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Effects of country and individual factors on public acceptance of artificial intelligence and robotics technologies: a multilevel SEM analysis of 28-country survey data
Behaviour & Information Technology ( IF 3.7 ) Pub Date : 2021-02-07 , DOI: 10.1080/0144929x.2021.1884288
Hong Tien Vu 1 , Jeongsub Lim 2
Affiliation  

ABSTRACT

Using data from 28 European countries, this study examines factors influencing public attitude towards the use of AI/Robot. Its multilevel SEM analysis finds that several factors at the individual level including Perceived threat of job loss and Digital technology efficacy predict public Acceptance of AI/Robot. Although country-level factors such as economic development, government effectiveness and innovation do not directly influence public acceptance of AI/Robot, they do have significant effects on Perceived threat of general job loss due to AI/Robot, and Digital technology efficacy. Findings indicate that these nationally macro variables influence people’s perceptions of AI and robotics technologies and their confidence in their digital skills. This research enriches the application of the Technology Acceptance Model by using predictive variables at two levels: individual and country. Furthermore, at the individual level, this study uses two variables (e.g. Perceived threat of job loss and Digital technology efficacy) that are unconventional to TAM, thus contributing to this theoretical model.



中文翻译:

国家和个人因素对公众接受人工智能和机器人技术的影响:28 个国家调查数据的多层次 SEM 分析

摘要

本研究使用来自 28 个欧洲国家的数据,考察了影响公众对使用人工智能/机器人的态度的因素。其多级 SEM 分析发现,个人层面的几个因素,包括感知到的失业威胁数字技术效能,可以预测公众对人工智能/机器人的接受程度。尽管经济发展、政府效率和创新等国家层面的因素不会直接影响公众对人工智能/机器人的接受程度,但它们确实对人工智能/机器人造成的普遍失业威胁数字技术效能有显着影响. 调查结果表明,这些国家宏观变量会影响人们对人工智能和机器人技术的看法以及他们对数字技能的信心。本研究通过在个人和国家两个层面使用预测变量,丰富了技术接受模型的应用。此外,在个人层面,本研究使用了对 TAM 非常规的两个变量(例如,感知的失业威胁数字技术效能),从而促成了这一理论模型。

更新日期:2021-02-07
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