Common ground in artificial intelligence applications

Abstract With the advance of contemporary internet based artificial intelligence (AI), many interactive scenarios emerge. The interaction between a user and their device centers around the provision and build-up of information that is recorded for further individual or communicative usage. Social media and messaging services are providing AI-based affordances that enable the implementation of adjacency, the provision of background knowledge and recipient design through links and hashtags, and expressions of stance and acknowledgement through likes. Further to that, virtual assistant technologies have become popular and widespread. Through AI, the mobile and home-based assistants are built to directly employ and facilitate pragmatic realities of communication, like turn taking, talk and reaction on the basis of common ground, addresses and ways of responding to them. In this article, I show that modern AI applications for domestic and mobile communication usage, both between humans and for human-machine interaction, are built around the idea of common ground. Taking into account the privacy concerns that are associated with sizable data transmission, I introduce the term übercommon ground for information that is tracked from users’ online activity and used for the benefit of a better browsing experience, but also potentially passed on without the users’ consent.