Overconfident youth, underconfident elders: Age differences in algorithmic knowledge confidence and information perceptions
2026-07-18
Age-related differences in algorithmic knowledge are typically interpreted as competence gaps that render younger “digital natives” better equipped and older users more vulnerable in algorithmically curated environments. This study challenges these assumptions by examining (a) algorithmic knowledge confidence—whether users’ subjective algorithmic knowledge exceeds or falls short of their algorithmic awareness and knowledge—and (b) what consequences such misalignment has for information environment perceptions. Using US survey data ( N = 1205), this study found systematic misalignment between subjective and awareness-based algorithmic knowledge: younger users overestimate their understanding, whereas older users underestimate theirs. Social media use partially mediated the age–knowledge confidence relationship. Knowledge confidence, in turn, predicted perceived information reliability and diversity. These findings reveal that critical assessment of information environment is determined not by knowledge level alone but by alignment between subjective and awareness-based knowledge, highlighting the need for age-tailored interventions addressing knowledge overconfidence and underconfidence.