CITIES, like all human systems, are enormously complex.
But it was not always so. Until about 12,000 years ago, people lived in small nomadic groups as hunter- gatherers.
Then, during the Neolithic Revolution, agriculture emerged and people began to produce food, instead of just hunting for it. The nomadic life of the hunter-gatherers began to be replaced by more sedentary societies based in human settlements like villages and towns. Villages and towns grew into cities over time.
The urban milieu became the catalyst for the development of a multitude of new human capabilities. Over time, people were no longer just hunters or farmers. They became builders, craftsmen, businessmen, entertainers, teachers, scholars, and so on.
As inhabitants of towns and cities took on increasingly specialised roles, and as cities grew, social and economic complexity increased.
But the human impulse is to reduce complexity. The complexity that began to emerge in towns and cities created an imperative for a new form of organisation - government - to manage it. An early, rudimentary form of government was the council of elders, which governed through consensus rather than imposed rules.
But cities evolved, they grew larger and more complex. Furthermore, ambitious rulers began conquering other cities and extending their reach of power. The challenges of controlling geographically diverse and complex cities demanded a more sophisticated form of urban governance than just the council of elders.
Establishing rules to manage complexity
THE Code of Hammurabi, dating back to around 1754BC, provides clues as to how early civilisation managed urban complexity.
The code comprised some 282 laws covering a variety of subjects. It prescribed punishments for those who flouted it. Through the code, King Hammurabi maintained political order and managed the complexity arising from the different practices, precedents and norms in the Babylonian empire.
What is interesting is the way in which the code appears to have promoted economic freedom and diversity: the code paints a picture of an economy driven by private property, as the king did not own any land.
The code was an instrument to manage an early form of capitalism. Today, we recognise in it many aspects of the modern economy: the enforcement of property rights, the protection of the weak against the strong, and the use of commodity as money and credit. The code freed up the economy, which in turn promoted long- term growth.
Literacy, political structures, levels of industrialisation, and per capita income are conventional indicators of economic health. However, the economists Ricardo Hausmann and Cesar Hidalgo have suggested that the most important predictor of growth is economic complexity, or the diversity of products that an economy possesses.
Countries with the most natural resources tend to have simple economies, as they do not produce unique goods. Thus, economies that are dependent on a particular kind of export - for example, oil or timber - may do well when demand for these products is high, but fail in the long run because they are not diversified and cannot compete in other sectors.
A case in point is Detroit, a city that built its fortunes on the auto industry. Detroit became highly reliant on the auto industry. But after World War II, automakers began to move to suburban areas, outside the city proper. This in turn led to residential movement to the suburbs. From a peak of 1.85 million in 1950, Detroit's population today is less than 700,000, a decline of more than 60 per cent. Population flight led to a loss of tax base and jobs. Detroit declared bankruptcy in 2013, and its unemployment that year was 23.1 per cent.
Catalysing complexity: the case of Boston
THE ability to produce unique goods and services depends on the amount of "productive knowledge" in an economy. This is the kind of knowledge derived from experience and exposure to different sectors and domains of production.
Invention and innovation occur when these bits of productive knowledge are connected. Improvements to economic growth can be achieved either by harnessing existing capabilities in new combinations, or by accruing new capabilities to expand the productive potential of the country.
So, urban governance is not all about reducing complexity. Instead, in some cases, it should catalyse complexity, by creating more networks to connect multiple economic domains.
For example, in contrast to Detroit, Boston is a city that was shocked and surprised, but then reinvented itself, at least three times in its 400-year history.
Harvard economist Edward Glaeser tells of how Boston, in the 17th and 18th centuries, was the leading port in America. But by the mid-18th century, Boston as a port had been eclipsed, first by Philadelphia, then by New York.
What saved Boston from the fate of other New England ports was a large population of Irish immigrants. By the late 19th century, Boston had transformed itself into a centre of manufacturing built on immigrant labour, and it prospered on the back of America's industrialisation.
