Making Robot's Attitudes Predictable: A Stereotype Content Model for Human-Robot Interaction in Groups

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This project aims to investigate how stable content dimensions of stereotypes can affect Human-Robot interaction in groups. More specifically, we focus on perceived warmth and competence as dimensions of stereotypes around which the individual organizes their perception about the other. We aim to explore how the aforementioned dimensions play a role in the individual's behavioral and emotional response to the robotic agent, as well as the effect it has on his/hers future intention to work with it. Moreover, we will explore these issues in the context of small mixed group interactions, involving more than one human and more than one robot, interacting over a card game entertaining scenario.

Oliveira, R. A., Arriaga, P., Correia, F., & Paiva, A. (2018, March 3). Making Robot's Attitudes Predictable: A Stereotype Content Model for Human-Robot Interaction in Groups. https://doi.org/10.31234/osf.io/kfzdg


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