## 4 Results
### Experimental Results  
This study employed non-parametric tests for independent sample analyses, with task difficulty as the independent variable and the degree of trust and its dynamic changes \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Demographics** & & **Number** & **Percentage (\%)** \\ \hline \multirow{2}{*}{Gender} & Male & 16 & 27 \\ \cline{2-4}  & Female & 44 & 73 \\ \hline \multirow{2}{*}{Education Level} & Undergraduate & 42 & 70 \\ \cline{2-4}  & Graduate & 18 & 30 \\ \hline \multirow{2}{*}{Familiarity with AI} & Moderately Familiar & 41 & 68 \\ \cline{2-4}  & Unfamiliar & 19 & 32 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Descriptive Statistics. Figure 7: Average time consumption for different task difficulties. as the dependent variables. Table 2 provides a detailed listing of the participants' trust levels towards UAVs at three core time points: \(T_{0},\ T_{1},T_{2}\) These represent the trust levels participants had towards the UAV during the Training, Accompanying, and Automated stages, respectively. \(T_{0}\) denotes static trust, whereas \(T_{1}\) and \(T_{3}\) represent dynamic trust after Step 2 and Step 3. The term \(\Delta T_{i}\) quantifies the shift in participants' trust levels towards the UAV across these stages. The experimental results indicate that during the training phase of the experiment, prior to any interaction with the UAV, participants from all groups manifested comparable trust levels, with no statistically significant differences observed (\(\chi^{2}\) = 5.7, df = 2, \(p\) = 0.058 \(>\) 0.05). This implies that after participants fully grasped the experimental background and the relevant artificial intelligence algorithms, their static trust \(T_{0}\) remained consistent, setting a stable baseline for the subsequent experimental stages. However, in Step 2, the varying task difficulty significantly influenced trust levels (\(\chi^{2}\) = 16.448, df = 2, \(p\) = 0.0 \(<\) 0.01). This finding suggests that participants' interaction experiences with AI when managing tasks of different difficulties significantly influenced their trust levels. Such variations in trust could be attributed to the distinct interaction experiences participants encountered while executing tasks of different complexities. Nevertheless, in Step 3, the trust discrepancies arising from task difficulty diminished and were no longer statistically significant (\(\chi^{2}\) = 2.235, df = 2, \(p\) = 3.27). This could indicate that although task difficulty initially shaped trust, its influence seemed to neutralize as the experiment progressed. It is noteworthy that between Step 2 and Step 3, i.e., \(\Delta T_{12}\), a significant shift in trust levels was observed (\(\chi^{2}\) = 17.914, df = 2, \(p\) = 0.0 \(<\) 0.01). This outcome supports our core hypothesis: task difficulty, along with the distinct interaction experiences it produces, plays a significant role in influencing the dynamic changes in trust levels. While an initial level of trust may be consistent, it tends to adapt based on the task's complexity. However, this fluctuation in trust tends to stabilize as interactions become more frequent and profound. Figure 8 further elucidates the impact of task difficulty on trust levels. Figure 8a-c illustrate shifts in the average trust values across stages and varying task difficulties. In Figure 8a, before the experiment, the trust participants placed in artificial intelligence was consistent across all difficulty groups. However, during Step 2, those engaged in normal difficulty tasks exhibited higher average trust values than their counterparts in the easy and hard task groups. By Step 3, after experiencing HRI, the trust levels for the normal difficulty group declined, settling below the easy and hard task groups. Figure 8d outlines the differences in trust between Step 2 and Step 3. The trend mimics a \"V\" shape, suggesting that participants tackling either easy or hard tasks felt a stronger inclination to interact with AI.