Frequently, we talk of the ‘elephant in the room’ to refer to some threat or phenomenon which is not discussed. There is often an implicit taboo on discussing the elephant because, once it is recognised as such, it can no longer be ignored. This article discusses the elephant of economic collapse.

The last global economic collapse occurred in the 1930s, following the Wall St Crash of 1929 which led to the great Depression.

Are we due another collapse of similar proportions? How has the world changed in the past 90 years? Are people, families and communities more or less vulnerable to that type of depression? Do we have an economic system which is more or less resilient than back then? What do we have in our policy armoury to resist or respond to such a financial calamity? Are recent market jitters, reverberating around the globe, heralding something more than temporary retrenchment in a long-term upwards trend? In the context of history, these are very important questions which few are addressing. This is a huge elephant.

This article won’t address these questions but it will explain why our existing means of understanding macro or global risks are incapable of anticipating the possibility of economic collapse and addresses the question: Do we currently have the requisite structures and processes in place to accurately identify and assess macro risk?

We face macro risks in common. Should collapse come, no one will be immune and yet our structures and processes to assess macro risk are competitive rather than collaborative. Yes, superficially, we pay lip service to the idea of collaboration within industry bodies and other frameworks but, at the end of the day, we are rewarded when we are perceived to be better than our peers or competitors and penalised if we are not seen to be ‘winners’. This is hardly conducive to open cooperation.
We are reliant on others to understand how our ‘piece of the puzzle’ fits into the overall picture of the political economy

Few of us are polymaths. Consequently, we are reliant on others to understand how our ‘piece of the puzzle’ fits into the overall picture of the political economy. We take information on trust from people and organisations that are similarly confined, often without exploring how they derived their analysis or came to their conclusions.

How many of us can really claim that we can see the whole elephant? In the story of the six blind men of Indostan, each of them grasps a different part of the elephant’s anatomy and tells his peers what an elephant is, based on limited information. None of them can agree because they aren’t cooperating to describe the elephant but competing.

Furthermore, the institutions and individuals we rely on for data and information have a vested interest in preserving the status quo within their sphere of influence. Cumulatively, that means no one will think the unthinkable or challenge accepted wisdom because it would be like ‘turkeys voting for Christmas’.

Yes, there are competing views but these tend to lock us into the realms of binary ‘groupthink’ in which views polarise between opposites: Keynes versus Hayek; Capitalism versus Socialism; true versus false; right versus wrong. Yet life and systems are seldom binary but complex, ambiguous and nuanced. Clearly we’re ill-equipped to account for subtlety or ambiguity when we’re locked into opposing viewpoints or agreeing with others on a relatively simple, binary proposition.

We are further hampered by the sheer volume and complexity of information, much of which we don’t see because it resides in places we don’t look. To take a simple example: we look at officially reported inflation figures and base many assumptions and decisions on these. Yet, if we were to talk to people in the street about their weekly budget and the real inflation they experience, we’d arrive at a very different answer. How does one translate the cumulative experience of millions into an inflation figure? We abstract data and make relatively simple, probably outdated and inappropriate assumptions to arrive at a figure which is likely to have no foundation in reality. There are many other examples one could cite.

Co-creative learning

How do we overcome the obstacles experienced by the blind men of Indostan? How do we gain multiple perspectives on the political economy to understand it well enough to anticipate and respond to the possibility of economic collapse and global depression? By learning co-creatively rather than competitively. Co-creative learning is described as learning unfettered “by the incentives, penalties and limitations of established education practice … to unleash human creative potential”.

What we find in co-creative learning is that there is a geometric progression of understanding. The power of this learning is evident in free, open source software and other examples, such as Sugata Mitra’s experiments in self-organised learning among illiterate slum children in India who learnt about genetics in six months.

There seems to be a factor in co-creative learning which is difficult to describe in words. One is barely aware of progress while learning co-creatively but documenting, recording and sharing work as we learn reveals the rapid development of our understanding. Done right, the results of co-creative or self-organised learning are impressive. We know it works but only by doing it yourself can you appreciate its power.

The free, open source CoCreative learning project offers a guide on forming and operating a co-creative learning group, to asses and evaluate macro risks in the evolving political economy. Through collaboration and cooperation, openly reviewing and sharing information, we can work to identify the ‘elephant’ from multiple perspectives.

A number of macro risk learning groups, operating autonomously but interdependently, would result in an ‘ecology’ of expertise to anticipate economic collapse and identify what steps we need to take to prevent or respond to that possibility.

Information on the free, open source CoCreative Learning project