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by Jeremy Douglass & Mark Marino
“AI” is a current zeitgeist phrase in academia and culture at large, due in large part to the recent rise to public prominence of (and hype about) large language models (LLMs) and the consequences of their rapidly increasing capability, especially in the generation of images, prose, and code.
For Critical Code Studies the large language model era raises a number of questions with respect to our methodologies. Systems which could automatically summarize and translate code into plain-text descriptions (or could generate code from plain-text descriptions) were previously rare, highly specialized, and limited--and suddenly they are becoming commonplace, in part due to a concentrated research agenda on code generation (i.e., if there’s one thing programmer’s would like LLMs to produce…). This evolving situation raises at least three broad categories of questions about the intentional humanistic reading of code:
There are of course many questions beyond these. Conversations about CCS+AI occur in the context of a number of related discourses, with one notable recent addition being Critical AI. As they write on https://criticalai.org:
Though rooted in critical methods from the humanities, social sciences, and arts, Critical AI works with technologists, scientists, economists, policy makers, health professionals, teachers, community organizers, legislators, lawyers, and entrepreneurs who share the understanding of interdisciplinary research as a powerful tool for building and implementing accountable technology in the public interest. Open to ideas born of new interdisciplinary alliances; design justice principles; antiracist, decolonial, and democratic political practices; community-centered collaborations; experimental pedagogies; and public outreach, Critical AI functions as a space for the production of knowledge, research endeavors, teaching ideas, and public humanities that bears on the ongoing history of machine technologies and their place in the world.
Our goal for this “AI” special topic of the Critical Code Studies working group is to solicit through this discussion as wide a range as possible of different experiences, perspectives, and insights into the intersection of contemporary AI and code, and what that tells us about Critical Code Studies. For some of our members this is a current area of active research--or active pedagogical practice. For others, being drawn into the hype of “AI” headlines may ultimately be a trap, whether due to the empty signifier of artificial “intelligence,” the devastating environmental impacts that corporate LLM paradigm appears to entail, or the implication of AI agents in the ongoing alienation of labor / “deskilling” enacted by algorithmic neoliberalism--among other possible reasons.
To kick off this week’s conversation, Mark and I brainstormed a list of a few CCS+LLM-related topics and questions to share with each other in an informal conversation. These included questions about intentional writing, interpreter personas, code and accessibility, and the role of the detail in code interpretation.
Below is the ~15 minute video:
We have also provided our shared pre-discussion topic brainstorm list below as an aid to discussion:
Our ask for participants is to:
...and, in addition, you might consider: