Is 21st-century Urbanism on the Right Track?
A Discussion on the Smart City
Popcorn and surround sound keep people going to the cinema. In the case of the erudite cinephiles, they find a je ne sais quois only at the movies. I go there for the trailers. However, last time I went to the cinema I saw many advertisements. That’s when I learned about the latest project in Buenos Aires suburbs. A firm is developing a theme park that reproduces a Middle Age town in Tuscany.
That wasn’t the opening sequence of the movie. I double-checked it with the person sitting next to me. Had I had another human being on the other side, I would have triple-checked it. Fact: half an hour away from one of South America’s largest city, a developer bought an antediluvian piece of Europe.
Less than a month ago, I was absorbed in Toronto’s dilemma: to build or not to build a smart city.
In 2017, Waterfront Toronto launched a competition. The task: design a sustainable project with affordable housing and green mobility. The winner: the American Sidewalk Labs, a sister company of Google.
The ideas are astounding. And although the two parties have an open dialogue, the project is currently paused. The dimension of the designed neighborhood and data manipulation are being revised.
By now, most of us have heard about the Quayside and IDEA District project. Tv guides aside, every respectful publication has written about it. I won’t delve into details here. Quayside has aroused controversy worldwide because it isn’t only about Quayside. Toronto has challenges many other cities face, like traffic jams, exorbitant square meter prices, and waste.
It’s telling that Sidewalk Toronto will solve none of those problems in the area they’ve been assigned to. The acres where they’d build up a smart city is nowadays undeveloped. Let’s not forget that Waterfront Toronto was born to revitalize the city’s lakefront. Time will tell how innovations apply to the rest of Toronto — where actual problems are. Anyway, Quayside is an excuse opportunity to explore the smart city. As such, Sidewalk’s intervention is beneficial. Moreover, it’s not the project’s what but its where and how that are under revision.
People’s Data-Centered Cities
There are no complaints about the innovative proposals Sidewalk Toronto has presented. There are people aloof to them but no one is opposed to a low carbon footprint neighborhood. The alliance Waterfront Toronto-Sidewalk Labs broke out in disagreement over the collection and use of data. The geographical scope of the project is another pending issue. Long story short, both subjects had remained in a grey-comfort-zone.
If the people-centered cities model has been a paradigm shift in urbanism, big data-centered cities is a new one. We’ve been collecting information since when bedsheet based outfits were fashionable. The drastic change is that today we can do it in a systematic way, getting more material, faster. Big data is a complementary tool to support the analysis urban experts get from observation, listening, and common sense.
Living in a smart city means that the traces we leave are now registered. The aim is to better frame the changes taking place now. This improves the analysis of livability, facilitating its evaluation throughout time.
I discussed the idea of turning city life into numbers to make it more human-centered with Zhan Guo. He studied in Beijing, Tianjin, and Cambridge. Guo’s currently Associate Professor of Urban Planning and Transportation Policy, at Wagner Graduate School of Public Service, New York University. That’s where I met him. According to him, the technical system is currently biased towards cars. It analyzes traffic but pedestrian activities are ignored. We have a constraint. Computers should run faster and the statistic models could be more accurate. ‘We have to identify, capture, and analyze all these trips’. Technologies should adjust the urban services and infrastructure to our current needs, in an efficient way.
Datafication won’t be a magical solution on its own. Numbers can provide objective information. That doesn’t mean, however, that decisions based on them will be accurate. The smartest decision could be threatened by politicians looking for cutting costs to please taxpayers.
Smart People’s Cities
Reading about smart cities today takes me back to the last weeks of the year 1999. We thought that in 2000, there’d be robots everywhere and we’d fly cars. But when the 2000s arrived, things hardly changed. At home, the most sophisticated items were a blender with a glass jar and a StarTAC. The blender chopped ice cubes in less than 10 seconds and the phone had a vibrating alert. Still, nothing impressed me more than the fact that the phone revived after mom dropped it in the toilet and left it overnight in a rice bowl.
