three words provided by the previous writer” (xiv). These simple rules for producing text remind us that the current anxieties about text generation are not uniquely technological in nature. We’re likely to see more scholarship on what we might call the pre-history of the algorithm over the next few years, as algorithmic thinking becomes an increasingly important cultural “key-word,” as Ted Striphas argues. Indeed, his recent book, Algorithmic Culture Before the Internet is a perfect example of this kind of historical excavation of the algorithm, although his focus on its origins in mathematics makes it very different from The Community and the Algorithm. Klobucar’s similar attempt to broaden the historical frame is very much welcome.
Just as important in this discussion of exquisite corpse is the communal nature of the text production: “Almost immediately, a messy, highly interactive group project takes shape, briefly shocking the contributors with its results, yet allowing each of them to escape full responsibility” (xv). Other chapters offer more contemporary examples of collaborative practices. Rui Torres and Daniela Côrtes Maduro discuss the promise of author/reader collaborations in digital writing across a wide variety of electronic literature, sometimes called “wreadings,” for merging writing and reading in their chapter, “Wreadings: Digital Poetry and Collaborative Practice.” They see this as especially powerful in the classroom subjecting “the concept of authorship [...] to creative reexamination” (22). In her chapter, “Digital Swarm Techniques: A Case Study to Teach Digital Collaboration and Disrupt Power Structures in Education,” Maria Aladren picks up on the potential for these collaborative practices in the classroom, claiming that they can “disrupt power structures in education” (57). She advocates for “swarm pedagogy principles” (63) that “help students tolerate failure and diminish its impact in pedagogical groups, and, thus, [help] to ‘free’ the student to question, fail, and create” (71). The difference between this view of algorithmic creativity and the anonymous text production that Kirschenbaum worries about is striking.
Equally interesting is this focus on disrupting institutional spaces. In almost all current discourse around our coming algorithmic future, our governmental, educational, and business institutions are taken as a kind of a given. We worry if ChatGPT makes it impossible to distinguish between student writing and AI authored texts, in large part because we take the institutions as a stable context: how am I supposed to grade papers in this new AI world? Likewise, the broader anxiety about the way that this might change the employment landscape largely depends on a static understanding of the world: if AI can write basic news reports (which it has been doing for decades), or if AI can generate stock photos instead of relying on photographers, the employment landscape will simply shrink by that same amount. Of course, it is easier to think about disrupting institutions in the relatively safe space of the classroom, where the goal is to explore ideas and creative activities. But The Community and the Algorithm makes a compelling case that we should think about the algorithm’s ability to change our communities, rather than just framing the matter as a zero-sum exchange, where algorithms displace human activity. In a thoughtful Medium essay, David Golumbia reflects this zero-sum thinking when he notes the irony of automating precisely the kind of jobs that most of us find compelling and satisfying: “As they have with other Generative AI programs like DALL-E and Stable Diffusion, creators have raised alarms about the technology. Some of their worries have to do with replacing their jobs–jobs which, it should be noted, are generally among the kinds of work that people enjoy doing and, presuming they are properly compensated, derive significant satisfaction from doing.” Golumbia makes a good point about the nihilism implicit in much of the thinking about AI generated material, but Klobucar’s volume offers another vision for such content that supplements and expands human creativity, rather than replacing it.
Finally, this volume places the creative potential of algorithms at its center. In many ways, this simply builds on its community focus, since at the heart of all of these essays is the way that a group can use algorithms to do something that really wasn’t possible before. But the ability of these kinds of algorithmic systems to foster creative practices, rather than simply replacing artists, is something that needs more emphasis in our current debates. In a recent Atlantic article, Ian Bogost wrote about how he is using AI image creators like DALL-E to produce visuals to accompany seemingly trivial musings (“My daughter texted, asking what her ‘goth name’ should be; moments later, I sent back an Edward Gorey–style illustration of her possible Victorian-dead-girl alter ego”) and he concludes by emphasizing AI’s potential to help us think: “But I’ve certainly noticed that the technology works best when I use it to extend my imagination rather than my image generation. [...] To construct a goth rendition of my daughter demands pondering the nature of her personality and how it might be expressed in dark-horror form. Seeing the results teaches me something about myself and my experience, even if I’m the only person who ever sees the results.” The Community and the Algorithm offers compelling examples of this creative use of algorithms in a wide variety of artistic and educational contexts.
