DOI: 10.1111/josl.12684 DIALOGUE: COMMENTARY Machines built out of other people’s words: Comment on Helen Kelly-Holmes’ discussion article Ilana Gershon 1 Courtney Handman 2 1 Department of Anthropology, Rice University, Houston, Texas, USA 2 Department of Anthropology, University of Texas, Austin, Texas, USA Correspondence Ilana Gershon, Department of Anthropology, Rice University, Houston, TX 77098, USA. Email: igershon@rice.edu 1 INTRODUCTION In asking how sociolinguists should engage with generative artificial intelligence (AI), Helen Kelly- Holmes explores useful methodological cautions that scholars attentive to language in social contexts should keep in mind when engaging with large language models. As linguistic anthropologists, we find her take suggests useful warnings, and also serves as a reminder of how our two disciplines have concerns that speak productively to each other, yet occasionally differ in orientation. She calls schol- ars’ attention to how the use of generative AI is increasingly entering seamlessly and often invisibly into social interactions that have so far been studied as only occurring between humans. In doing so, she reframes a longstanding question that linguistic anthropologists and sociolinguists share, namely: what does one learn about communication when one takes every communicative interaction to be the cooperative co-production of meaningfulness? In turning to generative AI, the question now becomes what happens if this cooperative co-production of meaningfulness takes place when one of the partic- ipants is a new type of actor that operates according to principles of machine semiosis, and thus offers utterances resulting from probabilistic analysis instead of utterances keyed to context. Or put another way, since generative AI never refers, and people often view referentiality as a vital aspect of commu- nication, what should sociolinguists be careful to attend to when studying human–AI interaction? We propose building upon Helen Kelly-Holmes’ insightful questions to offer some further suggestions of what scholars might attend to now that generative AI is a participant, focusing in turn on each compo- nent of the cooperative coproduction of meaningfulness. In some cases, the sociolinguistic toolkit will be very helpful. In other cases, we suggest that sociolinguistics will need to borrow from other sources to tackle some of the challenges that generative AI poses. 2 CO-OPERATIVE What does it mean to understand generative AI as cooperating with its human interlocutors to produce meaning through interaction? Kelly-Holmes suggests that to understand this, scholars need to ask: “How do we deal now with technologically (co-)produced language, with a conversation or interaction 44 © 2024 John Wiley & Sons Ltd. Journal of Sociolinguistics. 2024;28:44–48. wileyonlinelibrary.com/journal/josl