Determinants of AI Literacy Competency: Focused on AI Usage Experience and Innovativeness
AI as Infrastructure Media and AI Literacy as Relational Competency

Jung Seo-hyun & Park Joo-yeon (2024) study published in Broadcasting and Communication Research (Autumn 2024, pp.137-168) investigates determinants of AI literacy competency among Korean adults using Bandura''s Social Cognitive Theory. Research design: AI service usage experience as behavioral factor; individual innovativeness as personal factor; studying how these predict AI literacy (critical evaluation + ethical use of AI, not just technical proficiency). Key findings: (1) AI usage experience has significant positive effect on AI literacy — more AI experience correlates with higher literacy across functional understanding, critical evaluation, and ethical use dimensions; (2) Innovativeness (openness to new technology adoption) significantly mediates the experience-literacy relationship — innovative individuals extract more learning value from AI interactions; (3) The combination of experience and innovativeness creates a reinforcing cycle: innovative individuals use AI more, gain more literacy, which further reduces adoption barriers. "AI as infrastructure media" framing: the authors argue AI literacy should be understood not as discrete technical skill but as relational competency — the ability to effectively navigate a pervasive infrastructure that mediates increasingly broad domains of daily and professional life. Policy implications: AI literacy education should focus not just on technical skills but on cultivating the disposition toward critical engagement with AI systems; innovativeness can be developed through structured AI experimentation programs rather than relying on innate personality traits; the digital divide in AI literacy will compound existing socioeconomic inequalities if not actively addressed through education policy.