The Valley Of Non Distraction Effect Of Robots Human Likeness On Perception Load

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title: “The Valley of non-Distraction: Effect of Robot's Human-likeness on Perception Load” collection: publications permalink: /publication/2021-01-01-The-Valley-of-non-Distraction-Effect-of-Robots-Human-likeness-on-Perception-Load date: 2021-01-01 venue: ‘In the proceedings of Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction (HRI '21 Companion), March 8–11, 2021, Boulder,CO, USA’ citation: ‘ Daisy Ingle, Nadine Marcus, Wafa Johal, "The Valley of non-Distraction: Effect of Robot's Human-likeness on Perception Load." In the proceedings of Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction (HRI '21 Companion), March 8–11, 2021, Boulder,CO, USA, 2021.’ —Abstract:”Previous research in psychology has found that human faces have the capability of being more distracting under high perceptual load conditions compared to non-face objects. This project aims to assess the distracting potential of robot faces based on their human-likeliness. As a first step, this paper reports on our initial findings based on an online study. We used a letter search task where participants had to search for a target letter within a circle of 6 letters, whilst an irrelevant distractor image was also present. The results of our experiment replicated previous results with human faces and non-face objects. Additionally, in the tasks where the irrelevant distractors are images of robot faces, the human-likeness of the robot influenced the response time (RT). Interestingly, the robot Alter produced results significantly different than all other distractor robots. The outcome of this is a distraction model related to human-likeness of robots. Our results show the impact of anthropomorphism on distracting potential and thus should be taken into account when designing robots.”