An economical measure of attitudes towards artificial intelligence in work, healthcare, and education (ATTARI-WHE) - Timo Gnambs; Jan-Philipp Stein; Markus Appel; Florian Griese; Sabine Zinn (Computers in Human Behavior: Artificial Humans)
Artificial intelligence (AI) has profoundly transformed numerous facets of both private and professional life. Understanding how people evaluate AI is crucial for predicting its future adoption and addressing potential barriers. However, existing instruments measuring attitudes towards AI often focus on specific technologies or cross-domain evaluations, while domain-specific measurement instruments are scarce. Therefore, this study introduces the nine-item Attitudes towards Artificial Intelligence in Work, Healthcare, and Education (ATTARI-WHE) scale. Using a diverse sample of N = 1083 respondents from Germany, the psychometric properties of the instrument were evaluated. The results demonstrated low rates of missing responses, minimal response biases, and a robust measurement model that was invariant across sex, age, education, and employment status. These findings support the use of the ATTARI-WHE to assess AI attitudes in the work, healthcare, and education domains, with three items each. Its brevity makes it particularly well-suited for use in social surveys, web-based studies, or longitudinal research where assessment time is limited.