Qualitative analysis reveals future factory workers prefer robots without emotional displays, suggesting design improvements in human-robot interaction.
Collaborative robots (cobots) and AI technologies are increasingly adopted in industrial settings to enhance productivity and efficiency. While cobots equipped with AI capabilities can enable more collaborative work between people and machines, they also face worker acceptance challenges. Understanding future workers’ perceptions, attitudes, and experiences with cobots and conversational AIs can inform robot designers and developers to design systems that promote collaboration, trust, and acceptance. In this study, we gathered quantitative and qualitative data from 37 participants enrolled in a vocational training program for industrial factory workers, who interacted with an AI-empowered, voice-enabled cobot during a simulated smart factory assembly task and visited an art exhibition featuring industrial robots and cobots. While these participants are not currently employed in factories, they are considered proxy users –individuals with relevant domain knowledge and training who represent future factory workers. The art exhibition functioned as a design probe to illicit discussion and prompt critical reflection about automation and the role of artificial emotions in HRI. The smart factory task offered participants a concrete example of how AI-empowered virtual assistants might be combined with cobots on the factory floor. In contrast with some of the HRI literature, participants expressed a strong preference for robots without emotional displays and social behaviors, challenging the view that anthropomorphism and human-like emotions promote robot acceptance. Based on our study, we propose design recommendations for developing AI-empowered, voice-enabled cobots based on five themes generated from the qualitative data.
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Nielsen et al. (2025) studied this question.
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