Institute of Sociological Sciences, Faculty of Social Sciences, The John Paul II Catholic University of Lublin, al. Raclawickie 14, 20-950, Lublin, Poland.
Sci Rep. 2024 Nov 20;14(1):28776. doi: 10.1038/s41598-024-80305-5.
The article aims to determine the sociodemographic factors associated with the level of trust in artificial intelligence (AI) based on cross-sectional research conducted in late 2023 and early 2024 on a sample of 2098 students in Poland (1088) and the United Kingdom (1010). In the times of AI progressively penetrating people's everyday life, it is important to identify the sociodemographic predictors of trust in this increasingly dynamically developing technology. The theoretical framework for the article is the extended Unified Theory of Acceptance and Use of Technology (UTAUT), which highlights the significance of sociodemographic variables as predictors of trust in AI. We performed a multivariate ANOVA and regression analysis, comparing trust in AI between students from Poland and the UK to identify the significant predictors of trust in this technology. The significant predictors of trust were nationality, gender, length of study, place of study, religious practices, and religious development. There is a need for research into the sociodemographic factors of trust in AI and for expanding the UTAUT to include new variables.
本文旨在通过 2023 年末至 2024 年初在波兰（1088 人）和英国（1010 人）的 2098 名学生样本中进行的横断面研究，确定与对人工智能（AI）的信任水平相关的社会人口因素。在 AI 逐渐渗透到人们日常生活的时代，确定信任这种日益动态发展的技术的社会人口预测因素非常重要。本文的理论框架是扩展的接受和使用技术的统一理论（UTAUT），该理论强调了社会人口变量作为 AI 信任预测因素的重要性。我们进行了多元方差分析和回归分析，比较了来自波兰和英国的学生对 AI 的信任，以确定信任这种技术的显著预测因素。信任的显著预测因素是国籍、性别、学习时间、学习地点、宗教实践和宗教发展。需要对 AI 信任的社会人口因素进行研究，并将 UTAUT 扩展到包括新的变量。
