Presentation Schedule
Reimagining the Dining Area for Solitary Agers: Integrating Generative AI with Four Evidence-Based Design Principles (104462)
Session Chair: Yong Yang
Thursday, 26 March 2026 15:10
Session: Session 4
Room: Room 708 (7F)
Presentation Type: Oral Presentation
As Asian cities confront rapid population aging and an increasing number of older adults living alone, the home environment has become a critical site for supporting autonomy, emotional stability, and social connection. This study focuses on the dining area—an everyday setting where routines, relationships, and psychological rhythms converge—to examine whether a set of evidence-based aging-friendly design principles (emotional comfort, safety-assured independence, community connectivity, and ability-adaptive design) can be effectively operationalized through human–AI collaboration. This study engaged 18 professional interior designers to generate AI-assisted spatial concepts embodying these four principles. Utilizing generative AI tools, participants produced a total of 432 images. Subsequently, three experts in gerontology and design evaluated the outputs using a structured rubric aligned with the principles to assess the feasibility and appropriateness of the proposed solutions. Follow-up semi-structured interviews explored how designers interpreted the diverse needs of older adults, negotiated design constraints, and navigated the interplay between professional judgment and AI-generated suggestions.
Findings reveal both the potential and limitations of generative AI in translating aging-friendly principles into actionable spatial strategies. While AI accelerates visualization and supports broader concept exploration, it also exposes cultural and contextual gaps—particularly regarding safety, daily routines, and social norms in Asian households. This study provides empirical grounding for future aging-in-place design practices, long-term care facility planning, home modification policies, and design education across the Asia–Pacific region.
Authors:
Wen-Yuan Yang, National Taipei University of Technology, Taiwan
Tung-Ming Lee, National Taipei University of Technology, Taiwan
Tzuno Tseng, National Taipei University of Technology, Taiwan
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