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On the potentials of interaction breakdowns for HRI

Published online by Cambridge University Press:  05 April 2023

Britta Wrede
Software Engineering for Cognitive Robots and Cognitive Systems, University of Bremen, 28359 Bremen, Germany
Anna-Lisa Vollmer
Medical Assistive Systems, Bielefeld University, 33615 Bielefeld, Germany
Sören Krach
Department of Psychiatry and Psychotherapy, Social Neuroscience Lab (SNL), Lübeck University, Center of Brain, Behavior and Metabolism (CBBM), 23538 Lübeck, Germany


How do we switch between “playing along” and treating robots as technical agents? We propose interaction breakdowns to help solve this “social artifact puzzle”: Breaks cause changes from fluid interaction to explicit reasoning and interaction with the raw artifact. These changes are closely linked to understanding the technical architecture and could be used to design better human–robot interaction (HRI).

Open Peer Commentary
Copyright © The Author(s), 2023. Published by Cambridge University Press

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Burdett, E. R. R., Ikari, S., & Nakawake, Y. (2022). British children's and adults’ perceptions of robots. Human Behavior and Emerging Technologies, 2022(January), 116.CrossRefGoogle Scholar
Hegel, F., Krach, S., Kircher, T., Wrede, B., & Sagerer, G. (2008). Understanding Social Robots: A User Study on Anthropomorphism. RO-MAN 2008 – The 17th IEEE International Symposium on Robot and Human Interactive Communication, August, pp. 574–579. IEEE.CrossRefGoogle Scholar
Hindemith, L., Göpfert, J. P., Wiebel-Herboth, C. B., Wrede, B., & Vollmer, A.-L. (2021). Why robots should be technical. Interaction Studies, 22(2), 244279.CrossRefGoogle Scholar
Krach, S., Hegel, F., Wrede, B., Sagerer, G., Binkofski, F., & Kircher, T. (2008). Can machines think? Interaction and perspective taking with robots investigated via FMRI. PLoS ONE, 3(7), 11.CrossRefGoogle ScholarPubMed
Nass, C., & Moon, Y. (2000). Machines and mindlessness: Social responses to computers. The Journal of Social Issues, 56(1), 81103.CrossRefGoogle Scholar
Pfeiffer, U. J., Timmermans, B., Vogeley, K., Frith, C. D., & Schilbach, L. (2013). Towards a neuroscience of social interaction. Frontiers in Human Neuroscience, 7(February), 22.CrossRefGoogle ScholarPubMed
Schilbach, L., Timmermans, B., Reddy, V., Costall, A., Bente, G., Schlicht, T., & Vogeley, K. (2013). Toward a second-person neuroscience. The Behavioral and Brain Sciences, 36(4), 393414.CrossRefGoogle Scholar
Schulte, C. (2008). Duality reconstruction – Teaching digital artifacts from a socio-technical perspective. ISSEP (2008).Google Scholar
Vollmer, A.-L., Read, R., Trippas, D., & Belpaeme, T. (2018). Children conform, adults resist: A robot group induced peer pressure on normative social conformity. Science Robotics, 3(21), eaat7111.CrossRefGoogle ScholarPubMed
Złotowski, J., Sumioka, H., Eyssel, F., Nishio, S., Bartneck, C., & Ishiguro, H. (2018). Model of dual anthropomorphism: The relationship between the media equation effect and implicit anthropomorphism. International Journal of Social Robotics, 10(5), 701714.CrossRefGoogle Scholar