Associations Between Generative AI Use and Facial Expression-Derived Central Executive Network Indices: A Pilot Study

Abstract

<b>Background/Objectives:</b> The rapid diffusion of generative AI has raised concerns about its potential influence on human cognition, particularly during creative work. This pilot study explored task-related associations between generative AI use and facial expression-derived indices that have previously been shown to correlate with gray matter volume in the default mode network (DMN) and central executive network (CEN). <b>Methods:</b> Thirty-three business professionals completed three AI-supported writing tasks involving concept generation, concept combination, and a mixed task. <b>Results:</b> The results showed a statistically robust reduction in the CEN-related facial expression index during the concept combination task, whereas no corrected changes were observed during concept generation or the mixed task. In addition, higher creative self-efficacy was associated with smaller reductions in the CEN-related index. <b>Conclusions:</b> Given the indirect nature of the facial expression measures, the absence of a control condition, and the exploratory design, these findings should be interpreted cautiously and primarily as hypothesis-generating. Future research using controlled designs and direct neuroimaging methods is needed to clarify the cognitive and neural mechanisms underlying AI-assisted creativity.

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