A Human-Centered AI Community Education Model for Digital Literacy, Social Ethics, and Self-Directed Learning: An Integrative Review

Abstract

Artificial intelligence (AI) is increasingly used outside formal educational institutions, but community members often encounter it without adequate critical literacy, ethical guidance, or self-directed learning skills. This study develops a human-centered AI community education model integrating digital literacy, social ethics, and self-directed learning. A structured integrative review was conducted using 25 peer-reviewed, theoretical, methodological, and international policy sources. Sources were selected for relevance to AI literacy, digital competence, responsible AI, adult and community education, and learner autonomy. A concept matrix and deductive-inductive thematic synthesis produced five findings: AI affordances depend on pedagogical purpose; digital literacy must include critical evaluation of AI-generated content and data awareness; social ethics functions as both an outcome and a governance safeguard; AI supports self-directed learning when scaffolding preserves learner agency; and implementation depends on co-design, equitable access, facilitation, and iterative evaluation. The proposed model comprises contextual diagnosis, co-design and enabling conditions, an AI-supported learning cycle, community application, and evaluation. Critical digital and AI literacy, together with social ethics, rights, and human agency, operate across all stages. The model provides theoretical propositions and operational indicators for community learning centers, local governments, libraries, educational institutions, and civil-society organizations. Empirical validation through design-based, quasi-experimental, and longitudinal research is recommended.