A Human, Sensible Future City
Planning can be a confusing field of study for a designer, especially for those who have understood the profession from a tectonic lens. Having many diverse minds — coming from all kinds of educational backgrounds — and different points of view on how the field is approached in both the faculty and the students’ eyes can be disorienting, and at times puts one at loss. As I navigated the program in the first year, I faced the challenge of reconciling the great ideas into a translatable physical form — that is the most important aspect to me. After all, I pursue an urban design and planning degree to deepen my understanding of cities in their physical form.
This article synthesizes the different topics in the Senseable City Lab’s seminar on “Technology and The Future City”, covering subjects on big data and urban theory, future streets and infrastructure, new design tools and emergent technologies, computational social science, shared economies, and Artificial Intelligence to explain why technology will either revolutionize the future of our cities, and consequently lives, or destroy their very existence. When we speak about the future, some might refer to the near future (tens of years), and others might refer to further speculation. I will explore extensively and examine how the ideas in the six previous topics translate to the built environment. Hence it is important to keep in one’s mind that our future here is beyond, say, the 2050 cities’ vision plans, instead, 100 years or more is a good frame of reference.
We had learned much from Kevin Lynch’s elements of the city (remember those? see illustration), but perhaps it is good to start shaking our faith in those pillars a little since they seem to become less credible as cities become less of a stereotomic (a term used in architecture to refer to three-dimensional solids), heavy, stationary object into a dynamic, virtual, light, and advanced organism. The thing that seems to not have changed through history, however, is the human instinct for survival. Everyone is optimizing for their own self-benefit, and that informs the behavior of space-users and space itself. One might ask where I am going with this. Data collection is used mostly for maximizing the capital of the beneficiary, as we record more data on ourselves than ever before. In fact, we collect so much data that in the time you are spending reading this, you likely had your heart rate monitored, your location recorded, your breathing rate tracked, oxygen levels recorded, and your entire spending pattern updated. There is more knowledge about one person in 48 hours than the total period prior to 2003 known to mankind (Ratti, 2003). Most of the information stored is behavioral and in many instances biased (think about Snapchat asking to build a ‘bitmoji’ of one’s self and the biases that are used to reflect one’s ideal features, for example).
Big data and computation certainly have the potential to improve our daily lives with respect to outdoor urban spaces. Information is stored on servers of big private corporations that are interested in maximizing power/profit, which makes it unlikely for big data to be used in a democratic fashion. William Whyte in his “Social Life of Small Urban Spaces” touched on ideas of how, if big data was used and accessed democratically, the qualities of urban spaces can have a strong impact in forming them. As information is utilized as a tool to maximize benefit, there is a potential to deplete society's capital for the benefit of those in power (in this case data owners).
Transportation is already taking a turn in a new direction. Ricardo Alvarez and Carlo Ratti are optimistic about Autonomous Vehicles’ capacity to improve our lives, and the possibility to integrate them into the socioeconomic structure. Carlo speaks about issues where Autonomous Vehicles can contribute to improving cities of the future in his article “How Autonomous Vehicles could transform the cities” and where promises can be seen. Social perception of car ownership, presumably, would shift toward utility or a service-based model system catalyzing the transformation of the American Dream perception from material gains to the goal of experiential ones. Autonomous Vehicles would perhaps be utilized in a similar way as services like Uber and Lyft in some places (I would argue most places), while ownership stigma would linger a little longer in cultures that have car ownership as an integral part of their makeup (cultures that are tied to horses, camels, or any forms of transport prior to vehicles, for instance).
Policy and transaction, as well as taxation, would transform as Autonomous Vehicles become widespread. Transportation Infrastructure would require a re-configuration of our existing systems. Today, Municipalities use toll gates and tax car owners to maintain roads. With respect to Autonomous Vehicles, using a system where a service provider is taxed for the roads might pose complications for the city, because we built them for cars and human drivers, we put stop lights and signs, crossovers, wider streets with multiple lanes, and so on. A great promise for Autonomous Vehicles is the efficiency in infrastructure; there would be less requirement for wide lanes, signals, and crossovers, with a more streamlined flow (See animation above). Our existing infrastructure is built for existing traveling methods that require humans to steer them, and its integration has the potential to destroy our current transportation systems without sufficient, working, and better replacement. On the flip side, there is the opportunity of providing transport methods which save costs, give space back to people, and save time than ever in the history of cities.
The progression in gathering all this information, and venturing into Autonomous Vehicles was possible by the advancing technologies of simulation, and our ability to push our ideas using advanced visualization techniques. In our Quantitative Reasoning seminar, we discuss the handling and processing of big data extensively, and one of the biggest obstacles, I see, in communicating data that contains 3, 4, or sometimes 5 dimensions on a flat screen is using 2-dimensional media as a representation of complex matrices. Advancing communication tools help us understand spaces in their 3 dimensions, and by providing the third dimension we can get closer to understanding other dimensional information. Immersing-in can be of great use for builders, creators, and innovators to improve spaces and lives in cities, but I fear our adoption of technologies has the capacity to disconnect individuals physically and that is the very key to our existence: society coming together in our mere physical form.
