Trusting a Virtual Driver That Looks, Acts, and Thinks Like You

Abstract

Objective: We examined whether participants would trust an agent that was similar to them more than an agent that was dissimilar to them.

Background: Trust is an important psychological factor determining the acceptance of smart systems. Because smart systems tend to be treated like humans, and similarity has been shown to increase trust in humans, we expected that similarity would increase trust in a virtual agent.

Methods: In a driving simulator experiment, participants (N = 111) were presented with a virtual agent that was either similar to them or not. This agent functioned as their virtual driver in a driving simulator, and trust in this agent was measured. Furthermore, we measured how trust changed with experience.

Results: Prior to experiencing the agent, the similar agent was trusted more than the dissimilar agent. This effect was mediated by perceived similarity. After experiencing the agent, the similar agent was still trusted more than the dissimilar agent.

Conclusion: Just as similarity between humans increases trust in another human, similarity also increases trust in a virtual agent. When such an agent is presented as a virtual driver in a self-driving car, it could possibly enhance the trust people have in such a car.

Application: Displaying a virtual driver that is similar to the human driver might increase trust in a self-driving car.

Keywords: facial similarity; liking; mimicry; perceived similarity; shared goals; similarity; trust; virtual agent.