This study critically examines the limitations of current technology-centered AI education in light of the socio-cultural transformations driven by the rapid spread of generative artificial intelligence and digital transformation. In response to these...
This study critically examines the limitations of current technology-centered AI education in light of the socio-cultural transformations driven by the rapid spread of generative artificial intelligence and digital transformation. In response to these changes, the study proposes an alternative model of AI education that emphasizes the integration of the humanities and social sciences. By focusing on the formation of convergent AI talent, the research highlights the necessity of incorporating emotional, ethical, and contextual understanding into AI education. The study takes a closer look at the Gwangju AI Academy as a case study, analyzing its interdisciplinary education model, program outcomes, and alignment with regional policy frameworks. It emphasizes the importance of regionally grounded, community-based AI education as a sustainable approach to building a lifelong learning ecosystem. The findings suggest that AI education must go beyond technical skill development and include critical thinking, cultural competence, and ethical literacy. Through a humanities and social sciences-based AI curriculum, it is possible to cultivate well-rounded, socially responsible AI professionals. Ultimately, this study contributes to shaping a more inclusive and context-aware model of AI talent development.