AI for Creativity: A GenAI-Based Approach for Early Concept Design and Its Impact on Senior Architects

要旨

Senior architects are pivotal in shaping architectural projects, yet integrating Generative AI (GenAI) into their workflows presents notable challenges. A formative study (N=11) identified key pain points in their early concept design process. To address these, we developed EarlyArchi, a GenAI-driven system supporting automated concept generation and evaluation. In a within-subject study (N=13), participants used EarlyArchi for early-stage design tasks. Results showed enhanced perceived creativity, improved design competency, and more efficient ideation. However, concerns emerged regarding controllability and domain-specific accuracy, highlighting the need for features that preserve professional autonomy and trust. Further analysis revealed three GenAI involvement modes—fully AI-driven, GenAI-led, and human-led—emphasizing the importance of adaptive role allocation in balancing creative exploration with expert leadership. These findings offer insights into supporting senior architects through GenAI while identifying key considerations for designing future human–AI co-creation systems.

著者
Jiajuan LI
The Hong Kong Polytechnic University, Hong Kong SAR, China
Xia Wang
The Hong Kong Polytechnic University, Hong Kong, China
Chengzhong Liu
Hong Kong Generative AI Research and Development Center, Hong Kong, China
CHEN Yaxin
Laboratory for Artificial Intelligence in Design, Hong Kong, Hong Kong
Le Fang
The Hong Kong Polytechnic University, Hong Kong SAR, China
YINGQING XU
Tsinghua University, Beijing, China
Lie Zhang
Tsinghua University, Beijing, China
Kun-Pyo Lee
The Hong Kong Polytechnic University, Hong Kong, China
Stephen Jia Wang
The Hong Kong Polytechnic University, Hong Kong SAR, China

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: AI for Task Augmentation

Area 1 + 2 + 3: theatre
7 件の発表
2026-04-15 18:00:00
2026-04-15 19:30:00