Critical Reflection & Professional Judgement

Introduction

Throughout the redesign of Floating Ground – ARCA Student Clubhouse, AI became a useful design assistant rather than a replacement for architectural thinking. One of the main lessons from this process is that AI can help designers work more efficiently, explore a wider range of ideas, and evaluate projects from different perspectives. However, the final responsibility always remains with the architect. It is the architect who must determine what is realistic, appropriate for the site, and beneficial to the overall project.

AI as a Tool for Research and Design Exploration

AI contributed significantly during the research and conceptual exploration stages. Research-based AI tools were used to investigate architectural precedents, climate-responsive strategies, façade systems, and the concept of lightness in architecture. These insights encouraged a more critical evaluation of the original project.

The original Floating Ground concept already possessed a strong identity through its cantilevered multi-purpose hall and the idea of elevating the building above an open student ground. However, AI-assisted research highlighted opportunities for further development. It became clear that the building should not only appear to float visually but should also communicate why it floats, how it responds to climate conditions, and how the elevated design benefits student activities below.

Improving Design Communication Through AI

ChatGPT played an important role in translating research findings into clearer design narratives and image-generation prompts. This was valuable because architecture involves more than physical form; it also encompasses atmosphere, materiality, movement, and user experience.

Through prompt development, the project evolved into the concept of “Floating Ground as Climate Social Infrastructure.” This shifted the design focus from a purely formal cantilever expression toward a proposal that integrates environmental and social considerations, including shade, natural ventilation, rain protection, filtered daylight, and student interaction.

Visual Testing and Design Development

Image-generation AI provided a fast method for testing visual possibilities. It enabled exploration of different façade treatments, translucent materials, shaded public spaces, and tropical lighting conditions. These visual studies helped reinforce the idea of creating a lighter and more atmospheric architectural expression, particularly for the cantilevered hall.
The generated images also emphasized the importance of human scale. By incorporating students, seating areas, rain gardens, and shaded gathering spaces, the project evolved from being perceived as a standalone object into a functional campus destination where people can gather, study, wait, and interact.

Limitations of AI in Architectural Design

Despite its advantages, AI demonstrated several limitations. One major issue was its tendency to prioritize visual appeal over architectural realism. Many generated outputs appeared impressive but lacked structural credibility. In some cases, the cantilever became excessively dramatic, structural supports disappeared, or the building appeared to float without a logical load-transfer system.
This highlighted an important limitation: AI does not truly understand gravity, structural engineering, construction methods, or building regulations. While it can generate convincing images, a visually convincing image does not necessarily represent a feasible architectural solution.

Site-Specific Challenges and Human Decision-Making

Another limitation was AI’s inability to fully understand the actual site context. The project is located within a campus environment that includes existing buildings, circulation networks, parking areas, drop-off zones, and established student movement patterns. These factors require site-specific analysis that AI cannot accurately generate through assumptions alone.

As a result, key design decisions still relied on personal understanding of the site and studio requirements. Elements such as the shaded plaza, pedestrian circulation routes, rain gardens, and arrival sequence required careful planning and architectural judgement rather than purely visual generation.

Ethical Considerations in the Use of AI

The use of AI in architectural design also raises ethical concerns. AI-generated images can make a project appear more complete and resolved than it actually is. Without proper explanation, this may create misleading impressions regarding the technical development of a proposal.

There is also the risk of unintentionally replicating the styles of well-known architects or becoming overly dependent on AI-generated aesthetics. To address these concerns, AI outputs were treated as exploratory tools rather than final architectural solutions. The final proposal remained grounded in the project's specific site conditions, design objectives, and architectural intentions.

Professional Responsibility and Architectural Judgement

This process reinforced the understanding that architects have responsibilities beyond producing attractive visual representations. Professional architectural practice requires consideration of users, climate, safety, structural performance, material behaviour, and long-term functionality.

For this project, these responsibilities translated into improving the student experience at ground level, enhancing the façade’s response to tropical sunlight, clarifying the structural logic of the cantilever, and increasing overall comfort within Kajang’s climate conditions.

Conclusion

Ultimately, my role throughout this process was that of an architectural editor. AI generated a wide range of possibilities, but it was necessary to evaluate, select, reject, modify, and translate those possibilities into a realistic architectural proposal.

The most important professional judgement involved recognizing when an AI-generated result provided meaningful design value and when it was merely visually appealing. The revised Floating Ground proposal became stronger because AI expanded the scope of exploration, while human judgement ensured that the final design remained grounded in architectural logic, climate responsiveness, and student experience.

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