Too Distracted to Think Straight?
How Does External Cognitive Load Affect Young Adults’ Ability to Evaluate AI-Generated Content?
W.K. Glinkowski (TU Delft - Electrical Engineering, Mathematics and Computer Science)
U.K. Gadiraju – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)
E.C.S. de Groot – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)
M. van Dalen – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)
S. Biswas – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)
M.L. Tielman – Graduation committee member (TU Delft - Electrical Engineering, Mathematics and Computer Science)
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Abstract
In recent years, there has been a gradual increase in the use of generative artificial intelligence (AI) among young adults. At the same time, they tend to process textual information while under conditions of divided attention. As a result, young adults may encounter AI-generated misinformation when their cognitive resources are occupied, potentially affecting their ability to evaluate information critically. Previous research has linked external cognitive load (CL) to task performance, but less is known about its impact on the evaluation of AI-generated misinformation. To address this gap, this study used a simulated experiment in which AI personas representing young adults evaluated the veracity of AI-generated true and false statements under no-load, low-load, and high-load conditions, measuring accuracy, confidence, and sharing intention. High CL reduced personas' accuracy and confidence in evaluating veracity, whereas low CL did not differ significantly from the no-load condition. No statistically significant effect of CL was found for sharing intention. As the study is simulation-based, the results should not be interpreted as direct evidence of the behaviour of real young adults.