August 2021

An artificial turn in social interaction research?

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.


Nevile, M. (2015). The Embodied Turn in Research on Language and Social Interaction. Research on Language and Social Interaction, 48(2), 121–151.

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The interactional coordination of virtual and personal assistants in a homecare setting

Saul Albert, Magnus Hamann & Elizabeth Stokoe (for the 6th Copenhagen Multimodality Day), October 2021.


Policymakers and care service providers are increasingly looking to technological developments in AI and robotics to augment or replace health and social care services in the context of a demographic ageing crisis (House of Lords, 2021; Kingston et al., 2018; Topol, 2019, pp. 54–55). However, there is still little evidence as to how these technologies might be applied to everyday social care situations (Maguire et al., 2021). This paper uses conversation analysis of ~100 hours of video recorded interactions between a disabled person, their virtual assistant (Alexa), and their (human) personal assistant to explore how routine care tasks are organized in a domestic setting. We focus on how the human participants organize conversational turn-space around ‘turns-at-use’ with the virtual assistant. Specifically, how turns-at-use ostensibly designed for the virtual assistant can recruit overhearing others. Further, we show how participants include the virtual assistant in their shared taskscape by, for example, putting ongoing activities and conversations on hold, visibly reorienting their bodies, or explicitly making themselves available for – or requesting – assistance when coordination trouble emerges between the machine-human dyad. Our findings show that virtual assistants expand the affordances of a homecare environment but do not replace the work of personal assistants.


Alač, M., Gluzman, Y., Aflatoun, T., Bari, A., Jing, B., & Mozqueda, G. (2020). How Everyday Interactions with Digital Voice Assistants Resist a Return to the Individual. Evental Aesthetics, 9(1), 51.

Amazon Echo. (2019). Amazon Alexa: Sharing is Caring.

Archibald, M. M., & Barnard, A. (2018). Futurism in nursing: Technology, robotics and the fundamentals of care. Journal of Clinical Nursing, 27(11–12), 2473–2480.

Bedaf, S., Gelderblom, G. J., de Witte, L., Syrdal, D., Lehmann, H., Amirabdollahian, F., Dautenhahn, K., & Hewson, D. (2013). Selecting services for a service robot: Evaluating the problematic activities threatening the independence of elderly persons. 2013 IEEE 13th International Conference on Rehabilitation Robotics (ICORR), 1–6.

Casey, D., Felzmann, H., Pegman, G., Kouroupetroglou, C., Murphy, K., Koumpis, A., & Whelan, S. (2016). What People with Dementia Want: Designing MARIO an Acceptable Robot Companion. In K. Miesenberger, C. Bühler, & P. Penaz (Eds.), Computers Helping People with Special Needs (pp. 318–325). Springer International Publishing.

Chappell, N. L., Dlitt, B. H., Hollander, M. J., Miller, J. A., & McWilliam, C. (2004). Comparative Costs of Home Care and Residential Care. The Gerontologist, 44(3), 389–400.

Dowling, S., Williams, V., Webb, J., Gall, M., & Worrall, D. (2019). Managing relational autonomy in interactions: People with intellectual disabilities. Journal of Applied Research in Intellectual Disabilities, 32(5), 1058–1066.

García-Soler, Á., Facal, D., Díaz-Orueta, U., Pigini, L., Blasi, L., & Qiu, R. (2018). Inclusion of service robots in the daily lives of frail older users: A step-by-step definition procedure on users’ requirements. Archives of Gerontology and Geriatrics, 74, 191–196.

Goodwin, C. (2000). Action and embodiment within situated human interaction. Journal of Pragmatics, 32(10), 1489–1522.

Harmo, P., Taipalus, T., Knuuttila, J., Vallet, J., & Halme, A. (2005). Needs and solutions—Home automation and service robots for the elderly and disabled. 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 3201–3206.

House of Lords. (2021). Ageing: Science, Technology and Healthy Living (p. 132). House of Lords Science and Technology Select Committee.

Kachouie, R., Sedighadeli, S., Khosla, R., & Chu, M.-T. (2014). Socially Assistive Robots in Elderly Care: A Mixed-Method Systematic Literature Review. International Journal of Human–Computer Interaction, 30(5), 369–393.

Kendrick, K. H., & Drew, P. (2016). Recruitment: Offers, Requests, and the Organization of Assistance in Interaction. Research on Language and Social Interaction, 49(1), 1–19.

Kingston, A., Comas-Herrera, A., & Jagger, C. (2018). Forecasting the care needs of the older population in England over the next 20 years: Estimates from the Population Ageing and Care Simulation (PACSim) modelling study. The Lancet Public Health, 3(9), e447–e455.

Krummheuer, A. L., Rehm, M., & Rodil, K. (2020). Triadic Human-Robot Interaction. Distributed Agency and Memory in Robot Assisted Interactions. Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction, 317–319.

Levine, D. M., Ouchi, K., Blanchfield, B., Diamond, K., Licurse, A., Pu, C. T., & Schnipper, J. L. (2018). Hospital-Level Care at Home for Acutely Ill Adults: A Pilot Randomized Controlled Trial. Journal of General Internal Medicine, 33(5), 729–736.

Maguire, D., Honeyman, M., Fenney, D., & Jabbal, J. (2021). Shaping the future of digital technology in health and social care. The King’s Fund.

Share, P., & Pender, J. (2018). Preparing for a Robot Future? Social Professions, Social Robotics and the Challenges Ahead. Irish Journal of Applied Social Studies, 18(1).

Stokoe, E., Sikveland, R. O., Albert, S., Hamann, M., & Housley, W. (2020). Can humans simulate talking like other humans? Comparing simulated clients to real customers in service inquiries. Discourse Studies, 22(1), 87–109.

Topol, E. (2019). The Topol Review: Preparing the healthcare workforce to deliver the digital future (p. 103). Health Education England.

Tuisku, O., Pekkarinen, S., Hennala, L., & Melkas, H. (2018). “Robots do not replace a nurse with a beating heart”: The publicity around a robotic innovation in elderly care. Information Technology & People, 32(1), 47–67.

White, G. W., Lloyd Simpson, J., Gonda, C., Ravesloot, C., & Coble, Z. (2010). Moving from Independence to Interdependence: A Conceptual Model for Better Understanding Community Participation of Centers for Independent Living Consumers. Journal of Disability Policy Studies, 20(4), 233–240.

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Putting wake words to bed

Magnus Hamann and I wrote a provocation paper for the third conference on Conversational User Interfaces 2021.

In it, we argue (hopefully provocatively), that voice user interface designers should stop using wake words like “Alexa” and “Hey Siri” that are crowding each other out of the audible environment of the smart home. Our point is that, as interface elements, wake words are misleading for users who seem to treat them like fully-fledged interactional summons, when they’re really little more than glorified ‘on’ buttons.

We got a surprisingly positive response from the technically-inclined audience at the conference. I found it surprising mostly because wake words are so ubiquitous and central to the branding and functionality of today’s voice interfaces that it seems hard to imagine them being phased out in favour of something more prosaic.

You can read the full paper on the ACM site, or a preprint here.


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