Systems Science is one or our great hopes for a method of addressing the major challenges facing our world in the 21^st century and beyond.  Large among these challenges are:

• Climate change and the adaptation of our environment to these changes
• Lower impact economies and living
• Transition from the centralized systems of the Industrial Age to the distributed systems of the Information Age

The implementation of solutions to these challenges will, to a very large extent (at least 70%), be implemented in cities around the world.  Hence the understanding of cities as complex systems must be a primary target for GSS.

My point of view on cities as complex systems is that we must begin from a people-centric perspective.  This is problematic already, as many researchers in Systems Science contest whether people can be modeled in a meaningful way.  GSS needs to consider this challenge deeply and to find a way to engage with these agnostics.  I assume that our models will be imperfect in many ways and this is just one more instance that will require caution in how we interpret our results.

Setting this non-trivial issue aside, I consider cities to be the stages on which immense numbers of interactions take place among people and between people and the Capabilities of the city.  Note:  by “city” I mean some poorly-defined geographic region and by “Capability” I mean any form of public or commercial offering whether product or service to which each person has, in principle, access.  Naturally many capabilities are produced by people, so people and capabilities are intimately intertwined.  Many capabilities also involve the deployment of physical infrastructure, the built environment.  Many of them consume indigenous or exogenous resources and produce waste products.

My inclination is to model the urban systems as very large sets of interactions over many GIS layers.  Grossly simplified these would include:

• The topography of the city
• The fixed resources within this region (arable land, minerals, aquifers…)
• The renewable resources (air, water, soil, natural & domesticated vegetable and animal life…)
• The built environment (major infrastructure, housing, workplaces…)
• The public and private capabilities (government, public safety, healthcare, utilities, education, transportation, industry, commerce, entertainment….)
• The living systems by which each inhabitant or visitor conducts his or her own life through the exploitation of the capabilities thereby creating the social and economic systems

The spatial scales for these layers range from 1m to several km.  The timescales range from less than one minute to several decades.  ICT has roles through these models in supplying the data and algorithms.  At short timescales, in intelligent cities, the ICT sensing and controlling systems allow such models to provide operational decision support to achieve desired outcomes.

An aspect of growing importance in such a model is the interdependencies within each layer and between layers.  These interdependencies are incorporated in urban systems as implicit or explicit assumptions and may have crucial bearing on the resilience of the city when these assumptions are violated.  At long timescale, in intelligent cities, ICT provides the spatially and temporally integrated data that makes visible how the city works and hence what urban design and economic development decisions should be considered.

 

Transforming City, Regional, or Global Governance

Today the methods of providing the Capabilities mentioned above are deeply rooted in the core principles of the Industrial Age.  In short this model consists of:

• Concentrating the mean of production in “factories”
• Producing defined products and services based on historical experience of demand
• Distributing these products and services to an anonymous and invisible group of consumers
• Requiring these consumers to determine how to combine these capabilities to best meet the needs of their lives

There were good reasons in the past for employing this model, including maximising the use of capital, developing pools of low-cost labour, and the absence of alternative management methods.  A key shortcoming of the model is the disconnection between the design and production of the capability and the actual and current needs of the consumers.  It leads to a siloed view of the world in which the service provider is isolated from the short-and medium-term evolution of the city’s needs.

Across many domains, for example media, electrical utilities, and manufacturing, this model is breaking down.  Broadcast media give way to self-selection.  Electrical utilities realize the need to understand and influence consumer behaviour and consumers implement distributed generation for sustainability and resilience.  3D printing enables individuals and small companies to design and produce complex mechanical devices.

Perhaps the great failure of this model has been in transportation, where the private car has largely displaced public transportation which still requires the passengers to organize their lives around the offered capability, instead of the inverse.

The industrial model will not disappear.  Some capabilities, for example waste water treatment systems, do not lend themselves to distributed alternatives.  However, it seems likely that the biggest obstacle for both public and private institutions is the transformations that are required in governance and in management thinking.  In this regard, the Open Data movement is perhaps a step in the direction of external transformation of these legacy institutions in urban governance and management.  I think of this as the analogue of the transformation of legacy software into Object Oriented models through external wrappers.

I imagine that in the coming decades cities will need to be far more agile as they are confronted by the challenges of changing regional and global economies, increased competition for many basic resources, large scale migrations, climate change and its many consequences.  It seems unlikely to me that the industrial model can meet this need for agility.  In the Age of Information we have new models of creating and managing complex capabilities, we have new levels of education, and we begin to have new methods of capital allocations.  What does GSS have to say about such a transition?