ATIAS: A Model for AI Technology Acceptance, Combining the User's AI Trust and the Intention to use AI Systems
Open AccessThis interdisciplinary quantitative research study aims to investigate the potential support for theories of trust in AI systems by developing a hybrid model that combines AI ethics variables with technology acceptance model (TAM) variables. The research used surveys of large populations of decision-makers to collect data on their levels of trust in AI and their intentions to choose and use AI systems. The study focused on the healthcare domain, where AI is increasingly being used. The hybrid model, called ATIAS (AI Trust and Intention to use AI Systems), will be used to examine the impact of known technology acceptance factors and AI ethical factors on users' trust in and positive attitudes toward AI. The study used Partial Least Squares Structural Equation Modeling (PLS-SEM) as the data analysis method. The study aims to address the gap in the current research on human trust in AI systems, which tends to focus on either ethical factors or technology acceptance factors. By combining both types of factors in a hybrid model, the study hopes to provide a more comprehensive understanding of why people intend to use AI systems. The research will be valuable for policymakers, AI system designers, and healthcare providers who are interested in understanding the factors that influence users' trust in AI systems. By identifying the factors (fairness, privacy, explainability, usefulness, and ease of use) that are most important in shaping users' attitudes toward AI, the study can inform the development of more effective AI systems that are trusted and accepted by users.
- All rights reserved
Notice to Authors
If you are the author of this work and you have any questions about the information on this page, please use the Contact form to get in touch with us.