Department of Industrial Engineering, Kumoh National Institute of Technology, South Korea.
Hum Factors. 2024 Jan;66(1):126-144. doi: 10.1177/00187208211064707. Epub 2022 Mar 28.
The study aimed to provide a comprehensive overview of the factors impacting technology adoption, to predict the acceptance of artificial intelligence (AI)-based technologies.
Although the acceptance of AI devices is usually defined by behavioural factors in theories of user acceptance, the effects of technical and human factors are often overlooked. However, research shows that user behaviour can vary depending on a system's technical characteristics and differences in users.
A systematic review was conducted. A total of 85 peer-reviewed journal articles that met the inclusion criteria and provided information on the factors influencing the adoption of AI devices were selected for the analysis.
Research on the adoption of AI devices shows that users' attitudes, trust and perceptions about the technology can be improved by increasing transparency, compatibility, and reliability, and simplifying tasks. Moreover, technological factors are also important for reducing issues related to human factors (e.g. distrust, scepticism, inexperience) and supporting users with lower intention to use and lower trust in AI-infused systems.
As prior research has confirmed the interrelationship among factors with and without behaviour theories, this review suggests extending the technology acceptance model that integrates the factors studied in this review to define the acceptance of AI devices across different application areas. However, further research is needed to collect more data and validate the study's findings.
A comprehensive overview of factors influencing the acceptance of AI devices could help researchers and practitioners evaluate user behaviour when adopting new technologies.
本研究旨在全面概述影响技术采用的因素,以预测人工智能 (AI) 技术的接受程度。
尽管用户接受理论通常将 AI 设备的接受程度定义为行为因素,但技术和人为因素的影响往往被忽视。然而,研究表明,用户行为可能因系统的技术特征和用户的差异而有所不同。
进行了系统综述。共选择了 85 篇符合纳入标准并提供有关影响 AI 设备采用因素信息的同行评审期刊文章进行分析。
对 AI 设备采用的研究表明,通过提高透明度、兼容性和可靠性以及简化任务,可以改善用户对技术的态度、信任和认知。此外,技术因素对于减少与人为因素相关的问题(例如不信任、怀疑、缺乏经验)也很重要,并为意图使用和信任 AI 注入系统较低的用户提供支持。
由于先前的研究已经证实了具有和不具有行为理论的因素之间的相互关系,因此本综述建议扩展包含本综述中研究因素的技术接受模型,以定义在不同应用领域中对 AI 设备的接受程度。然而,需要进一步研究以收集更多数据并验证研究结果。
全面概述影响 AI 设备接受程度的因素可以帮助研究人员和从业者评估采用新技术时的用户行为。