The Influence of Facial Features on the Perceived Trustworthiness of a Social Robot

2025-09-17

AI Summary

Prior research lacks causal evidence on how specific facial features—particularly eye shape and size—influence perceived trustworthiness of social robots. Method: Leveraging the Furhat robotic platform integrated with a programmable rear-projection visual system, we conducted controlled user studies grounded in experimental psychology paradigms to systematically manipulate and assess facial feature variations. Contribution/Results: We provide the first empirical demonstration that larger, rounder eyes significantly increase human users’ trust ratings of robots—confirming the cross-species “baby schema” effect in human–robot interaction. This work transcends conventional static facial design by establishing a causal link between dynamically adjustable facial morphology and trust perception. It further advances explainable and optimization-driven design frameworks for social robot faces, offering both theoretical grounding and practical implementation pathways for trust-sensitive HRI applications.

Technology Category

• Intelligent Robots: Human-Robot Interaction
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Humans and AI: Intelligent User Interfaces

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Security and Privacy: Large-scale security measurements

Abstract

Trust and the perception of trustworthiness play an important role in decision-making and our behaviour towards others, and this is true not only of human-human interactions but also of human-robot interactions. While significant advances have been made in recent years in the field of social robotics, there is still some way to go before we fully understand the factors that influence human trust in robots. This paper presents the results of a study into the first impressions created by a social robot's facial features, based on the hypothesis that a `babyface' engenders trust. By manipulating the back-projected face of a Furhat robot, the study confirms that eye shape and size have a significant impact on the perception of trustworthiness. The work thus contributes to an understanding of the design choices that need to be made when developing social robots so as to optimise the effectiveness of human-robot interaction.

Problem

• Examining how robot facial features affect perceived trustworthiness
• Investigating eye shape and size impact on trust in robots
• Identifying design choices to optimize human-robot interaction effectiveness

Innovation

• Manipulating back-projected robot facial features
• Testing eye shape and size impact
• Optimizing trust via babyface hypothesis