Recipient design in human–robot interaction: the emergent assessment of a robot’s competence
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Abstract People meeting a robot for the first time do not know what it is capable of and therefore how to interact with it—what actions to produce, and how to produce them. Despite social robotics’ long-standing interest in the effects of robots’ appearance and conduct on users, and efforts to identify factors likely to improve human–robot interaction, little attention has been paid to how participants evaluate their robotic partner in the unfolding of actual interactions. This paper draws from qualitative analyses of video-recorded interactions between a robot and groups of participants, in the framework of ethnomethodology and conversation analysis. We analyse the particular ways in which participants shape their embodied actions, how they can reproduce a prior action that failed to obtain a response from the robot; and how they explore the robot’s embodied nature. We find a set of recurrent methods or practices, showing that robot-recipient design displays not only participants’ initial assumptions about the robot’s competences, but also more importantly perhaps their continuous assessment of the robot’s behaviour, and their attempts to adapt to it. Participants locally produce and constantly revise their understanding of the robot as a more or less competent co-participant, drawing from its past, current, and projected conduct and responsiveness. We discuss the implications of these findings for research in robotics and human–robot interactions, and the value of the approach to shed new light on old questions by paying attention to the quality of gesture and the sequential organisation of interaction.
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Studies of recipient design in talk to/with robots reveal users' assumptions about the interactional competence of their robotic co-participants and demonstrate the methods they use to make themselves understood given those assumptions.
“For example, studies of recipient design in talk to/with robots (Pelikan and Broth 2016; Avgustis et al. 2021; Tuncer et al. 2023) reveal users' assumptions about the interactional competence of their (robotic) co-participants, and demonstrate the methods they use to make themselves understood given those assumptions.”
From AI in situated action: a scoping review of ethnomethodological and conversation analytic studies (2025) · cites this paper as Tuncer et al. 2023
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AI in situated action: a scoping review of ethnomethodological and conversation analytic studies
Mlynář, J., de Rijk, L., Liesenfeld, A., Stommel, W., & Albert, S. (2025) · AI & SOCIETY · doi:10.1007/s00146-024-01919-x · Cited by 18 · see citing works
“For example, studies of recipient design in talk to/with robots (Pelikan and Broth 2016; Avgustis et al. 2021; Tuncer et al. 2023) reveal users’ assumptions about the interactional competence of their (robotic) co-participants, and demonstrate the methods they use to make themselves understood…”
- Authors
- Tuncer, S., Licoppe, C., Luff, P., & Heath, C.
- Affiliations
- King's College London (GB)
- Télécom Paris (FR)
- Corresponding author
- Tuncer, Sylvaine
- Venue
- AI & SOCIETY
- Published
- 2023-01-05
- Volume
- 39
- Issue
- 4
- Pages
- 1795-1810
- ISSN
- 0951-5666 (ISSN-L)
- 1435-5655
- OpenAlex
- W4313571751
- Cited by
- 36
- References
- 3
- Citations by year
- 2026: 12 · 2025: 11 · 2024: 9 · 2023: 4
- FWCI
- 10.68
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- AI & Society (publishedVersion, cc-by)
- Research Portal (King's College London) (submittedVersion, cc-by)
- HAL (submittedVersion)
- Funders
- King’s College London
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Social Sciences › Arts and Humanities › Language and Linguistics › Language, Discourse, Communication Strategies
- Keywords
- human-robot interaction, recipient design, social robotics, embodied action, ethnomethodology, conversation analysis
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