Life-like humanoid robots are on the rise, aiming at communicative purposes that resemble humanlike conversation. In human social interaction, the facial expression serves important communicative functions. We examined whether a robot’s face is similarly important in human-robot communication. Based on emotion research and neuropsychological insights on the parallel processing of emotions, we argue that greater plasticity in the robot’s face elicits higher affective responsivity, more closely resembling human-to-human responsiveness than a more static face. We conducted a between-subjects experiment of 3 (facial plasticity: human vs. facially flexible robot vs. facially static robot) × 2 (treatment: affectionate vs. maltreated). Participants (N = 265; M age = 31.5) were measured for their emotional responsiveness, empathy, and attribution of feelings to the robot. Results showed empathically and emotionally less intensive responsivity toward the robots than toward the human but followed similar patterns. Significantly different intensities of feelings and attributions (e.g., pain upon maltreatment) followed facial articulacy. Theoretical implications for underlying processes in human-robot communication are discussed. We theorize that precedence of emotion and affect over cognitive reflection, which are processed in parallel, triggers the experience of ‘because I feel, I believe it’s real,’ despite being aware of communicating with a robot. By evoking emotional responsiveness, the cognitive awareness of ‘it is just a robot’ fades into the background and appears not relevant anymore.


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    Title :

    Differential facial articulacy in robots and humans elicit different levels of responsiveness, empathy, and projected feelings


    Contributors:

    Publication date :

    2020-12-01


    Remarks:

    Konijn , E A & Hoorn , J F 2020 , ' Differential facial articulacy in robots and humans elicit different levels of responsiveness, empathy, and projected feelings ' , Robotics , vol. 9 , no. 4 , 92 . https://doi.org/10.3390/robotics9040092



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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