4.6 Article

Estimating the Impact of Humanizing AI Assistants

Publisher

TAYLOR & FRANCIS INC
DOI: 10.1080/10447318.2023.2291614

Keywords

Anthropomorphism; human-AI interaction quality; smart home assistants; utilitarian; hedonic

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An increasing number of product designers are adopting anthropomorphic design strategies to enhance the use of AI assistants. However, the ideal degree of anthropomorphism is still unclear. To explore the influence of different degrees of anthropomorphism on human-AI interaction quality, we conducted two scenario experimental studies. We also considered the impact difference between hedonic and utilitarian contexts. The results show that different degrees of anthropomorphism significantly affect human-AI interaction quality in different ways, with a pronounced positive effect observed when AI assistants have a medium-level degree of anthropomorphism. Furthermore, the positive relationship between anthropomorphism and human-AI interaction quality is more robust in the hedonic usage context, but disappears in the utilitarian usage context. This study is expected to provide practical guidance for AI product designers to ensure the long-term feasibility and sustainability of their products.
More and more product designers are adopting anthropomorphic design strategies to facilitate the widespread use of AI assistants. However, existing studies show that the ideal boundary of the degree of anthropomorphism is still unclear. Therefore, we design two scenario experimental studies to explore the influence of different degrees of anthropomorphism on human-AI interaction quality. We also consider the difference in impact between two usage contexts: the hedonic and utilitarian contexts. The results show that different degrees of anthropomorphism significantly affect human-AI interaction quality in different ways; when AI assistants have a medium-level degree of anthropomorphism, the positive effect is pronounced. Furthermore, the positive relationship between anthropomorphism and human-AI interaction quality is more robust in the hedonic usage context; this positive effect disappears in the utilitarian usage context. We expect this study to provide practical guidance for AI product designers to achieve their products' long-term feasibility and sustainability.

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