The City Collaborative

The City Collaborative

The following is a summary of a talk given by Geoff Mulgan to the Seoul Institute in September 2012:

Over many years I have been interested in what tools can help big cities think through and solve their problems. Visiting many city governments has confirmed for me that their tools for thought and decision-making lag far behind their tools for such things as transport management or infrastructure. The ideal is a city that can mobilise many different kinds of intelligence to help with problem solving, policy and action. There is plenty of activity happening under the label 'smart cities' - but this tends to mean investment in hardware, IT systems for managing infrastructures, perhaps inevitably because of the large firms involved.  It never seems to be smart in a deeper sense. Here I set out some of the ideas for a more intelligent city and how these are beginning to be applied.

One way of thinking about this is to look at the components of intelligence, and how these might be reused at the level of a city (some of this is covered in the paper I co-wrote for Nesta last year on collective intelligence). These include:

  • Consciousness, and consciousness of being a self or agent
  • Reflexivity - the ability to observe one's own thought processes
  • Observation - the ability to see, hear, smell the world
  • Attention - the ability to focus
  • Cognition - the ability, or abilities, to think and reason
  • Creation  - the ability to imagine
  • Memory - the ability to remember
  • Judgement - the ability to judge
  • Wisdom - the ability to make sense of complexity and to integrate moral perspectives

So how do any of these look at the level of a city?

Accurate observation - a first step is knowing what is happening, in as close to real time as possible, to everything from crime to business start-ups and jobs.  This will include:

  • Statistics
  • Commercial data
  • New methods such as Global Pulse analysis of Twitter to predict unemployment
  • Shared tools - such as city level equivalents of Intellipedia, the wiki used by US intelligence agencies for nonclassified information
  • Sensing systems - for air quality, traffic flows etc, all set to be revolutionised by the Internet of Things

Accurate diagnosis - then there is the ability to make sense of shifting patterns.  Cities contain enormous brainpower but it is used in very inefficient ways, situated in research institutions, university departments etc without effective linkages to action.

The missing piece is active orchestration of analytic and diagnostic capacity - through commissions, formal research collaboratives and actively run networks. The Strategy Unit model I helped develop - linking into a network of researchers inside and outside the system is another. Wikis can play a role, as can taskforces and surveys - the key is the orchestration of this knowledge so that it is easily accessible, combining face to face and online interaction.

Wise decision making - the ability to make good judgements in conditions of uncertainty.  This can be helped by evidence centres - orchestrating knowledge about what is working or not, and in every field there is a need for a map of what's proven, what's promising and what's possible, informed by judgement.

  • Proven models can be found through - formal evidence scans. Project Oracle as example, early intervention
  • Promising ones can be found through scans of emerging practice, a role for networks like SIX
  • Possible ones can be defined through- the more creative exploration of ideas worth developing and testing, through methods like camps, incubators, accelerators, crowdsourcing and prizes.

These then need to be drawn on by people with experience and a feel for what actually works, politically as well as practically. Decision making still has to rest with elected leaders and their officials, and of course there is a whole science (or probably more accurately, a craft) relating to effectiveness and wisdom in judgements and leadership.  The further we move away from data the more these intangible, qualitative judgement capacities become key.  Involving people with direct frontline experience in decisions is important (most governments make the most important decisions with no one in the room who has direct knowledge of the topic); as is tapping into experience of past successes and failures, as well as lateral perspectives and 'beginners mind'.

The London Collaborative

The London Collaborative tested some of these ideas but on a small scale and with only partially engaged governance. Its aim was to bring together three tiers of government - national government which controlled most public spending in the city; the Mayor and Greater London Assembly; and the 32 boroughs which were responsible for many key services such as education. It was funded by the London peak bodies, led by the Young Foundation and also involved the Office of Public Management and Common Purpose.  The idea was to encourage more effective common problem-solving through:

  • Joint events to create a community of leadership - with the 600 or so leading public officials taking part in events together, some also involving business and civil society
  • Working groups focused on problem solving and innovation, specifically on workless households, retrofitting and behaviour change - drawing on the energy of younger officials, who then had to pitch ideas to groups of chief executives
  • Future oriented scans and events
  • A web space for collaboration

Looking to the future we envisaged many new elements

  • Open data stores - which have now largely been achieved
  • Wikis for the main public agencies to share information and knowledge - for example on economic conditions in parts of the city, gangs, transport (Intellipedia was one of the models for this)
  • A much more systematic clearing house for commissions from academics in the main universities, including regular sessions linking decision makers and researchers on topics such as public health or gang violence.
  • A rolling process of strategy development for key crosscutting issues, ideally with mutually transparent plans, data etc across the different tiers and agencies

Despite support amongst many of the key chief executives, the peak bodies were lukewarm and saw this as an institutional threat and moved to kill it. I became convinced that in the near-term only an unusually intelligent and strategic mayor would be likely to grasp the value of such a system, although in the future, systems of this kind might become the norm.

At the time I asked many people involved in city governance around the world what parallel solutions there were to the challenge of how to help the city to think, and make the most of its thinking resources.  Many had research institutes; strong relationships with groups of universities; and the beginnings of sophisticated open data. But I couldn't find any that had anything resembling a collective intelligence system, and most were bedevilled by tensions between the tiers of government. So the task of creating the world's first intelligent city remains undone.