Hostname: page-component-848d4c4894-p2v8j Total loading time: 0 Render date: 2024-06-08T02:08:50.690Z Has data issue: false hasContentIssue false
  • English
  • Français

A neurocognitive view on the depiction of social robots

Published online by Cambridge University Press:  05 April 2023

Ruud Hortensius Open the ORCID record for Ruud Hortensius [Opens in a new window]  and
Eva Wiese
Ruud Hortensius
Affiliation:
Department of Psychology, Utrecht University, 3584 CS Utrecht, The Netherlands r.hortensius@uu.nl www.ruudhortensius.nl
Eva Wiese
Affiliation:
Cognitive Psychology & Ergonomics, Institute of Psychology and Ergonomics, School of Mechanical Engineering and Transport Systems, Berlin Institute of Technology, D-10587 Berlin, Germany eva.wiese@tu-berlin.de https://sites.google.com/view/gmuscilab
Get access Rights & Permissions [Opens in a new window]

Abstract

While we applaud the careful breakdown by Clark and Fischer of the representation of social robots held by the human user, we emphasise that a neurocognitive perspective is crucial to fully capture how people perceive and construe social robots at the behavioural and brain levels.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 46 , 2023 , e38
Check for updates
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abubshait, A., Weis, P. P., & Wiese, E. (2021). Does context matter? Effects of robot appearance and reliability on social attention differs based on lifelikeness of gaze task. International Journal of Social Robotics, 13(5), 863–876. https://doi.org/10.1007/s12369-020-00675-4CrossRefGoogle Scholar
Abubshait, A., & Wiese, E. (2017). You look human, but act like a machine: Agent appearance and behavior modulate different aspects of human–robot interaction. Frontiers in Psychology, 8, 1393. https://www.frontiersin.org/article/10.3389/fpsyg.2017.01393CrossRefGoogle Scholar
Cross, E. S., & Ramsey, R. (2021). Mind meets machine: Towards a cognitive science of human–machine interactions. Trends in Cognitive Sciences, 25(3), 200–212. https://doi.org/10.1016/j.tics.2020.11.009CrossRefGoogle ScholarPubMed
Henschel, A., Hortensius, R., & Cross, E. S. (2020). Social cognition in the age of human–robot interaction. Trends in Neurosciences, 43(6), 373–384. https://doi.org/10.1016/j.tins.2020.03.013CrossRefGoogle ScholarPubMed
Hortensius, R., & Cross, E. S. (2018). From automata to animate beings: The scope and limits of attributing socialness to artificial agents. Annals of the New York Academy of Sciences, 1426(1), 93–110. https://doi.org/10.1111/nyas.13727CrossRefGoogle Scholar
Hortensius, R., Hekele, F., & Cross, E. S. (2018). The perception of emotion in artificial agents. IEEE Transactions on Cognitive and Developmental Systems, 1–1. https://doi.org/10.1109/TCDS.2018.2826921Google Scholar
Hortensius, R., Kent, M., Darda, K. M., Jastrzab, L., Koldewyn, K., Ramsey, R., & Cross, E. S. (2021). Exploring the relationship between anthropomorphism and theory-of-mind in brain and behaviour. Human Brain Mapping, 42(13), 4224–4241. https://doi.org/10.1002/hbm.25542CrossRefGoogle ScholarPubMed
Li, Z., Terfurth, L., Woller, J. P., & Wiese, E. (2022). Mind the Machines: Applying Implicit Measures of Mind Perception in Social Robotics. Proceedings of the 2022 ACM/IEEE International Conference on Human–Robot Interaction, Sapporo, Hokkaido, Japan, pp. 236–245.CrossRefGoogle Scholar
Özdem, C., Wiese, E., Wykowska, A., Müller, H., Brass, M., & Overwalle, F. V. (2017). Believing androids – fMRI activation in the right temporo-parietal junction is modulated by ascribing intentions to non-human agents. Social Neuroscience, 12(5), 582–593. https://doi.org/10.1080/17470919.2016.1207702CrossRefGoogle ScholarPubMed
Tahiroglu, D., & Taylor, M. (2019). Anthropomorphism, social understanding, and imaginary companions. British Journal of Developmental Psychology, 37(2), 284–299. https://doi.org/10.1111/bjdp.12272CrossRefGoogle ScholarPubMed
Teufel, C., Fletcher, P. C., & Davis, G. (2010). Seeing other minds: Attributed mental states influence perception. Trends in Cognitive Sciences, 14(8), 376–382. https://doi.org/10.1016/j.tics.2010.05.005CrossRefGoogle ScholarPubMed
Waytz, A., Gray, K., Epley, N., & Wegner, D. M. (2010). Causes and consequences of mind perception. Trends in Cognitive Sciences, 14(8), 383–388. https://doi.org/10.1016/j.tics.2010.05.006CrossRefGoogle ScholarPubMed
Wiese, E., Metta, G., & Wykowska, A. (2017). Robots as intentional agents: Using neuroscientific methods to make robots appear more social. Frontiers in Psychology, 8, 1663. https://doi.org/10.3389/fpsyg.2017.01663CrossRefGoogle ScholarPubMed
Wykowska, A., Chaminade, T., & Cheng, G. (2016). Embodied artificial agents for understanding human social cognition. Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1693), 20150375. https://doi.org/10.1098/rstb.2015.0375CrossRefGoogle ScholarPubMed
Wykowska, A., Wiese, E., Prosser, A., & Müller, H. J. (2014). Beliefs about the minds of others influence how we process sensory information. PLoS ONE, 9(4), e94339. https://doi.org/10.1371/journal.pone.0094339CrossRefGoogle ScholarPubMed