Because cities are an elemental part of the Earth, they are part of its geology and transformation. Earth and we have never stopped the evolution cycle, we are mutating and changing with our planet's transformation as part of the cosmic neighborhood and within itself. As such, it keeps adapting to find some sort of balance; when the CO2 levels increase, for example, Earth changes in a way to find a balance to the new disturbance in the ecosystem, and as that complex system is never stable, so is our technological application. Carlo eloquently explained the phenomenon of planes — that we have reached the unanimous form of flying objects because planes have one purpose, when data is gathered towards maximizing for one function, diversity in solutions shrinks. Cities, however, are continuously adapting not only as part of the Earth, but part of human’s changing needs, subsequently updating the approach to designing for them and in them. Progression in how we design, visualize and build cities can indeed reach uncharted territories of how to perceive spaces, as well as urban form, but relying on these emerging technologies as our modes of communication and ‘presence’ will disconnect the physical experiences which make us thrive as a species.
Social dynamics within a city are perhaps one of the strongest forces in decision-making, policies do not get passed without hearings, and permissions to build developments are not granted without ensuring most voices are received with regard to building. In my latest public hearing engagement for OMA’s development in Seaport District, the proposed master plan did not get the seal of approval before holding an open session with developers, business owners, and the local community of the area. Of course, one can debate the success of the methodology in which city hall has arranged the process, but in principle, it attempts to capture an inclusive decision in city making.
The privatization of data, as discussed by David Lazer, is a critical aspect of computational social science as tensions between data ownership and regulators become prominent. In one view, data grows in an intertwined manner — who you know, knows other connections that can share similar biases — they create intricate network nodes that maximize outreach. From an information delivery perspective, nodes essentially are the directories of maximized outreach. For example, we talk about the different urban systems in Urban Design Seminar at MIT often being central, decentralized, or distributed (blockchain). One can imagine that central systems are most suitable for accessibility and systems such as sewage and electrical infrastructure, vis-à-vis a distributed system where the network is complicated at city scales.
The “Fake News” phenomenon is a recent instance where one can witness impacts on policy, and consequently urban form in longevity; in less visible examples, such as datasets collected by Amazon or Google, data is stored and used in the dark. Corporates’ vast collection, storage, accumulation, and use of triangulated (networked) personal information provide the kit of parts for powerful computational social science tools, bringing along the potential for abuse by governments and private corporations.
Shared economies using technological advances have already disrupted ‘conventional’ ways of doing business. While the common business model’s most challenging aspect is overcoming the barrier of entry for first users, the shared economies structure leaps over it to include as many customers at no cost to the consumer. Perhaps what made services relying on shared economies, like Uber or Airbnb, so popular is the market acquisition of first users with no barriers to entry, and this vital difference is what perhaps catalyzes these businesses to thrive today. As shared economy models venture into uncharted territories, cities are always a step behind with regulations. They rely on the city where there is a high intensity of demand, supply, and ready-infrastructure to streamline the running of businesses. I have explained this idea in further detail in “Are Shared Economies Exploiting Our Cities?” article where deregulation allows this exploitation of resources for business owners.
Perhaps more concerning than any other element in our city's evolution is Artificial Intelligence, something we have started and are possibly unable to control with no clear understanding of its capabilities. What is certain, however, is its lack of contextual understanding: culture and other biological characteristics that hinder the progress of the human race, but also solidify its existence — we know cultures bring people together, and ideologies create communities and physical connections. In retrospect, it is important to understand biological organism’s rate of growth as a blessing in disguise; humans have arrived at this rate of evolution after 200,000 years of mutation and are continuing to develop, and undermining this growth by leveraging silicon chips, as explained by Groves C.P. (2005), could have unforeseen circumstances put in a simple and abstract way. Machines are designed, at the core, to understand binary relationships where we (biological organisms) construct the world in an unobstructed way. For example, humans see a rainbow as a stream of continuous colors, whereas machines see it as strips of colors stacked together (look at the atmospheric study of planets’ gases, for example, where we test signature chemicals on a digital scale), while they have a similar initial portrayal of the rainbow to the human eye, the machine that constructed the rainbow would not understand rainbows from that lens.
Comprehending how to morally code machines (which I wrote about in my other article “The Future of Cities Within the I and 0”) slowly pushes key players, such as Elon Musk, to take a step back and be mindful of their implications. The common thread I see in discussions is the assumption of machines have intellectual capability, pushing for creating moral codes that are set to be in control of machines’ processors. Machines lack the understanding of context, how and why things are perceived the way they do in certain geographies, and Grey’s philosophical understanding of ‘good’, among other things that I explained here.
It is difficult to have a conclusion with respect to the future of city models because it is a speculative subject relying on diverse fields of discipline. I also bring in my bias from what I experienced practicing in architecture and urban design, although (ironically) I am an advocate of technological advancement and saw myself at the forefront of any emergent technological tools as a practitioner. I will end this seminar on a precautionary state with respect to technology and the future of cities, that big data has the tendency to deplete societies for the benefit of those in power, that Autonomous Vehicles have the potential of improving efficiency in transport but more likely to disrupt spatial movement, that visualization and computational social science have the potential of disconnecting us and are possibly going to disfigure our spaces in their second-order effects, that shared economies exploit what we have understood fairly well to be a good economic city model, and that Artificially Intelligent machines would not have the capacity to understand the world from the point of view of a biological organism. This does not mean one should reject ideas promoting technology in the progression of cities, but one would always value life over the tools s/he makes to serve the world, and technology is no exception.
