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Semi‐Human Artificial Intelligence: The Effect of Search Modality (Text vs. Voice) on Perceived Eeriness and Consumers' Purchase Intention

模态(人机交互) 心理学 社会心理学 认知心理学 计算机科学 人工智能
作者
Atieh Poushneh,Richard Gearhart
出处
期刊:Journal of Consumer Behaviour [Wiley]
标识
DOI:10.1002/cb.2496
摘要

ABSTRACT Advances in artificial intelligence (AI) have changed the relationships between humans and machines. AI can exhibit human‐like characteristics in its behavior, prompting humans to view it as a semi‐human. Companies embed humanlike traits in AI to facilitate interaction with consumers. As humanlike traits in AI increase, people may perceive it as eerie. Yet, there is no consensus on the effect of search modalities (text vs. voice) on humanlike traits in AI. In addition, it is not clear which humanlike traits in AI influence eeriness and purchase intention. To address the gaps, we utilized anthropomorphism theory and human psychological needs to identify why people perceive more autonomy, competence, and social presence in voice‐based AI compared with text‐based AI. We employed a quasi‐experiment (one group) consisting of 385 participants, and two experiments: pretest 2 consisted of 130 participants (two groups: experimental and control groups) and the main experiment consisted of 528 participants (two groups: experimental and control groups). We used Amazon Mechanical Turk and recruited participants in the USA who completed between 500 to 1000 HITS with a 90% approval rate. Results reveal that voice searching in AI evokes greater autonomy, competence, and social presence. Utilizing the uncanny valley effect, results showed that perceived competence lowers perceived eeriness and thereby enhances purchase intention. Although social presence enhances perceived eeriness, it increases purchase intention. In addition, perceived autonomy triggers eeriness, yet it increases consumers' purchase intention for low‐involvement products. Additionally, we examined the interaction effects of self‐construal and autonomy, competence, and social presence on eeriness. We also suggest practical implications for AI developers and research limitations, and directions for future research.
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