Task context matters: Gender dynamics and robot abuse in task-based interactions

Abstract

As robots become increasingly embedded in social roles, concerns have emerged about gender bias and abuse in human-robot interaction (HRI). This study investigated how robot gender cues, participant gender, and task type shape abusive behavior and mind attribution toward robots. Sixty-four participants interacted with a humanoid robot presented with either masculine or feminine cues across two task contexts: equation-solving (analytical) and emotion-recognition (social). Participants could reward or punish the robot based on its performance, providing behavioral measures of praise and punishment. Results showed no effects of robot gender cues or participant gender on praise and punishment. However, task context influenced punishment, with participants punishing the robot more during the equation-solving task than during the emotion-recognition task. Mind attribution revealed a gender-alignment effect, with participants attributing more mind to robots whose gender cues matched their own. These findings suggest that task context, not robot gender cues, plays a more prominent role in shaping abusive responses in HRI, while gender alignment subtly shapes social perception. Together, the results underscore the need for context-sensitive and socially aware robot design.