Beyond human-likeness: Socialness is more influential when attributing mental states to robots
Research output: Contribution to journal › Article › peer-review
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- PIIS2589004224012951
Accepted author manuscript, 5.68 MB, PDF document
- 1-s2.0-S2589004224012951-main
Final published version, 2.85 MB, PDF document
Licence: CC BY Show licence
DOI
We sought to replicate and expand previous work showing that the more human-like a robot appears, the more willing people are to attribute mind-like capabilities and socially engage with it. Forty-two participants played games against a human, a humanoid robot, a mechanoid robot, and a computer algorithm while undergoing functional neuroimaging. We confirmed that the more human-like the agent, the more participants attributed a mind to them. However, exploratory analyses revealed that the perceived socialness of an agent appeared to be as, if not more, important for mind attribution. Our findings suggest top-down knowledge cues may be equally or possibly more influential than bottom-up stimulus cues when exploring mind attribution in non-human agents. While further work is now required to test this hypothesis directly, these preliminary findings hold important implications for robotic design and to understand and test the flexibility of human social cognition when people engage with artificial agents
Keywords
- social neuroscience, social robotics, second-person neuroscience, social cognition, Mentalizing
Original language | English |
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Article number | 110070 |
Journal | iScience |
Volume | 27 |
Issue number | 6 |
Early online date | 22 May 2024 |
DOIs | |
Publication status | Published - 21 Jun 2024 |
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