The Impact of Anthropomorphism on Trust in Human-Robot Interaction
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The Impact of Anthropomorphism on Trust in Human-Robot Interaction


Automated systems are becoming increasingly more prominent in our lives. As this continues to happen, we see more interactions between humans and machines in a wider variety of contexts. This raises questions about the extent to which interactions between humans and machines will translate to interactions between humans, and how robots can be designed aesthetically to facilitate those interactions. I was interested in exploring how a robot’s physical appearance might influence people’s attitudes towards human-robot interaction, and particularly how much people would trust a given robot with certain tasks. Established literature on the subject points to many potential determinants of such attitudes, but I was primarily interested in three: anthropomorphism of a robot, gender presentation of robot, and racial presentation of the robot. To explore these determinants, I conducted a series of experiments in which I presented participants with videos of robots with differing levels of human resemblance, different gender presentations, and different racial presentations in online surveys. Each video would comprise a robot assuming the fictional role of a household caretaker giving a brief speech to the viewer about its capabilities. Participants then answered a series of questions about how much they would trust the robot in their homes performing such tasks, and they would then rate their perceptions of the robot along a variety of criteria such as how likable or how intelligent they perceived the robot to be, all on a series of Likert scales. I conducted two sets of these studies: one in which the robots assigned to participants differed based on level of anthropomorphism and male or female gender presentation, and another in which the assigned robots differed based on level of anthropomorphism and white or Black racial presentation. The results of these experiments broadly indicated that anthropomorphism at extreme levels significantly influenced trust in the robots as well as perceptions of them, while gender and racial variations did not. The data also demonstrated strong correlations between the trust metrics and perceptual appraisals that I used, potentially suggesting that such metrics are reliable indicators of attitudes towards robots. This dissertation, The Impact of Anthropomorphism on Trust in Human-Robot Interaction, is submitted by Umesh Krishnamurthy in 2021 in partial fulfillment of the degree Doctor of Philosophy in Cognitive and Information Sciences at the University of California, Merced under the guidance of dissertation committee chair Paul Maglio.

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