Artificial Intelligence Attitudes Inventory (AIAI): Development and Validation Using Rasch Methodology

Abstract With the rapid advancements in artificial intelligence (AI), it is vital to develop psychometrically sound measures of public attitudes toward this technology. The present study aimed to refine a pool of candidate items to create a concise yet robust inventory for assessing attitudes toward AI. Using a dataset of 604 participants from the general population of the United States, a pool of 96 candidate items was subjected to iterative Rasch analysis to reduce the number of items while ensuring psychometric robustness. The resulting scale, named the Artificial Intelligence Attitudes Inventory (AIAI), consists of two 8-item subscales measuring positive and negative attitudes toward AI. Analyses revealed that these subscales are distinct constructs rather than opposites on a single continuum, and they are only weakly related to psychological distress. The AIAI provides a concise yet comprehensive measure of positive and negative attitudes toward AI that can be efficiently administered alongside other measures. The findings underscore the multifaceted nature of public perceptions of AI and highlight the need for further research into the profiles and determinants of these attitudes. As AI continues to shape our world, the AIAI offers a valuable tool for understanding and monitoring public sentiment toward this transformative technology.