I do have some reservations about elements of this collection, most of which are inherent to the nature of a volume produced by a variety of contributors. There is a somewhat uneven presence of the COVID pandemic in the book. Some chapters, like Anastasia Salter’s discussion of interactive storytelling and “critical making” (78) in her chapter “Maker Generation? The Uncertain Future of Students as Interactive Storytellerrs” frames its composition in the summer of 2020 quite explicitly (73), while in others COVID as a circumstance or motivation for pedagogical or compositional changes is absent. This is hardly a significant flaw, but it does reflect the nature of such collections, written as they are at different times with different ideas about the overall goal of the project. There is an interesting question here about the relationship between pandemic-inspired reliance on technology and the sudden rise in algorithmic tools in the last year or so, but the heterogenous nature of collections like this make it hard to pursue that question consistently.
This variation in goals is somewhat more important when it comes to understanding the definition of the algorithm itself. Although I think that most of the chapters really do explore algorithmic practices in a relevant manner, there are others that stretch the definition of algorithm in a way that may not ultimately be helpful. Rob Wittig's Chapter, “Netprov: Collaborative, Online Roleplay as an Art Form,” defines his key term as a “creative use of social media, where fictional scenarios are devised and performed over a chosen network platform” (87). Defined this way, netprov does make use of rules for roleplaying; but in general the dominant impulse behind netprov is, of course, improvisation. Would live-action improvisation (familiar from so much stand-up comedy) also be algorithmic? This is an interesting question to consider: does the term “algorithm” remain useful in this expanded context, and useful for what? But like many edited collections whose contributors work mostly independently, there really isn’t motivation to ask questions between the chapters in this way. That’s a shame because one question implicit in this volume is how our understanding of non- or pre-digital creative practices benefit from being described as algorithmic–or, perhaps, are harmed by being subordinated to the digital.
Obviously, from the way that I have framed this review, I think that with this turn to communal creativity and (mostly) non-AI algorithms, Klobucar offers a corrective to our current ChatGPT panic. But any collection like this is also making a claim to define a field or area of inquiry, and so I hope that this collection prompts us to pay more attention to the stakes of this kind of disciplinary reorientation, even if it doesn’t quite provide an answer. What happens when we frame a bunch of analog creative practices as algorithmic?
Works Cited
Bogost, Ian. “A Tool to Supercharge Your Imagination.” The Atlantic, October 31, 2023. https://www.theatlantic.com/technology/archive/2023/10/ai-image-generation-human-creativity-imagination/675840/.
Golumbia, David. “ChatGPT Should Not Exist.” https://davidgolumbia.medium.com/chatgpt-should-not-exist-aab0867abace.
Heckman, Davin. “Thoughts on the Textpocalypse.” Electronic Book Review, May 7, 2023. https://electronicbookreview.com/essay/thoughts-on-the-textpocalypse/
Kirschenbaum, Matthew. “Prepare for the Textpocalypse.” The Atlantic, March 8, 2023. https://www.theatlantic.com/technology/archive/2023/03/ai-chatgpt-writing-language-models/673318/
Klobucar, Andrew, ed. The Community and the Algorithm: A Digital Interactive Poetics. Vernon Press, 2021.
Manjoo, Farhad. “ChatGPT Is Already Changing How I Do My Job.” The New York Times, April 21, 2023. https://www.nytimes.com/2023/04/21/opinion/chatgpt-journalism.html.
Striphas, Ted. Algorithmic Culture Before The Internet. Columbia University Press, 2023.