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  • Geoff Mulgan

Thinking systems

This draft paper describes methods for understanding how vital everyday systems work, and how they could work better, through improved shared cognition - observation, memory, creativity and judgement – organised as commons.

Much of our life we depend on systems: interconnected webs of activity that link many organisations, technologies and people. These bring us food and clothing; energy for warmth and light; mobility including rail, cars and global air travel; care, welfare and handling of waste. Arguably the biggest difference between the modern world and the world of a few centuries ago is the thickness and complexity of these systems. These have brought huge gains.

But one of their downsides is that they have made the world around us harder to understand or shape. A good example is the Internet: essential to much of daily life but largely obscure and opaque to its users. Its physical infrastructures, management, protocols and flows are almost unknown except to specialists, as are its governance structures and processes (if you are in any doubt, just ask a random sample of otherwise well-informed people). Other vital systems like those for food, energy or care are also hardly visible to those within them as well as those dependent on them. This makes it much harder to hold them to account, or to ensure they take account of more voices and needs. We often feel that the world is much more accessible thanks to powerful search engines and ubiquitous data. But try to get a picture of the systems around you and you quickly discover just how much is opaque and obscure.

If you think seriously about these systems it’s also hard not to be struck by another feature. Our systems generally use much more data and knowledge than their equivalents in the past. But this progress also highlights what’s missing in the data they use (often including the most important wants and needs). Moreover, huge amounts of potentially relevant data is lost immediately or never captured and how much that is captured is then neither organised nor shared. The result is a strangely lop-sided world: vast quantities of data are gathered and organised at great expense for some purposes (notably defense or click-through advertising)

So how could we recapture our systems and help them make the most of intelligence of all kinds? The paper shares methods and approaches that could make our everyday systems richer in intelligence and also easier to guide. It advocates:

· A cognitive approach to systems – focusing on how they think, and specifically how they observe, analyse, create and remember. It argues that this approach can help to bridge the often abstract language of systems thinking and practical action

· It advocates that much of this systems intelligence needs to be organised as a commons – which is very rarely the case now

· And it advocates new structures and roles within government and other organisations, and the growth of a practice of systems architects with skills straddling engineering, management, data and social science - who are adept at understanding, designing and improving intelligent systems that are transparent and self-aware.

The background to the paper is the great paradox of systems right now: there is a vast literature, a small industry of consultancies and labs, and no shortage of rhetorical commitment in many fields. Yet these have had at best uneven impact on how decisions are made or large organisations are run.

In the paper I show the relevance of some of the methods I suggest for governments seeking to better address challenges such as decarbonisation and care for the elderly; in relation to business I suggest that the West has tended to fall behind China in terms of designing and operating complex, interconnected systems straddling many fields, an ability which will be vital for the future of finance, energy and transport; and for citizens, I emphasise how greater influence can be achieved over systems which are now surprisingly opaque.

In summary I argue that although we live surrounded by systems we struggle to understand them let alone to guide and control them. I believe we need a novel approach that focuses on how to enrich and open up the shared intelligence of the systems around us. This is the next step to take – building on the extraordinary achievements of the Internet itself, open data and other movements, and taking us to a world where there are accessible representations of the multiple systems on which we depend. My aim is to suggest some of the tools, insights and resources we could use to do this. The paper is shared as a first draft to elicit comments and improvements.

The full paper can be found here:


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