What question did this study set out to answer?

To examine whether cognitive load selectively alters analytical versus heuristic trust updating pathways during trial-by-trial human-AI decision making.

August 16, 2026Human Factors The Journal of the Human Factors and Ergonomics Society

How Cognitive Load Affects Dynamic Trust Calibration in Human–AI Collaboration: Evidence for Selective Pathway Effects

View Full Paper

Ask AI

Bookmark

Authors

XCXiaojiao ChenBeijing Institute of Technology YLYonghan LiuZhejiang University YMYiran MaEli Lilly (United States)

Discussion

Member takes

Implication

Dual-task experiment reveals high cognitive load attenuates analytic evaluation and elevates heuristic reliance in human-AI decision makers, indicating mechanism-level trust reconfiguration.

Key Points

To examine whether cognitive load selectively alters analytical versus heuristic trust updating pathways during trial-by-trial human-AI decision making.
Implemented a dual-task paradigm embedded within a simulated mining exploration task to manipulate cognitive load levels during dynamic trust calibration.
Operationalized process-based (analytical evaluation of recommendation correctness) and outcome-based (heuristic reliance on task outcomes) trust updating pathways.
Analyzed trust calibration dynamics and behavioral reliance using linear mixed-effects models.
High cognitive load selectively attenuated process-based trust updating, reducing user sensitivity to AI recommendation correctness.
High cognitive load amplified outcome-based updating, increasing heuristic bias toward task outcomes regardless of recommendation accuracy.
High cognitive load elevated both overall subjective trust and behavioral reliance on the AI system.

Cite This Study

Chen et al. (2026) studied this question.

synapsesocial.com/papers/6a817a11f2fb91fc834adaf9 https://doi.org/10.1177/00187208261477486

View Full Paper

Ask AI

Bookmark

Implication

Dual-task experiment reveals high cognitive load attenuates analytic evaluation and elevates heuristic reliance in human-AI decision makers, indicating mechanism-level trust reconfiguration.