Cities as complex systems


The city is a dynamic and intricate complex system undergoing constant transformation.

Cities are in a perpetual state of flux. They contract here, sprawl there, come alive or go quiet based on a multitude of interconnected factors. While these urban transformations hold the potential to enhance mobility, living environments, and population health, they also carry the risk of unforeseen consequences. How can we adequately consider and address these ramifications?

The construction of new housing, for instance, can set off a chain reaction, influencing everything from the development of transportation infrastructure to shifts in economic and social dynamics. These intricate interactions, though challenging to grasp, are not isolated. The systems at play, such as mobility, economy, and climate, coexist with other social systems like poverty and inclusion. Gentrification serves as a poignant example of the intertwined cause-and-effect relationships; while we understand some of its mechanisms and interconnections, we cannot fully anticipate its causes and effects.

Confronted with this complexity, city builders are actively seeking effective courses of action to maximize investments and make a meaningful impact where needs are most urgent. Despite the growing body of evidence regarding the impact of one factor on another, a crucial gap persists: the lack of a holistic vision. A comprehensive view is needed to support the transformation of our cities into inclusive, sustainable spaces for all. It’s why our team is working to represent the complex system of the city, with a specific emphasis on gentrification.


Fuzzy Cognitive Mapping

Fuzzy cognitive mapping is a method for representing and analyzing the relationships between different concepts or ideas in a given system. Imagine a network of thoughts, where each node (or point) represents an idea or concept, and the links between these nodes indicate how these ideas relate to each other. The “fuzzy” aspect comes from the fact that these relationships are not binary. Rather, they are represented by degrees of certainty or strength. For example, if you think one concept has a moderate influence on another, you can represent this relationship as “partially true” or “somewhat strong”. This method is useful for modeling complex systems.

Fuzzy cognitive mapping can be used to model the workings of a complex system. To achieve this, we draw on a wide range of expertise:



Scientific evidence 

 We reviewed dozens of literature reviews to lay the foundations for a map of urban dynamics related to gentrification.


Multidisciplinary expertise

 We extend the map to incorporate perspectives from different disciplines, such as forestry, housing, economics, mobility, and anthropology. 


Realities on the ground

We discuss gentrification issues on the ground with community stakeholders to identify gaps and adjust the map to reflect urban realities.


Neural network algorithms

We model the complex system using artificial intelligence tools to quantify relationships, and simulate the impact of an intervention on the system as a whole.