I’m an Engineer, and I’m Not Buying Into ‘Smart’ Cities

Andrea Chronopoulos

I’m an Engineer, and I’m Not Buying Into ‘Smart’ Cities
By Shoshanna Saxe, Opinion, The New York Times, 16 July 2019

Dr. Saxe is an assistant professor of civil and mineral engineering at the University of Toronto.

Sensor-equipped garbage cans sound cool, but someone still has to take out the trash.

TORONTO — Like a classroom full of overachieving students, cities around the world are racing to declare themselves “smart” — using sensors, data and ubiquitous cameras to make themselves more efficient, safe and sustainable. Perhaps the most famous initiative is here in Toronto, where Sidewalk Labs, a sibling company to Google, recently released a 1,500-page master plan to remake two neighborhoods with things like snow-melting roads and an underground pneumatic-tube network.

Smart cities make two fundamental promises: lots of data, and automated decision making based on that data. The ultimate smart city will require a raft of existing and to-be-invented technologies, from sensors to robots to artificial intelligence. For many this promises a more efficient, equitable city; for others, it raises questions about privacy and algorithmic bias.



But there is a more basic concern when it comes to smart cities: They will be exceedingly complex to manage, with all sorts of unpredictable vulnerabilities. There will always be a place for new technology in our urban infrastructure, but we may find that often, “dumb” cities will do better than smart ones.

As we know all too well from our personal lives, tech products have a short reliable life span. We accept regular disruptions in internet and cellphone function as a fact of life. Technology ages rapidly, with glitches increasing common only a couple of years into its life.

But would we accept the same rate of disruption in, say, our water and power services? City infrastructure, especially in high-income countries, is designed to last decades or centuries and must always work. Bridges are built to last 100 years, tunnels longer.

New technology in 2015 will be outdated before 2020. If we widely deploy smart tech in cities, we need to be prepared to replace it every few years, with the associated disruption and cost. But who will assume those costs?

Assuming these upgrades take place in a democratically run city, who can guarantee that future elected leaders, in an effort to cut costs and appease taxpayers, won’t shortchange spending on replacement technology — which, after all, might take place long after they leave office?

Cities must also plan for the inevitable moments when the sensors fail no matter how often we maintain or replace them. Failures in engineered systems tend to come at the most inconvenient times, like when a storm drops high levels of water and simultaneously knocks out the electricity to a smart storm water management system.

Managing all the sensors and data will require a brand-new municipal bureaucracy staffed by tech, data-science and machine-learning experts. Cities will either need to raise the funds required to pay a tech staff or outsource much of their smart city to private companies. Since current average salaries for tech workers are typically higher than for public employees, such a bureaucracy is likely to be expensive. If the answer is to outsource that staffing to private companies, then cities need to have frank conversations about what that means for democratic governance.

The most critical question, however, is whether having a smart city will make us meaningfully better at solving urban problems. Data and algorithms alone don’t actually add very much on their own. No matter how much data a city has, addressing urban challenges will still require stable long-term financing, good management and effective personnel. If smart data identifies a road that needs paving, it still needs people to show up with asphalt and a steamroller.

For many urban challenges, effective analog — “dumb” — solutions already exist. Congestion can be tackled with autonomous cars, true; it can also be tackled with better railways, bus rapid transit and bike lanes. Houses can be covered in sensors to control an automated heating and cooling system; they can also be built with operable windows and high-quality insulation.

And public garbage cans can be emptied when sensors say they are full, or on a regular basis, based on the expertise of experienced, well-paid city workers. Smart solutions might be exciting, and they might seem cheaper in the short run, but that alone doesn’t make them better.

As an infrastructure engineer, I seek the simplest effective solution to a problem with a minimum of negative consequences. What will be durable and effective over the long term? Tech solutions to urban challenges are often a Rube Goldberg machine, a fun but unnecessarily complicated approach to solving challenges with more direct solutions.

Rather than chasing the newest shiny smart-city technology, we should redirect some of that energy toward building excellent dumb cities — cities planned and built with best-in-class, durable approaches to infrastructure and the public realm. For many of our challenges, we don’t need new technologies or new ideas; we need the will, foresight and courage to use the best of the old ideas.

As we consider the city of the 21st century, we do well to remember that the things we love most about cities — parks, public spaces, neighborhood communities, education opportunities — are made and populated by people, not technology. Tech has a place in cities, but that place is not everywhere.

Shoshanna Saxe is an assistant professor of civil and mineral engineering at the University of Toronto.

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https://www.nytimes.com/2019/07/16/opinion/smart-cities.html