Abstract:We put forth a critical theoretical framework for analyzing generative models both descriptively and normatively. Our thesis is that generative models automate the production not only of intellectual labor or intelligence, but of a broader set of human social capacities we name "social doing." We do this by historicizing the commodification of sociality in the digital economy, leading to the availability of social data as the precondition for generative models. We elaborate our definition of "social doing" by drawing a distinction between "use" and "exchange" sociality and further differentiate between the ways that generative models either substitute for or mediate existing social relations and processes. We then turn to existing empirical research on how people use generative model-based products and the effects that their use has upon them. In this, we introduce the concept of Synthetic Sociality, a social reality in part fabricated by Silicon Valley's privately owned and undemocratically governed generative models. Lastly, we offer a normative analysis based on our findings and framework, and discuss future design opportunities.
| Subjects: | Computers and Society (cs.CY); Graphics (cs.GR); Machine Learning (cs.LG) |
| ACM classes: | K.4.2; K.2; I.2.0; I.3.3 |
| Cite as: | arXiv:2605.14090 [cs.CY] |
| (or arXiv:2605.14090v1 [cs.CY] for this version) | |
| https://doi.org/10.48550/arXiv.2605.14090 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Ana Dodik [view email]
[v1]
Wed, 13 May 2026 20:19:24 UTC (46 KB)