Cognitive Abilities and Trust Calibration: Understanding Individual Differences in Automation Trust Dynamics

Individual differences in cognitive abilities may influence how people develop and maintain trustin automated systems, yet the mechanisms underlying this relationship remain poorlyunderstood. This study investigated how three foundational cognitive abilities — workingmemory (WM), attention control (AC), and fluid intelligence (Gf) — shape trust dynamics,particularly focusing on trust decline and recovery after automation failures. Participants (n=111)completed cognitive tests measuring WM, AC, and Gf before performing a dual-task paradigmwhere they monitored an automated memory aid exhibiting varying reliability levels (100%-65%-100%) while completing a mental arithmetic task. Results revealed that WM and Gfpositively predicted trust recovery after automation failures, while AC influenced long-term trustcalibration, with high-AC individuals showing more nuanced trust adjustments reflecting systemreliability history. Trust decline was uniform across ability levels, suggesting immediacy of trustloss. The relationship between abilities and trust may have been partially mediated byautomation schemas, with WM negatively correlating with all-or-none thinking aboutautomation. These findings suggest different cognitive abilities play distinct roles in trustdynamics: WM supports monitoring automation performance, Gf enables effective schemaupdating, and AC facilitates appropriate deployment of these resources for trust calibration. Thiswork advances our understanding of trust mechanisms and has implications for designingautomation interfaces that accommodate individual cognitive differences.