2 minute read
How can AI Shape the City?
Until a few years ago, all the buzz of future urbanization was about the concept of the smart city—except no one knew what that was, let alone how to make it happen. Slogans can be useful as long as some form of result matches their power as a message; otherwise, they become just another unrealized promise. Together with their crucial symbolic role, that significant capacity explains their utility for politicians across the globe—until of course, people stop believing in their promises. In any case, in its most promising version, the smart city turned out to be mainly a data-driven urban management tool with the primary goal of a more efficient mobility system. Not a bad idea at all, if only its many promoters had made a genuine commitment to its many possibilities.
The conversation has now moved on and more people seem interested and intrigued by the potential of artificial intelligence (AI) as a game changer in the coming years. But again, most of the emphasis as far as the built environment is concerned seems to be placed on its operational capabilities and utility. Yet perhaps the promise of these tools is rather in how AI might help us imagine, design, and construct new environments that can best reflect the desires, needs, and values of a society. Such challenges in the relationality between design and AI are the primary goals of the latest research studio conducted at the Harvard University Graduate School of Design with support from our collaborators at AECOM Asia Pacific. The location of our research for this project is the city of Shenzhen in China. Shenzhen’s geographical position and proximity to Hong Kong, and its history of rapid growth and transformation as
3 an advanced technology hub, make it an ideal location for this investigation.
There are two key advantages in using AI as a critical component and complement to innovative forms in design and planning. The first advantage is configurational in character. The use of AI can enable a multi-scalar and multi-thematic approach to the analysis and investigation of a possible design area. Configurational knowledge involves the accumulation and juxtaposition of various forms of data and knowledge that affect a geographical territory over time. It allows future design projects to consider dynamic interrelationships—physical, operational, and environmental—between the two scales: territory and a site-specific location.
The second benefit of using AI might be described as projective in character. It relates to the role of AI in shaping how designers plan, organize, and devise speculative proposals for an area in the light of the data at the territorial scale. The use of projective methods could enable the investigation, development, and potential evolution of a project and its impact analysis within the larger territory. The use of such dynamic multi-scalar approaches is by necessity contingent on various forms of disciplinary knowledge, from environmental sciences to transportation systems, from the social sciences to planning and design. It requires new forms of collaboration and affiliation between the disciplines that AI might support.
Equally valuable, an approach for elevating the citizens’ engagement and participation could also be incorporated in Shenzhen’s possible futures. What role can social media play in linking people and places, virtual and physical spaces? How can AI help shape the physical environment and make it respond to changing patterns of use over time? Making Shenzhen a flexible and responsive city is the exciting challenge that lies ahead.