Warmth and Competence in the Swarm: Designing Effective Human-Robot Teams

2026-04-21

AI Summary

This study investigates how humans perceive the social attributes of robot swarms to inform the design of human–robot collaborative teams. Drawing on the competence–warmth framework from social psychology, two behavioral manipulation experiments examine differences in perceived warmth and competence when human participants act as either observers or operators in a collaborative search task with robot groups. This work is the first to systematically apply this social cognition framework to swarm–human interaction, revealing that longer broadcast durations enhance perceived warmth, larger inter-agent spacing increases perceived competence, and speed exhibits no significant effect. Teams exhibiting both high warmth and high competence are most preferred by participants. Notably, social perception proves a stronger predictor of team preference than objective task performance, offering novel insights for designing human-centered collaborative systems involving robot swarms.

Technology Category

• Humans and AI: Teamwork, Team formation
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Intelligent Robots: Human-Robot Interaction

Application Category

• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

As groups of robots increasingly collaborate with humans, understanding how humans perceive them is critical for designing effective human-robot teams. While prior research examined how humans interpret and evaluate the abilities and intentions of individual agents, social perception of robot teams remains relatively underexplored. Drawing on the competence-warmth framework, we conducted two studies manipulating swarm behaviors in completing a collective search task and measured the social perception of swarm behaviors when human participants are either observers (Study 1) and operators (Study 2). Across both studies, our results show that variations in swarm behaviors consistently influenced participants' perceptions of warmth and competence. Notably, longer broadcast durations increased perceived warmth; larger separation distances increased perceived competence. Interestingly, individual robot speed had no effect on either of the perceptions. Furthermore, our results show that these social perceptions predicted participants' team preferences more strongly than task performance. Participants preferred robot teams that were both warm and competent, not those that completed tasks most quickly. These findings demonstrate that human-robot interaction dynamically shapes social perception, underscoring the importance of integrating both technical and social considerations when designing robot swarms for effective human-robot collaboration.

Problem

• human-robot teams
• social perception
• warmth
• competence
• swarm robotics

Innovation

• swarm robotics
• social perception
• warmth-competence framework
• human-robot collaboration
• team preference