Abstract
This case examines the integration of artificial intelligence (AI) in landscape architecture education to enhance critical reflection, equip students with innovative tools, and navigate AI applications, implications and challenges. Conducted over two years in the MLA International Studio at the University of Hong Kong (HKU), it involved students in iterative exercises using AI tools such as Midjourney and DALL-E. In the first exercise, students envisioned speculative fictional futures based on existing imaginaries (Baudrillard and Evans, 1991; Malakuczi, 2024). They used AI to create digital collages, translating narratives into visuals. This process, characterized by revisions and critiques, fostered discussions and critical reflections, forcing students to continuously (re)interpret their proposals. In the second exercise, students proposed design interventions engaging the social dynamics and public space grounded in the site genius loci (Qian, 2014). Students fed photographs of physical models developed in class into AI, with prompts based on their context research. The AI-images were evaluated for proportion, scale, and spatial qualities, and contextualized through the drawing of plans, and sections (Jensen and van Dooren, 2012). Finally, they used AI to speculate on extreme future conditions.
The post-teaching analysis reveals that AI bridges conceptual abstractions and pragmatic design outcomes. The non-linear process often required students to reformulate their methods, amplifying the iterative nature of design (Allen, 1999; Sreenivasan and Suresh, 2024; Zhou et al., 2023). Since the methodology demanded students to use different types of representations, the process acknowledged the use of representation as a performative tool (Corner, 1992). AI-assisted methodologies reduced information processing time and consolidated diverse textual sources into visuals. Establishing procedural frameworks was crucial for maintaining consistency and focus, ensuring a reflective approach to design teaching. The experience underscores AI’s transformative potential in landscape architecture education, highlighting the need to explore how AI bridge conceptual and practical design and to open critical discussions on its potential implications. AI offers new pathways for rapid exploration and visualization of complex ideas. The study advocates for a balanced approach, integrating AI with traditional methods and for broadening the in-class discussion of the use of AI tools with students regarding design development. It calls for further experimentation to refine these methodologies, ensuring their relevance in an evolving technological landscape (Qiu, 2024). By fostering continuous learning and adaptation, educators can better navigate the opportunities and challenges of AI, paving the way for innovative and effective educational practices.
Presenter(s) / Author(s)
