Exploring factors affecting user intention to accept explainable artificial intelligence

Explainable Artificial intelligence (XAI) represents a pivotal innovation aimed at addressing the ?black box? problem in AI, thereby enhancing users? understanding of AI reasoning processes and outcomes. The implementation of XAI is not merely a technological endeavor but also involves various individual factors. As XAI remains in its early developmental stages and exhibits unique characteristics, identifying and understanding the factors influencing users? intention to adopt XAI is essential for its long-term success. This study develops a research model grounded in the characteristics of XAI and prior technology acceptance studies that consider individual factors. The model was evaluated using data collected from 252 potential XAI users. The validated model exhibits strong explanatory power, accounting for 45% of the variance in users? intention to use XAI. Findings indicate that perceived value and perceived need are key determinants of users' intention to adopt XAI. These results provide empirical evidence and deepen the understanding of user perceptions and intentions regarding XAI adoption.