The Persistence of First Impressions: The Effect of Repeated Interactions on the Perception of a Social Robot
Abstract
Numerous studies in social psychology have shown that familiarization across repeated interactions improves people's perception of the other. If and how these findings relate to human-robot interaction (HRI) is not well understood, even though such knowledge is crucial when pursuing long-term interactions. In our work, we investigate the persistence of first impressions by asking 49 participants to play a geography game with a robot. We measure how their perception of the robot changes over three sessions with three to ten days of zero exposure in between. Our results show that different perceptual dimensions stabilize within different time frames, with the robot's competence being the fastest to stabilize and perceived threat the most fluctuating over time. We also found evidence that perceptual differences between robots with varying levels of humanlikeness persist across repeated interactions. This study has important implications for HRI design as it sheds new light on the influence of robots' embodiment and interaction abilities. Moreover, it also impacts HRI theory as it presents novel findings contributing to research on the uncanny valley and robot perception in general.
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In educational scenarios, entrainment is an indicator for better learning outcomes and mutual understanding.
“In educational scenarios, entrainment has been identified as an indicator for better learning outcomes and mutual understanding [128].”
From A Taxonomy of Social Errors in Human-Robot Interaction (2021) · cites this paper as [128]
Cites
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“Before their first encounter with the robot, participants filled out questionnaire (Q1) covering their demographics, personality traits [48], and negative attitude towards robots (NARS) [42].”
BackgroundExposure and affect: Overview and meta-analysis of research, 1968–1987.
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Social Robots for Long-Term Interaction: A Survey
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“peated interactions with multiple days of zero exposure in between, instead of multiple measurements within one interaction session [10][23][44][60].”
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A Taxonomy of Social Errors in Human-Robot Interaction
Tian, L., & Oviatt, S. (2021) · ACM Transactions on Human-Robot Interaction · doi:10.1145/3439720 · Cited by 133 · see citing works
Lee, C. P., Cagiltay, B., & Mutlu, B. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3501955 · Cited by 46 · see citing works
- Authors
- Paetzel, M., Perugia, G., & Castellano, G.
- Affiliations
- Uppsala University (SE)
- Venue
- Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction
- Publisher
- ACM
- Published
- 2020-03-09
- Pages
- 73-82
- OpenAlex
- W3010164621
- Cited by
- 99
- References
- 7
- Citations by year
- 2026: 11 · 2025: 20 · 2024: 15 · 2023: 16 · 2022: 18 · 2021: 15 · 2020: 4
- FWCI
- 18.69
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM/IEEE International Conference on Human-Robot Interaction (HRI) (publishedVersion)
- Funders
- Stiftelsen för Strategisk Forskning (RIT15-0133)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- first impressions, human-robot interaction, familiarity, repeated interaction, robot competence, threat perception, human-likeness, embodiment, uncanny valley, long-term interaction, robot perception
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