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Accepted Paper

GenAI as parasite: Tracing the reconfiguration of a knowledge-building community through the Stack Exchange data dump  
Jukka Huhtamäki Kévin Carillon (UCLouvain) François Lambotte (UCLouvain)

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Paper short abstract

Following Serres (1980), we conceptualize the relationship between GenAI and a Q&A platform Stack Exchange (SE) as parasitic, with GenAI acting as an extractor and disruptor and SE serving as the host. Our lens focuses on data dump, a core sociotechnical artifact serving as the extractive resource.

Paper long abstract

Following Serres (1980), we conceptualize the relationship between GenAI and a Q&A platform Stack Exchange (SE) as parasitic, with GenAI acting both as an extractor and disruptor and SE serving as the host. Founded in 2009, SE operated without major disruptions until the launch of modern GenAI tools, after which major perturbations emerged.

Epistemologically, we enter the analysis through the data dump, a core sociotechnical artifact archiving all the contents of the SE platform. We take a computational-qualitative approach to trace the data dump on discussions between SE community members, moderators, and company representatives held on dedicated meta forums and available as part of the data dump. Moreover, we draw from developer platforms GitHub and HuggingFace to identify the affordances and qualities that the developers perceive in the data dump.

Our analysis identifies and conceptualizes three movements of the parasite framework in the platform capitalism context in the GenAI era. The first is extraction (or grabbing, or capture): for us, the fact that the data dump is used without visible reciprocity for the host (no return contributions, institutionalized acknowledgement, or value-sharing arrangements). The second is the production of noise (or interference), which is central in Serres' thinking: the emergence of controversies on SE, governance frictions, and a loss of trust, including credibility disputes, suspicion, and tightening of policies. The third is the reconfiguration of flows: the displacement of attention and value toward AI systems and external infrastructures, observable through declines in visits/contributions and shifts in usage trajectories.

Traditional Open Panel P125
A field in formation: What do we mean by ‘critical’ and ‘AI’ in Critical AI Studies?
  Session 3