by Finn
Since the beginning of my Master studies last fall I’ve continually struggled to figure out what STS does and how it fits with my own beliefs. Coming from the natural sciences, I felt some estrangement to what I perceived as a sometimes rather associative and arguably less rigorous style of thinking. I also haven’t had a clear understanding of the political claims of STS yet.
To explore some of those questions I thought it best to see some STS done outside of our cozy department in the top of NIG. So I skipped school for a few days and visited this year’s conference of the German STS society at Ruhr University Bochum. The theme was before ruins and I had a great time and met loads of nice people. I learned a lot from the very diverse talks (especially Anne Pasek’s awesome lecture on AI in Ruins) and enjoyed the dense studying experience.
Core to the conference was the experimental case format: almost a whole day was blocked for workshop-like explorations in groups around a topic or method, ranging from localartistic interventions to museum visits and discussions of academic boycotts. The cases were created by conference participants and placed in the center of the program, right between the opening event and association assembly on the first and the paper presentations on the third day.
As I had some prior curiosity about methods, I chose to participate in a case on computational approaches in STS. Due to my technical background, I also felt a little more confidentI’dbe able to at least contribute something there.
The six participants (including two digital humanities scholars organizing the case) toyed around with topic modeling to sort through a large collection of interview transcripts. After lunch we continued with the same body of text and prompted large-language models (LLMs) to reproduce analysis of passages using different hermeneutics (“You are a Social Scientist using Grounded Theory. Interpret the following passage:” or “You are Bruno Latour. Use your own theories and approaches to discuss the following text:”). Being in a fairly advanced stage of my anti-AI radicalization journey, it seemed dirty to learn from the LLM. I felt its infuriatingly clear and reductionist formulations had the potential to infect my thinking, tricking me into believing I could comprehend complex analytical frameworks just by reading a few churned-out paragraphs.
We discussed the results, critiques and potential usages for both technologies. All the typical worries about LLM output came up (flatness and oversimplification, lack of context and indiscriminate responses, etc.). Nevertheless, there still seemed to be a radical openness in the room towards both, a quantitative-y analysis as well as the straight-out outsourcing of analysis to LLMs. Obviously there
is some self-selection of case participants happening here. Still, in retrospect I also understand this as characteristic for a field in which, instead of building up schools and thought traditions that combine broad world views with methodological claims, scholars are free to pick and choose, entertaining a much more open attitude towards all kinds of experiments and interventions. The dissonance of attending a lecture on the ruins of AI on one day, while burning tokens the next, only fully became clear to me later.

“Now she wants to engage with weapons manufacturers because critique out of distance ran out of steam a long while ago. I’m surprised and irritated, but interested”

Bundeswehr [German military] prof would hold a keynote there”1
This peculiar openness also showcased in the more immediately political topics. There seemed to be little consensus and much disagreement about the politics of research collaborations and corrupting effects of funding. To me, the discussion seemed a little crude at times. My impression was, that contributions often focused on the individual researchers room for maneuver without acknowledging the manifold nature in which systems exercise power, e. g. the legitimizing effects of critique and research. This still surprises me, since I assume those themes have been debated in STS for years and would’ve expected more nods to existing concepts and views. In this discussion, however, I also noticed the limits of my perception. As a newcomer I could follow the spin of what was asked and answered, but couldn’t make out the contours of the clashing factions for lack of contextualizing knowledge on the larger conflict lines within the field.
Nevertheless, it felt relatively easy to inquire about those contested topics and the atmosphere felt very open and somewhat pointedly anti-hierarchical. Especially the case format had participants of varying seniority thinking about something new together and thus facilitated becoming acquainted at eye level. However I suspect this particular culture regarding hierarchies to also be a feature of interdisciplinary approaches in general: if no one’s subject-related knowledge subsumes their conversational partner’s what else is there other than discussing on equal footing?
Still, I also felt some discomfort about the fact that disciplinary and status borders were, if not dissolved, then at least shaken up a little. I caught myself wondering about how I should even assert the substance and merit of what was said on stage. Does STS’ openness include a programmatic disengagement from a classical style of academic evaluation? How are the requirements of academic performance measures translated to fields of so little comparability? And of what attachments of mine does my unease speak here?
Overall, before ruins taught me a lot. I met kind scholars who patiently explained their epistemic considerations to me and, while I remain skeptical in some regards, I understood others and got curious about more. Most of all, however, I got to know people making up a small corner of the STS community and gained much implicit knowledge about who is (doing) STS. I feel privileged to have become a little more part of the thought collective.
1 The Bundeswehr, Germany’s Military, sustains two civil universities. A faculty member of the University of the Bundeswehr Munich gave a talk at the conference.
Finn is a master’s student at the department with a background in Computer Science.
















