The Influence of Social Cues and Controlling Language on Agent's Expertise, Sociability, and Trustworthiness

For optimal human-robot interaction, understanding the determinants and components of anthropomorphism is crucial. This research assessed the influence of an agent's social cues and controlling language use on user's perceptions of the agent's expertise, sociability, and trustworthiness. In a game context, the agent attempted to persuade users to modify their choices using high or low controlling language and using different levels of social cues (advice with text-only with no robot embodiment as the agent, a robot with elementary social cues, and a robot with advanced social cues). As expected, low controlling language lead to higher perceived anthropomorphism, while the robotic agent with the most social cues was selected as the most expert advisor and the non-social agent as the most trusted advisor.