Many would argue that standard economic theory enabled us to analyse and understand the economy as it used to be,
with long stable periods punctuated only by occasional crises. However, the recent evolution of the global economy should drive us to pursue ways of expanding economic theory
such that it encompasses the new structures and organization
emerging as we globalize and network our world.
This is from a great new paper by Dirk Helbing and Alan Kirman, which asks and attempts to answer many questions that are of importance to development, and answer them by drawing on ideas from complexity theory. Well worth a read.
As concern grows about H7N9 in China, this post explores the importance of managing such pandemic risks through collaboration, innovation and systemic thinking
In the month of World Health Day (April 8th), the latest outbreak of bird flu in Asia provided a sobering sense of the challenges the international community still faces. To date, H7N9 has killed 21 people, infected 104, shut down poultry markets across Asia, and has led to Chinese shares tumbling.
The WHO originally announced that the likelihood of this latest pathogen is transmittable between people is low, and that the world should not ‘get into a flap’ – as one observer memorably put it. The potential of bird flu to be the source of the “Next Big One” means however that we cannot be complacent. In terms of global catastrophic risks, it is hard to think of one more serious than the 1918 avian influenza epidemic which killed 50-100 million people worldwide – 3-5% of the global population. This was so devastating in part because the virus had acquired mutations that allowed it to cross from birds to humans, and then to ‘go pandemic’. Based on analysis of the mutations in H7N9, scientists fear that this latest variant may have the same potential.
But there is still a lot we don’t know about H7N9. Where has it come from, why, and how? What is its relationship to earlier variants? How might it mutate? What impact might it have in the future? What does it mean for our ongoing, historically loaded, battle with avian flu?
To answer such questions, we need to draw on a variety of disciplines: epidemiology, molecular biology, virology, all of which fit nicely with the current models of public health. The problem is that many of these models set us, humans, apart from nature. Diseases, the standard narrative goes, encroach on our territory and we need to fend them off. The reality is in fact the exact opposite.
It is now widely acknowledged that many – the majority, in fact – diseases are born in the intersection between society, environment and economy. More than 2/3 of all human infectious diseases are zoonotic in origin, meaning that they somehow crossed species boundaries. The terminology likely to be adopted in future Hollywood blockbusters on the topic is simple but evocative: ‘spillover’. Primates, birds, bats, pigs, rats, mice, dogs, insects – any creature we co-exist with can act as sources or carriers of pathogenic lifeforms.
Spillover is driven by a pattern of activity which is becoming all too familiar. Deforestation: 4% increase can lead to 50% increase in malaria rates. Hunting has led to HIV-AIDS, Ebola, all crossing the species boundary. And, to bring it back to bird flu, livestock. Around 70% of the rural poor and 10% of the urban poor are dependent on livestock. Livestock conditions are increasingly creating tremendous opportunities for pathogens to cross from wild birds to caged birds, and onto humans. And the demand for animal-based protein is expected to grow 50% by 2020, much of it in the developing world. This problem is not going to go away any time soon.
Ecological and evolutionary principles are vital in understanding these complex system effects on a more solid scientific basis. Experts at the University of Florida made the point in pithy fashion a couple of weeks ago, “If we don’t understand the reservoir and the ecology of the virus, it’s hard to design interventions to protect humans.” But such understanding is – with a few exceptions – still under-utilised in public health.
Of course, every disease is different, every context is unique. But the process by which spillover happens is similar. We can point to ecologies under stress. Life forms under duress. As an excellent briefing by colleagues in the Consortium on Disease Dynamics (CDD) puts it, “The health of people and animals are… interconnected and inextricably linked to the environments both inhabit. Given the complex pathways that lead to spillovers, it is important that prevention and control measures are undertaken with a strategic approach and an understanding of the many interdependencies.”
What does this challenge add up to for the global risk management community? The work by the CDD gives some very useful pointers.
First, multi-disciplinary approaches are vital. The WEF Global Risks report has for some years now been calling for better disciplinary collaboration in order to think about emerging risks. With avian influenza there is a clear need for better collaboration between public health specialists, disease ecologists and evolutionary biologists. Some important work is already happening, under the auspices of entities such as the global One Health initiative, organisations like the EcoHealth Alliance, and initiatives like the USAID-funded Predict, and this work needs to move firmly to the centre of the debate.
Second, anticipation and warning systems – new investments in surveillance are urgently needed to establish and maintain necessary systems at multiple levels – community, national, regional and global. We need multi-stakeholder information platforms, bringing together government, civil society and the private sector in new kinds of networks, in order to establish ‘systemic surveillance approaches’. This needs to move beyond a focus on specific disease to looking at the whole system, looking at the intersection between disease drivers, disease incidence, and socio-economic factors.
