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The Valley of non-Distraction: Effect of Robot's Human-likeness on Perception Load

Daisy Ingle, Nadine Marcus, Wafa Johal

Year
2021
Citations
2

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.

Keywords

DistractionRobotPerceptionTask (project management)Face (sociological concept)Computer scienceHuman–robot interactionArtificial intelligencePsychologyHuman–computer interaction

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