Hello,
On behalf of Sohyeon Hwang, I’d. like to share a panel event in Seattle from September 3-6.
“My colleagues and I are organizing an open panel on AI harms and communities at the 50th Annual Meeting of the Society for Social Studies of Science (4S)<https://urldefense.com/v3/__https:/www.4sonline.org/about_the_conference_se…>, September 3-6, 2025 in Seattle. Focused on the idea of "social model collapse," we advocate for consideration of harms to communities (including online communities) as they respond to, are used for, and incorporate generative AI algorithms.
The call asks for a 250 word abstract, due January 31. We would love to see your submissions - the full call is pasted below and also available at the blog post in this link<https://urldefense.com/v3/__https:/blog.communitydata.science/thinking-abou…>. More information about 4S and submitting can be found here: https://www.4sonline.org/call_for_submissions_seattle.php<https://urldefense.com/v3/__https:/www.4sonline.org/call_for_submissions_se…>.
Please feel free to reach out with any questions.
Thank you,
Sohyeon Hwang
Postdoctoral Fellow
Center for Information Technology Policy
Princeton University
Open Panel: Risks of ‘Social Model Collapse’ in the Face of Scientific and Technological Advances
Model collapse in machine learning refers to the deterioration such a model faces if it is re-fed with its own output, removing variation and generating poor output; in this panel, we extend this notion to ask in what ways the use of algorithmic output in place of human participation in social systems places those social systems at risk. Recent research findings in the generation of synthetic text using large language models have fed and been fed by a rush to extract value from, and engage with, online communities. Such communities include the discussion forum Reddit, the software development communities producing open source, the participants in the question and answer forum StackExchange, and the contributors to the online knowledge base Wikipedia.
The success of these communities depends on a range of social phenomena threatened by adoption of synthetic text generation as a modality replacing human authors. Newcomers who ask naive questions are a source of members and leaders, but may shift their inquiries to LLMs and never join the community as contributors. Software communities are to some extent reliant on a sense of generalized reciprocity to turn users into contributors; such appreciation may falter if their apparent benefactor is a tireless bot. Knowledge communities are dependent on human curation, inquiry, and effort to create new knowledge, which may be systemically diluted by the presence of purported participants who are only algorithms echoing back reconstructions of the others. Meanwhile, extractive technology firms profit from anyone still engaging in a genuine manner or following their own inquiries.
In this panel, we invite consideration of current forms of social model collapse driven by a rush of scientific-industrial activity, as well as reflection on past examples of social model collapse to better contextualize and understand our present moment.
Submissions are 250-word abstracts due January 31st; our panel is #223, “Risks of ‘Social Model Collapse’ in the Face of Scientific and Technological Advances” [Submission site link<https://urldefense.com/v3/__https:/www.xcdsystem.com/4sonline/member__;!!Dq…>].”
Madison Deyo
Program Coordinator
Northwestern University
The Center for Human-Computer Interaction + Design<https://www.hci.northwestern.edu/>
Community Data Science Collective<https://wiki.communitydata.science/Main_Page>
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