Jakub Mlynář, Andreas Liesenfeld, Lynn de Renata Topinková, Wyke Stommel, Lynn de Rijk, and Saul Albert for the 6th Copenhagen Multimodality Day: Interacting with AI
The turn towards multimodality and embodiment in interaction research has yielded new terminology and representational schema in key publications (Nevile 2015). At the intersections between multidisciplinary fields, e.g., ethnomethodological and conversation analytic (EMCA) research exploring interactions between humans and ‘AI’, social robots, and conversational user interfaces, such methodological changes are even harder to track. How do these approaches to the meticulous, naturalistic study of technologies in (and of) social interaction reframe the key terms, schema and practices that constitute AI as a field of technosocial activity? Largely grounded in the EMCA Wiki bibliography, we map this emerging field and report on a bibliometric review of 90 publications directly relevant to EMCA studies of AI (broadly defined) including social robots and their components such as voice interfaces.
We found that the most works cited in the EMCA+AI corpus are classics from the canon of human interaction research (Garfinkel, Sacks, Schegloff, Goffman), including multimodality (Goodwin, Heath), human-machine interaction (Suchman), and STS (Latour). The most frequently cited texts are: Sacks, Schegloff and Jefferson’s (1974) ‘turn-taking paper’ (in 45% of items from the corpus), Garfinkel’s (1967) Studies (40%), and Suchman’s (1987) book (31%). Dealing specifically with AI from an EMCA perspective, Porcheron et al.’s 2018 paper on voice user interfaces is the most cited (11%). Apart from this one, two other texts feature as citation hubs: Alač’s (2016) and Pitsch et al.’s (2013) papers on social robots and embodiment. The study aims to provide a starting point for discussion about how concepts such as embodiment, agency and interaction are shared, used and understood through the practice of academic citation.