Abstract Summary/Description
Generative artificial intelligence (GenAI) is a type of computer program that can generate new content such as text, images, or music, mimicking human creativity (e.g., ChatGPT). Despite frequent commentary on the topic in social and news media, there are few scales developed and validated to measure public attitudes on GenAI. It is important to understand public attitudes on GenAI because this can guide policy and regulation and inform better GenAI designs and implementation. Based on current literature, 79 survey items were created to measure the public’s attitudes, perceptions, and emotions toward GenAI. A convenience sample of 305 respondents was recruited online to complete the questionnaire. For this project’s aims, only the first scale, which contains 19 items reflecting participants’ attitudes toward using GenAI, was analyzed. Exploratory factor analysis was conducted to identify possible subscales of GenAI attitudes. A 3-factor model was selected to yield the most practical and meaningful estimation. The three factors were identified as acceptance of GenAI, impressiveness of GenAI, and concerns about GenAI. All three factors showed good internal validity. Validity testing for the scale was performed using previously validated scales for psychological stress (K6), attitudes about AI more broadly (AIAS-4), and dispositional optimism (LOT-R). Confirmatory factor analysis (CFA) showed acceptable discriminant validity, excellent concurrent validity, and very poor convergent validity. Limitations and future research directions are discussed.