But Boston's heady period of growth was over by 1920. Population growth slowed and even began to shrink after 1950.
However, in the last two decades of the 20th century, Boston again reinvented itself, this time from an industrial city in decline into a high-tech, service-based economy. Its population grew rapidly between 1980 and 2000, reversing 50 years of stagnation and shrinkage.
Boston is now a centre of the information economy. Today, education is the dominant factor in Boston's economy. Boston ranks highly in its share of employees in managerial and professional jobs. Its top four export industries today are all skills-based: technology, finance, education and health care.
Using the lens of economic complexity, the Boston case shows us that the ability to re-orientate and create new value hinges on economic complexity.
From its earliest days, Boston was never just a port. Artisans manufactured some of the goods traded on Bostonian ships. Boston had banks, brokers and insurers from its seafaring days because shipping needed financial services. Education was always valued in the colony - Harvard University was founded in 1636 with government money.
Its rich, complex strengths and competencies enabled Boston to reach within itself to find new connections and value propositions. These enabled Boston to reinvent itself time and again when other more brittle, less economically complex cities like Detroit, heavily dependent on manufacturing, went into terminal decline.
URBAN planning in Singapore needs to take into account the complexity of packing in housing, green space, industrial land, commercial and retail space, land for transportation needs, and military training areas, all within the confines of a small island of 718 sq km.
In Singapore, the entire process, from the review of our strategic Concept Plan to the implementation of a detailed land-use Master Plan, involves close collaboration among economic, social and development ministries and agencies, as well as consultations with various stakeholders in the private sector and the public. This whole-of-government approach enables all stakeholders to better understand the interdependencies and implications of land use and strategic decisions. One example of the approach in coordinated and strategic land use is the Marina Barrage. It is a huge fresh-water reservoir created by damming the mouth of the Singapore River. It is located right in the middle of the Central Business District, an astonishing achievement considering Singapore's small size. Yet it had been planned more than 20 years ago, because the policymakers and urban planners understood even then that issues such as climate change and increasing demand for water would emerge in the future.
Today, the Marina Barrage serves multiple functions. It alleviates flooding in low-lying city areas by keeping seawater out, and boosts Singapore's water supply by storing rainwater during the monsoon seasons. It is also used for recreational water activities.
Big data and complexity science
THE agents within a complex system like a city - the people, public and private institutions, markets and networks - all generate a lot of data, much of which is location-based. Combined, this constitutes what we now refer to as big data. Complexity science offers a way to marry different tools - such as agent-based modelling that is used inter alia for traffic flow dynamics, combined with insights from big data using data analytics - to gain a better understanding of the city in all its complexity.
The tools of complexity science combined with the insights from big data can help us to "see" the city differently, through new lenses. What then are the fresh possibilities to "imagine" and "shape" a different and better city for the future? And if we can imagine a different city of the future, we can take active steps towards realising it.
We could imagine driver-less taxis that allow shared trips to reduce pressure on the roads while meeting passengers' demand.
We could also imagine traffic lights that change in response to traffic conditions that are monitored by sensors on the roads.
In societies that are rapidly ageing, like in Singapore, this could mean placing a network of sensors in the elderly's homes, which could monitor and track their daily living movement and patterns, and send out alerts to family members or neighbours when they deviate from daily norms, such as the frequency of use of the toilet, fall detection, and so on.
The complexity of cities needs to be managed. Too little complexity can lead to brittleness. The right level of economic and social complexity that gives a city the resilience of say, Boston, is partly due to good luck, but mostly due to good governance.
The example of Boston teaches us that nothing is forever, and that the most adaptable and flexible cities are the ones that will survive and succeed over the long term.
The writer is senior adviser to the Centre for Strategic Futures, set up by the Public Service Division to develop public sector capabilities for future strategic challenges.
This article is adapted from a speech delivered earlier this month at a workshop on Understanding Complexity - Offering Solutions To Problems Of The 21st Century in Vienna, Austria.