Today, Google’s sister company, Sidewalk Labs designs smart cities. Many Torontonians fear of being governed by machines. Feeling fear is overestimating the adversary. I prefer to think of smart cities as a collaborative project. Public and tech companies work together. Thus, machines will be at our service and not the other way around. Apps have enhanced our urban lives. We can discover restaurants and avoid visiting cafes where coffee nor the internet are good. We pick a place depending on its rating and reviews. Companies create infrastructure, we provide the content.
It’s our responsibility to be more realistic than previous generations. Tech progress faces obstacles. These obstacles make the development stop, revise procedures, go back, and try again. I don’t want to sound gloomy but we shouldn’t get rid of rice bowls so fast.
Something similar goes for big data. That’s what I talked about with Ceni Babaoglu. She is a Senior Data Analytics Associate and Data Science Instructor at Ryerson University. According to her, data sets aren’t 100% reliable and experts’ intuition is always something positive. Partly, the analysis accuracy will depend on how data has been collected. There may be some missing values. As Mrs. Babaoglu said, it can happen that data sets won’t give us the whole story. In such cases, external input is needed. Not only big data isn’t infallible, but its use is also conditioned on regulations. Even in cases when technology is available, we should wait for the law. Finally, Mrs. Ceni Babaoglu believes data should be de-identifyied. But she explained the process might be hard sometimes.
Data de-identification is key. That will emphasize the sensors’ statistical purpose. Only then will they be perceived as any other piece of infrastructure. Urban planners work with statistics. For instance, they identify crash-prone intersections and thus they decide where to put traffic lights.
Anonymity is inherent to the city landscape and I can’t see how that could change. If law regulations guarantee that the data collected will be solely used to enhance urban planning, there’d be no reason to panic.
Twenty-First Century Urbanism: The Paradox
Research has shown that the cinema audience is four times more likely to be emotionally engaged than a television audience. Still, that commercial about the medieval suburb didn’t impress me. Why should we go back in time when technology can make things way more interesting and efficient? Ox driven cart might be a zero-emission vehicle but, is that where we should return to?
Sidewalk Labs will have to keep waiting before breaking ground. This last October 31st, Waterfront Toronto put off a resolution. They announced changes the American firm had to accept to proceed with the project. Google’s sister company will pay market value for the land at the time of sale. It will also team up with one or more real estate partners. Besides, it will allow Canadian companies to use Sidewalk’s hardware and software patents. Finally, Sidewalk Labs will no longer rely on the 190-acres extension. The story is to be continued into March 2020.
I tried to find out how both parties foresee how things will unfold. I couldn’t make it. Instead, I read a Mayor John Tory’s ambiguous statement in the news. He said this is an opportunity for Toronto. Language politics. Another question I had was why an American company would choose a Canadian city to develop such a massive project?
Toronto isn’t an isolated case. Worldwide metropolis cope with the growing urban population, maintaining high standards of living, and strengthening cities’ sustainability. The smart city model may solve these challenges or it could at least be part of the solution. Yet, to many people, they are not convincing.
For the last decades, urbanism has switched its focus. Although car ridership is still challenging in many places, people-centered cities is the current paradigm. Here’s the paradox. Urban planners can use real-time information. To continue the progress, new tools and techniques require the collection of data. But doing so means facing some ethical dilemmas.
Cities are trapped in a furious present. It frequently gives its residents hyper-realistic glances of the future. It’s understandable, then, to have a chicken and egg situation with legislation. We’ll always be a step behind regulations. Even when we mean to be cautious, there’s always a chance for failure. We will neither identify nor precise risks until we go through smart cities.
A significant part of the problem is to keep using the qualifying term ‘smart’. Cities have always been smart: they’ve reflected the zeitgeist, the spirit of the age. They’ve attuned to our needs. In this sense, even the car-centered cities were smart. It was the (lack of) urban planning of that time which made poor choices. Now it’s our turn to be smart. We should observe, understand, and estimate our changing reality.
