‘Smarter’ and ‘Greener’ Cities: About Cities, AI, and Resilience

‘Smarter’ and ‘greener’ cities. Both words are often used together when talking about the future of cities. Yet, as author Antoine Picon once said, reality tells a different story where the smart has “captured” the green. Smart today means very fast-growing energy consumption and added CO2 emissions. Five years ago, computer and internet activity polluted as much as all air transport. Given the growth pace of the digital sector, in 2025, it will be as much as global road transport. Energy consumption is the hidden face of the digital world. Today, the internet consumes 10 percent of the world’s energy. One third of this energy is absorbed by computers, one third by networks, and one third by servers that store data. Therefore, smarter cities mean that our cities – which, according to the World Bank, already account for more than 80 percent of energy consumption and CO2 emissions – are increasing their energy and carbon footprint.

Furthermore, smart solutions have not yet reached the promises they announced for solving major urban challenges. Let’s consider the mobility issues: digital services were presented as a system to help fight against urban congestion, a threat to cities, quality of life, and urban economic attractiveness. Thanks to its ability to aggregate vast data, create new services, and build mobility platforms, digital technology promised to reduce congestion in the city by helping users plan their journeys better, avoid bottlenecks, or even to give up their personal car. However, these digital tools, now ten years old, have not made congestion disappear. Worse, as shown by our latest report on Congestion and Digital, they even made the use of cars in the city more competitive than before. Some cities are at the edge of sclerosis and some inhabitants at the most peripheral areas are captives of the automobile and seeing their mobility degraded, sometimes forcing them to “de-mobility” all together.

In such context, the use of artificial intelligence applied to urban issues raises both fears and hopes. Will Artificial Intelligence (AI) succeed where big data is on stand-by, or fail? Will more data-processing capacities mean more energy consumption, more CO2 emissions? Will it make the situation worse and add a major problem to an already problematic situation? If AI was only about more data processing, one would have good reasons to worry. But, even in its current early stage, AI also represents a promising field for cities. It can bring not only a quantitative change with its capacity to process more data from diverse sources, but it also brings a qualitative change thanks to its self-learning capacities.

Our cities are data mines, not only because they are vast and complex, but because they also have a long history. They are themselves wonderful self-learning bodies: how could thousand-year old cities live through centuries without learning from their experiences, good or dramatic? Cities are resilient institutions, and from that point of view, they could find a natural ally in AI. Both AI and resilience have indeed this in common; they are self-learning by design. In this respect, they are not just another tool for cities to use. If combined, they can help cities move to a new method, a new mindset to shape unheard and unseen solutions. To put it in different words, AI without resilience  could fall short of solutions when new challenges arise, because it relies on data from the past only. But resilience strategies without AI could miss the goal because of too much complexity.

Unheard and unseen solutions are exactly what we need to win the fight against climate change. Let’s admit it; we are collectively lagging on two major causes of CO2 emissions: buildings and mobility. We now know that we need more than to do  better. We need to do things differently. The news is that AI comes as a possible new player in the field. Good news or bad news? We’ll say it’s good news when we have proven that AI can be turned into an innovative solution to reach our climate change targets, whether by reducing the number of single-used cars in our metropolises without harming our citizens’ ability to go about their daily lives, or by starting a movement to reduce CO2 emissions from buildings. For the moment, let’s work to… make it work. Let’s create the right governance and framework to enable AI to fulfill its promises.