The AI of Tomorrow's Cities: Urban Planning and Design

Urban Planningand Design AI for Future Cities series enhance efficiency, speed and innovation. But what does this mean forcities: for how they are planned, designed, built and managed? Whatare the opportunities and what are the risks? Amongst the hype andspeculation, how do we ensure that these technologies support us in of critical refl ections and expert insights on the uses and impacts ofartificial intelligence across all aspects of our cities– from planningthrough to running them, from infrastructure through to the flows ofresources. It will give you a rich understanding of how AI alreadyoperates in the urban context today, what trends are shaping its usetomorrow, and informed speculation on the long-term possibilities. Upcoming publicationswill focus on these themes. Contents This fi rst issue in the series focuses onUrban Planning and Design.How are generative AI models changing the work and requiredcompetencies of practitioners and decision-makers? What does a citylook like that has been shaped by AI? And how do we ensure that AI AI for Future Cities 01: Urban Planning and Design Foresight Perspective:What unforeseen consequences will AI have for designers and planners? To drive sustainable cities, we might useAI for more iterative and participatoryapproaches, where the city becomes acollaborative and ever-evolving playground;redesigning and adapting to changing needs. in real time to environmental conditions and userpreferences. Planning processes are fast and, thanksto generative AI, citizens can see what their place willlook like as it is designed, giving them the opportunity Urban planners have been looking to integrate digitaltechnology into their practice for years. Today, thepressures for efficiencies in planning, design anddelivery are greater than ever. Overlapping factorsranging from growing urbanisation, public sectorspending challenges and increased competition areto be involved meaningfully. “We could imagine wholecities becoming more rapidlyreconfigurable; mutating,changing and evolving in frontof our eyes as AI connectscontextual data streams tocollective needs and drives context. The industry is looking towards generativeAI models to enable planners and designers to tackleurban challenges and ideate around solutions morequickly and efficiently. Combining these generativeAI models with an increasing availability of real-timedata allows practitioners to uncover novel insights the design lifecycle. AI-enhanced digital twinsenable planners to anticipate and respond to climateevents and to demographic shifts. Interconnectedinfrastructure systems create more responsive andintegrated cities. AI breaks down silos betweenbuilding services and allows structures to adaptnuanced adaptations andredesigns.” Wait, slow down.Artifi cial intelligence and the thirst for data are not without their problems. The rocketing demand forcomputing power places pressures on energy gridsand requires data centres to move into the city wherespace is already at a premium. New infrastructure question. Planners will have to think critically aboutbias, privacy and accountability, particularly wherethe processes behind the AI models are hidden. Howcan we balance technological advancements withhuman oversight? How can we ensure AI-drivenurban planning and design is equitable and inclusive?What safeguards are needed to prevent bias andprotect privacy? What new skills and responsibilities Horizon Scan Evidence:Trends shaping the future of AI in Planning and Design This is a small selection ofkey data we are trackingon how AI operates in thecontext of cities at present(now→), emerging trends weare observing (near →), andinformed speculations weare making about long-term spanning all issues of theAIfor Future Citiesseries. AI for Future Cities 01: Urban Planning and DesignThe City of 2035: AI for Future Cities 01: Urban Planning and Design How can we use AI thoughtfully in Design and Planning? From generative AI tools to digital twins,implications of AI in design and planningare transformative. Yet, its development anduse carry significant risks. We must criticallyrefl ect on how we can shape and use it not comprehend the meaning of its outputs, which canbe inaccurate or contradictory. AI outputs cannot beblindly relied upon. A leading thinker on AI in architecture, Neil Leachclaims that “AI is both incredible and terrifying”.1Indeed, AI technologies are transforming the designof the built environment, marking a paradigm shiftwith their ability to learn and operate autonomously.They are already supporting designers and planners indata analyses, image generation, design optimisationand performance simulation. Although currentlylimited to specific tasks, AI tools are developingrapidly, holding extraordinary potential to enhancedesign processes and address complex urban issues.Garbage in, garbage out:AI systems process massiveamounts of data, but their outputs depend on the datathey were trained on an