Impact of anthropomorphism in AI assistants’ verbal feedback on task performance and emotional experience
Shuhan Yang, Yanqun Huang, Xueqin Huang, Jian Zhang, Ziping Meng, Junyu Yang · Ergonomics · 2025
Artificial intelligence (AI) assistants are increasingly deployed across various fields to replace human operators in providing feedback to users, making anthropomorphism a pivotal topic in AI-assisted interactions. We investigated the impact of varying degrees of anthropomorphism in verbal feedback on task performance and user experience. A total of 30 participants were recruited, and their task performance and subjective experiences in response to different levels of feedback were measured. Moderate-level anthropomorphic verbal feedback elicited significantly lower self-efficacy and pleasure compared to high- and low- level feedback. Notably, under high-level feedback, participants demonstrated a significant increase in response speed compared to lower levels. These findings suggested that high-level feedback of AI assistants could enhance participants' performance and experience, thereby improving training or learning efficacy. However, moderate-level anthropomorphic feedback appeared to be less effective. The study outcomes could offer insights for future research and design of AI voice systems.