Multimodal perceptual curation for cognitive autonomy in Generation Z decision making
Abstract
Recommendation algorithms increasingly shape the perceptual environments through which young users encounter information, evaluate options, and form preferences. Although prior studies have mainly examined algorithmic exposure as a problem of content filtering, less is known about how multimodal digital cues influence perceptual attention, intuitive judgment, and decision autonomy. This study proposes an Algorithmic Cognitive Colonization framework to explain how sustained exposure to personalized recommendation systems may progressively affect attentional selection, preference formation, and self-related decision processes. Two behavioral studies were conducted with educated Chinese undergraduate participants. Study 1 used a 14-day information diet field experiment in which participants switched from personalized recommendation feeds to chronological or social-graph-based feeds while maintaining normal platform use. The intervention was associated with increased reported content-exposure breadth, a U-shaped adjustment pattern in perceived decision autonomy, and a short-term return of content-exposure breadth toward baseline after personalized feeds were resumed. Study 2 used a dual-process decision paradigm to compare rapid consumer choices with deliberative opinion formation. Algorithmic recommendation labels produced stronger conformity in speeded consumer-choice conditions than in more deliberative opinion-formation conditions. Moreover, metacognitive awareness of…
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