I’d rather use ‘predictive’ as a distinctive symbol of our generation. The predictive city. In predictive cities, daily practice updates the norm. Technology can forecast and thus optimize upcoming experiences. Urban settlements developed due to the immediacy and ease of doing business. Done well, predictive cities will only boost that. Plus, they’ll be interesting places to live in.
Predictive cities should aim for an efficient environment where transit, housing, and climate present no obstacles. Efficiency, however, isn’t linked exclusively to technology. More mindful urban planning, rather than robots, could solve some problems citizens face today. Think of hard to find pedestrian call buttons and confusing bus stops, for example.
It seems that the smart city model procrastinates some hand-operated quick fixes. Take, for instance, heat waves, strong winds, and floods. Trees’ shadows and water fountains freshen up the air. Short buildings don’t provoke hurricane formations at the sidewalk level as skyscrapers do. Civil engineering works can deal with flood-prone areas. They might no be as exciting and highly efficient as sensors but they do the job.
There are handcrafted alternatives to the modular paving, too. Sidewalk Labs’ hexagonal paving changes the road scheme, depending on the times of the day and the users’ needs. Colorful lights turn on and off, making roads, bike lanes, and sidewalks wider or narrower. Naked streets do pretty much the same, without the lighting spectacle.
In naked streets, drivers, bikers, pedestrians, and the rest of the road creatures share a unique, unmarked space. There are no lanes assigned to specific means of transport. All users are respectful of transit rules and speed limits. Pedestrianizing certain streets during the weekends, for example, could be a complementary tool. I’d insist on this type of measures before wiring a lighting circuit under the footway.
Today’s challenges can be fixed with existing tools and techniques. Hopefully, future cities will anticipate upcoming ones, as well as solve present tasks. I have high expectations of the recycling system. Sorting waste still looks superannuated. Depending on where you live, you’ll have to choose from 2 to 20 categories before throwing away a tuna can, wrapped in paper, and with some leftovers. Predictive cities should simplify that.
Cities’ social equity is a pending issue as well. Sidewalk Labs presented timber prefabricated housing units, as a faster and cheaper option. Accelerating construction is essential since the cities’ population will keep growing consistently. However, I have some reservations about its conveniency. First, what really fixes housing prices is the land. A project like IDEA District will certainly push land prices up. Even units made out of recycled plastic bottles will turn out to be unaffordable. Second, a key to make this timber housing work is uniformity and repeatability. Leith Moore, the founder of R-Hauz Solutions Inc., mentions these features as requisites to make the process more efficient and cost-effective. Eric Jaffe, Editor of Sidewalk Talk, says this won’t mean necessarily that all timber buildings will look alike. That’d be detail not to miss because the variety of facades is characteristic of walkable neighborhoods.
I’m an enthusiast of using IoT in cities. I support people-centered cities (PCC), too. People-centered cities are more than simply the opposite of car-centered cities. PCC’s design answers to people’s needs. As long as urban planning aims human-centered cities, technology will be at our service and no metropolis will turn into a dystopia. Procedures are being carried out to close the legal loophole regarding data collection. In the meantime, as I’ve mentioned, there are data-free options to try.
Besides its imperfections, its weaknesses, and the questions it arises the smart city is the direction to go. Thermal grids might not be imperative but they are definitely more interesting than remote burbs. In the 21st century, it’s not technology but suburbs, multi-lane avenues, and single-family homes that should give us the willies. High-quality urbanism can’t be conservative.
Still, why does an American company design a smart city in Toronto? Sidewalk Labs’s Associate Director answered it was a unique scenario, in a successful city. ‘It’s a huge swath of land on the waterfront, near the downtown core that is not developed yet’, Keerthana Rang said. They saw an opportunity and they took it. That was smart.