ISSN 1671-3710
CN 11-4766/R

心理科学进展 ›› 2022, Vol. 30 ›› Issue (4): 723-737.doi: 10.3724/SP.J.1042.2022.00723

• 研究构想 • 上一篇    下一篇


邓士昌1, 许祺1, 张晶晶1, 李象千2()   

  1. 1上海对外经贸大学工商管理学院, 上海 201620
    2上海体育学院心理学院, 上海 200438
  • 收稿日期:2021-02-02 出版日期:2022-04-15 发布日期:2022-02-22
  • 通讯作者: 李象千
  • 基金资助:

User acceptance mechanism and usage promotion strategy of AI services based on mind perception theory

DENG Shichang1, XU Qi1, ZHANG Jingjing1, LI Xiangqian2()   

  1. 1Management School, Shanghai University of International Business and Economics, Shanghai 201620, China
    2School of Psychology, Shanghai University of Sports, Shanghai 200438, China
  • Received:2021-02-02 Online:2022-04-15 Published:2022-02-22
  • Contact: LI Xiangqian


许多企业采用人工智能服务应答顾客需求, 然而多项研究指出用户并不总是对此感到满意。本研究围绕着用户对AI的心灵知觉的产生和影响, 探索了驱动用户对AI服务态度的关键因素及使用促进策略, 包括(1)机理分析层面:用户与AI早期接触的线索和体验因素如何使得人们产生了AI“擅长计算却缺乏感受”的心灵知觉?(2)调节作用层面:不同的用户内部状态和AI外部特征怎样调节了这种心灵知觉的形成和激活?(3)促进策略层面:将AI拟动物化和提供技术援助为何能借助心灵知觉使得用户在更广泛的场景中接受来自AI的服务?本研究试图在学理层面构建一个基于心灵知觉理论的新型AI服务接受模型, 为从理论上解释用户对AI服务的矛盾态度提供心理学参考; 同时试图在实践层面上借助心灵知觉理论提出两种促进用户接受AI服务的路径方法, 为企业在服务中提升AI的应用效能提供技术参考。

关键词: 人工智能, 心灵知觉, 客户服务, 刻板印象, 热情


Many enterprises have adopted AI services to respond to customer needs, yet several studies indicate that users are not always satisfied with AI in service. This study explores the key factors that drive users' attitudes toward AI services and usage promotion strategies based on the generation and influence of users' mind perceptions of AI, which including

(1) Mechanism analysis: How do the cues and experiential factors of users' early contact with AI lead to the perception that AI is “good at computing but not feeling”? This study argues that past frustrations with AI in emotional-social service scenarios and mass media portrayals of AI as “highly intelligent and low in emotional intelligence” have led users to develop the perception that AI is good at computation but lacks feelings. This makes users willing to use AI for functional purposes only in cognitive-analytical tasks, but not like to establish empathic connections with AI in emotional-social tasks.

(2) Moderating effects: How do different internal user states and external AI features moderate the formation and activation of this mind perception toward AI? This study believes that higher frequency of AI use and technology use self-efficacy make individuals more likely to establish para-friendship relationships with AI, those two factors that inhibit the formation of mind perceptions that users believe AI is good at computing but lacks feeling. On the other hand, the degree of anthropomorphism and the degree of flexibility in the task influenced individuals' cognitive cues to AI, those two factors that inhibit the activation of the user's mind perception toward AI.

(3) Facilitation strategies: With the reverse utilization of mind perception, how can the mimicry of AI as warmth animals and the provision of technical assistance enable users to accept services from AI in a wider range of scenarios? This study proposes that by designing an information framework that demonstrates the computational power of AI and at the same time, mimics AI as an animal with “high warmth” quality, it can reconcile the paradox of “AI is good at computation but lacks feeling” and promote the user's perception of AI's empathic ability. This will increase users' willingness to use AI in emotional-social tasks. On the other hand, providing users with tips and technical assistance when interacting with AI can help build a joint interaction model between AI and humans, reduce users' concerns about AI's lack of empathic capacity, and increase people's willingness to use AI in emotional-social tasks.

This study attempts to construct a new model of AI service acceptance based on the theory of mind perception at the theoretical level and provide a psychological reference for theoretically explaining users' ambivalent attitudes toward AI services. At the practical level, this study attempts to propose two pathways to facilitate users' acceptance of AI services with the help of mind perception theory and provide a technical reference for enterprises to enhance the effectiveness of AI applications in their service processes.

Key words: artificial intelligence, mind perception, customer service, stereotype, warmth