AIGC 기반 도시디자인 프로세스의 변화와 공공성 쟁점에 대한 탐색적 연구 = Public Design Strategies for Sustainable Cities in the AIGC Era: A Comprehensive Study

다국어 초록 (Multilingual Abstract)

(Background and Purpose) The rapid diffusion of AI-Generated Content (AIGC) is transforming the procedural structure of urban design decision-making. Traditionally, urban design secured publicness through expert-led planning and deliberative consensus mechanisms. However, the integration of AIGC shifts the locus of design generation from human experts to algorithmic systems, raising critical questions about the reconfiguration of publicness. This study aims to analyze the structural transformation of urban design processes under AIGC and to propose institutional principles for reconstructing publicness.(Method) This research employs a theoretical and policy-oriented analytical approach. It first establishes the normative baseline of procedural publicness in conventional urban design processes and then examines the characteristics of AIGC-based design structures through literature and policy review. Selected generative AI applications in urban design are examined as supplementary evidence.(Results) The findings reveal that AIGC expands analytical capacity and enables multi-scenario generation, while simultaneously shifting decision-making from creative production to algorithmic selection. This transformation introduces new challenges, including data bias, algorithmic opacity, platform dependency, and ambiguous accountability.(Conclusions) AIGC does not inherently guarantee publicness. Rather, publicness must be institutionally reconstructed through principles of public data governance, algorithmic transparency, and clarified responsibility structures. Urban design in the age of AIGC should therefore move beyond technological adoption toward a normative and institutional redefinition of publicness.