Google is launching a new … City? — How tech will disrupt city planning
How can people live better and happier in the city?
This is a question as old as civilization. Nowadays, tech companies are shifting their focus from software to solutions for matters affecting city life, working to address this major challenge and opportunity. In April, Alphabet’s urban technology-focused subsidiary, Sidewalk Labs, announced a plan to delve into an ambitious new arena: city building. In June, Y Combinator announced its project to study building new, better cities.
There are many expectations for these ambitious projects, but there is also skepticism around these ambitious projects. One thing that is certain is that technology has the potential to unlock challenges that city planners and governments have been facing. In this article, I will lay out some concepts that could be embedded and tested when building and managing the new city.
1. Don’t build effective cities, build smart cities
2. Design cities as if you design apps
3. Develop a language to design cities
4. Teach and learn from other cities
(This is not a comprehensive list and is intended as a thought starter for facilitating further discussion.)
1. Don’t build effective cities, build smart cities
Modern city planning is based on effectiveness. However, for the city to acclimate to the current rate of massive and rapid transformation, it should instead be designed to maximize learning and adaptiveness.
To maximize learning, data should be gathered including that pertaining to physical aspects (e.g. transportation flow, energy consumption) as well as citizen satisfaction. These two sets of data should be mapped against each other in order to understand the types of physical parameters that affect citizens’ satisfaction. The city should apply a system to enforce data collection, for instance by making it mandatory for offices to submit their energy usage data (already partially implemented as CBECS) or by providing tax benefits for citizens who respond to an annual citizen satisfaction survey.
To maximize adaptiveness, physical and legal infrastructure of the city should be made flexible in order to reflect the learnings from data collected (e.g. zoning should be able to change as the city dynamics change) and public procedure for changing existing systems should be flexible as well.
Some cities set examples for such initiatives. Moscow City gathers citizen satisfaction data across major areas such as health, transportation, and education, and reallocates part of its budget to items of high relevance to their satisfaction.
2. Design cities as if you design apps
One big challenge of physical development, compared to software development, is that it is extremely hard to perform A/B testing; it simply takes too much time and money to initiate. One way to deal with this is to create virtual cities in digital space — just like avatars — that are identical to physical cities and include all physical parameters.
In the setup phase, the city must input various types of parameters and track how each is correlated. A visualization of city data in real time will already provide immense value. When correlations have been revealed, allow the city avatar to simulate transformation over time and readjust, as a reflection of the real city. Through this process, the avatar city can simulate the real city with better precision. This means that citizens and government can A/B test a certain plan by digitally modifying parameters and initiating a time lapse in the avatar city.
3. Develop a language to design cities
There have been many efforts, by both the architecture and city-planning domains, to codify the elements that make a good city. Our current technology and experimentation in the new city may bring this to the next level.
The most famous example of such efforts is “Pattern Language” developed by Christopher Alexander. As a mathematician, computer scientist and architect, Alexander gathered the elements of “forms”(physical parameters such as buildings and open spaces) and “activities”(human behavior such as walking, gathering, and staying) that construct cities. He then codified them into 253 “Pattern Languages” (such as #8 Mosaic of subculture, #133 Staircase as a stage), and mapped their interdependence. City spaces are composed of a combination of these languages.
Alexander also states that a “City is not a tree.” He criticizes modern city planning for having a simple “Tree” structure and tending to be boring, whereas cities that are developed over time contain a more organic and complex “Semi-lattice structure.”
Although his theory was elegant, many researchers and practitioners state that Alexander could not build a semi-lattice city using this theory. Actually, his theory had the largest influence over the software world; Wikipedia, which has a complex self-referential (or semi-lattice) structure, and object-oriented programming language composed of a combination of small elements are considered deriven from Alexander’s theory.
Now may be the time to reintroduce his theory back from the software world to the hardware world. In the new city, we can treat both “form” and “activity” as datasets, and analyze their complex interdependence in real time. We may measure the “bounce rate” of a shop or analyze types of interventions (both in “form” and “activity”) that can attract people visiting a place, just as we do in online space.
4. Teach and learn from other cities
To maximize its learning and impact on other cities, the city should be digitally connected to others. Since the new city will gather the most information on every aspect, it has the potential to define the standard for city data formats worldwide.
To a limited extent, several projects have begun such an effort:
- FAB CITY connects cities and shares data and initiatives with the objective to realize “Locally Productive Globally Connected Cities.”
- ReGen Villages is planning to develop power positive off-grid villages in multiple locations, where each village shares and utilizes data from other villages.
Expertise and lessons learned from city building should be leveraged for other cities as well. For example, the Singapore government will be supporting construction of a south Indian city from scratch. City building can be offered as “service.”
- What if cities could learn daily from their current status and adapt themselves accordingly?
- What if any political, social or financial decision in cities could be tested virtually and improved?
- What if the recipe for effective and happy cities is codified and open sourced?
- What if all the cities collaborated by sharing data and initiatives to learn from each other?
These thoughts will trigger additional sets of questions to be considered:
- How would the role of the government and private sector be redefined?
- How would the governance and budget model change?
- How would cities balance sharing data and securing proprietary data?
There are few things more intriguing than the future of the city in the digital era. Can the city become as fluid and dynamic as software? What would you envision?
Thank you for reading! I’m currently in San Francisco and looking to connect with anyone in the city, architecture, real estate x tech space.
If you enjoyed reading this article, I’d really appreciate a recommendation. Tweet me @ryo14da to get in touch. I’d love to hear feedback, or answer any questions!
