  With the widespread application of artificial intelligence(AI), the
explainable AI (XAI) field has undergone a notable resurgence. In this
background, the importance of user experience in XAI has become increasingly
prominent. Simultaneously, the user interface (UI) serves as a crucial link
between XAI and users. However, despite the existence of UI design principles
for XAI, there is a lack of prioritization based on their significance. This
will lead practitioners to have a vague understanding of different design
principles, making it difficult to allocate design space reasonably and
emphasize design focal points. This paper aims to prioritize four design
principles, providing clear guidance for UI design in XAI. Initially, we
conducted a lightweight summary to derive five user experience standards for
non-expert users in XAI. Subsequently, we developed four corresponding webpage
prototypes for the four design principles. Nineteen participants then
interacted with these prototypes, providing ratings based on five user
experience standards, and We calculated the weights of the design principles.
Our findings indicate that, for non-expert users, "sensitivity" is the optimal
UI design principle (weight = 0.3296), followed by "flexibility" (weight =
0.3014). Finally, we engage in further discussion and summarization of our
research results, and present future works and limitations.
