How voice and helpfulness shape perceptions in human–agent teams

摘要

Voice assistants are increasingly prevalent, from personal devices to team environments. This study explores how voice type and contribution quality influence human-agent team performance and perceptions of anthropomorphism, animacy, intelligence, and trustworthiness. By manipulating both, we reveal mechanisms of perception and clarify ambiguity in previous work. Our results show that the human resemblance of a voice assistant’s voice negatively interacts with the helpfulness of an agent’s contribution to flip its effect on perceived anthropomorphism and perceived animacy. This means human teammates interpret the agent’s contributions differently depending on its voice. Our study found no significant effect of voice on perceived intelligence, trustworthiness, or team performance. We find differences in these measures are caused by manipulating the helpfulness of an agent. These findings suggest that function matters more than form when designing agents for high-performing human-agent teams, but controlling perceptions of anthropomorphism and animacy can be unpredictable even with high human resemblance. • Unhelpful human-like agents seem more human than helpful human-like agents. The opposite is true for robotic-voiced agents. • Contribution quality affects team performance at 75% task completion, not task end. This suggests adaptation to bad advice. • An agent’s voice type does not impact perceived intelligence or trust. These are influenced by contribution quality alone.