规则网络
判别效度
结构效度
可靠性(半导体)
比例(比率)
收敛有效性
心理学
构造(python库)
数据科学
增量有效性
计算机科学
人工智能
样品(材料)
焦虑
心理测量学
机器学习
结构方程建模
发展心理学
化学
功率(物理)
程序设计语言
物理
精神科
量子力学
色谱法
内部一致性
作者
Yuyin Wang,Yi‐Shun Wang
标识
DOI:10.1080/10494820.2019.1674887
摘要
While increasing productivity and economic growth, the application of artificial intelligence (AI) may ultimately require millions of people around the world to change careers or improve their skills. These disruptive effects contribute to the general public anxiety toward AI development. Despite the rising levels of AI anxiety (AIA) in recent decades, no AI anxiety scale (AIAS) has been developed. Given the limited utility of existing self-report instruments in measuring AIA, the aim of this paper is to develop a standardized tool to measure this phenomenon. Specifically, this paper introduces and defines the construct of AIA, develops a generic AIAS, and discusses the theoretical and practical applications of the instrument. The procedures used to conceptualize the survey, create the measurement items, collect data, and validate the multi-item scale are described. By analyzing data obtained from a sample of 301 respondents, the reliability, criterion-related validity, content validity, discriminant validity, convergent validity, and nomological validity of the constructs and relationships are fully examined. Overall, this empirically validated instrument advances scholarly knowledge regarding AIA and its associated behaviors.
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