Effects of Automation Accuracy and Task Difficulty on Decision-Making Efficiency: Insights from Systems Factorial Technology

We examined the impact of automation accuracy and task difficulty on human decision-making. We hypothesized that highly accurate aids would improve performance only under difficult conditions, and this effect would be influenced by individual selection history. Using a categorization task, we manipulated automation accuracy (high/low) and task difficulty (easy/difficult) with three types of aids presented in separate blocks or randomly intermixed to 36 participants. We used a capacity measure based on the single-target self-terminating (STST) rule within the framework of Systems Factorial Technology (SFT) to assess decision efficiency. Results showed that high-accuracy aids reduced accuracy and increased RTs compared to unaided decisions, regardless of automation accuracy and task difficulty. Notably, high-accuracy aids provided incorrect answers under difficult conditions, leading to a significant decline in performance. However, the STST capacity results showed that high-accuracy aids had supercapacity processing under difficult conditions in the block design, but not in the mixed design. These findings suggest that effective top-down control is essential to utilize high-accuracy aids to improve decision efficiency when the task is relatively difficult. Our study challenges the resource hypothesis and suggests that individuals may rely more on high-accuracy aids as task demands increase. Furthermore, these capacity differences may imply that participants utilize different decision strategies in terms of mental architecture to integrate current percept and aided information. Our research provides novel insights into the potential benefits and limitations of automated aids for information processing efficiency.