Does Trustworthy AI Motivate Generative AI Usage?

Due to growing concerns about the risks associated with artificial intelligence (AI), interest in trustworthy AI (TAI) has amplified. Currently, few empirical studies investigate (a) whether TAI factors indeed encourage individuals to increase their usage of Generative AI (GenAI), compared to motivators such as those identified in the Unified Theory of Acceptance and Use of Technology (UTAUT) and (b) whether users’ levels of motivation from specific TAI and UTAUT factors vary with their GenAI usage types (e.g., obtaining answers, assisting with writing). Such research focusing specifically on Asia-Pacific nations, such as Singapore, is even rarer. This study thus conducted an online survey of 300 adults in Singapore to explore the two research gaps above. Data were analyzed using descriptive and inferential statistics (multiple regressions). The study found “Effort Expectancy” and “Performance Expectancy” (both from UTAUT) to be the top motivators for GenAI usage, followed by the “Technical Robustness and Safety” TAI. Significant associations were observed between types of GenAI usage and motivation levels from different TAI and UTAUT factors. For instance, using GenAI “to get answers” was correlated with being motivated to increase GenAI usage by “Technical Robustness and Safety”, and using GenAI “to solve problems” was associated with being encouraged by the “Human Agency and Oversight” TAI. Among the demographic variables, education yielded the most statistically significant associations (five out of 11). The implications for AI governance, system design, and stakeholder engagement and training are discussed.