Third, new approaches – especially in the realm of complex adaptive systems – have a lot of relevance for how we think about such outbreaks in the future. Methods such as systems thinking, network analysis, agent-based simulations, and dynamical systems theories can help develop a more precise and accurate understanding of the complex dynamics of disease. Together with the rise in ‘big data’ approaches, there is scope to develop new models and theories of how pandemics unfold which are more appropriate to our ‘hyperconnected world’. We need to be careful however to ground this science in local, community understanding – to support affected communities to become the frontline of defence: adaptive managers of emerging risks.
Fourth, we need changed funding models – funding prevention, not just response, and linking pandemic risks to high-risk development activities, and ensuring that we don’t forget history too quickly. There needs to be attention even when the threats may not be imminent. The private sector, with interests in business continuity, can be key actors here. Done right, such investments can engender what might be seen as positive spillovers. As the CDD work suggests, investments in prevention of avian influenza can provide the basis for such work on other potential pandemics.
In closing, if we want to take a wide-angle lens on the problem of disease outbreaks like HN79, to understand why these diseases are occurring at an increasing rate, we could do worse than taking a lead from Nathan Wolfe. A globally renowned virologist, a couple of weeks ago Wolfe wrote a tub-thumping piece on the WEF blog about the continued risks of unregulated hunting, especially bushmeat, which gave birth to human immunodeficiency virus (HIV). His basic argument was by ignoring the implications of our food production systems, we are running an unacceptably high risk of terrifying global scourges in the future.
Clearly, we all need to start pay much more attention to the intersection of economy, society and the environment if we are serious about proofing ourselves against the Next Big One.
Many people around the world were deeply saddened to hear of the death of Elinor Ostrom in June this year. By way of a tribute, this extended piece brings together some of her ideas on the implications of complexity science for development aid. It draws on material from a series of interviews I conducted with Professor Ostrom between 2009-2012 for use in my forthcoming book, and has been approved for publication by her colleagues at The Workshop, Indiana University.
When Elinor Ostrom won the Nobel Prize in 2009, the Swedish Royal Academy of Sciences made the following statement:
[she] has challenged the conventional wisdom that common property is poorly managed and should be either regulated by central authorities or privatized. Based on numerous studies of user-managed fish stocks, pastures, woods, lakes, and groundwater basins, Ostrom concluded that the outcomes are, more often than not, better than predicted by standard theories.”
Challenging standard theories was a running theme Professor Ostrom’s work. Ideas of the commons and how they really worked were central to this, as was the analysis of institutions and the sustainability of social-ecological systems. Complexity was a particular interest: ideas of systems, self-organisation, the evolution of rules, institutions as emergent phenomena and resilience are all repeated motifs in her papers, books and speeches. Indeed, her 2009 Nobel Prize Lecture – she was the first and, to date, only woman to win the Economics Prize – builds on the distinction between simple and complex human systems, and closes with the following words:
We should continue to use simple models where they capture enough of the core underlying structure and incentives that they usefully predict outcomes. When the world we are trying to explain and improve, however, is not well described by a simple model, we must continue to improve our frameworks and theories so as to be able to understand complexity and not simply reject it.
She was on the Santa Fe Institute (SFI) Science Board for five years. Corresponding in 2011 while I was visiting the Institute, she wrote to tell me that it was one of her favourite places in the world. It is easy to imagine how the SFI approach naturally appealed to someone who had spent her life’s work breaking down disciplinary boundaries.
My small-scale engagement with Professor Ostrom started in 2009 following the publication of a report on complexity science and aid I led on while at ODI. She used it as reading material for her students in Autumn 2010 and kindly wrote back to tell me how useful she had found it. We subsequently had telephone and face-to-face interviews on the topic of complex systems, development and aid. These discussions, and of course her rich body of work, helped to shape the ideas in my forthcoming book, which she warmly encouraged from the outset. I have used material from these interviews to write this post.
*
What is your view on complexity and the complexity sciences? What is the value of this approach?
I get so upset when people use complexity as a reason not to do things – complexity and context are essential for operating in many different situations. In order to make sure decisions are relevant, we have to understand the context of decisions, and the complexity of the situation. My take on complexity is that it is a key set of concepts which are essential for understanding how the world works. There are many situations where simple models don’t work – when there are 10, 15, 20 variables. For example, think about situations where problems are nested within each other or situations where there are many actors capable of actions, conflicting information about transmissions and payoffs and diverse outcomes. Here, the ideas of complexity can lend a hand by providing a means of analysis and understanding the reality of these action situations.
How would you apply these ideas to international aid agencies?
The last thing aid agencies want to do is analyse things as a complex system! (laughs) But how do you unpack systems without such analyses? In biology and ecology, there is a necessity of using complexity science and related ideas as a model – although it is not always acknowledged, they do have to use it. For example, in a situation with 10, 15, 20 species, how do you understand the potential impact of the elimination of one species, when one unit being eradicated would cause disaster rather than simply being important. We can’t address these questions without drawing on complexity theory in some way.
The lack of long timeframes and a lack of supporting cultures means that aid agencies don’t help people learn how to think about and change the structure of the situations they are facing. In many situations, this is because of colonial roots of aid, which did not respect local institutions – they didn’t understand them so they were treated as non-existent.
The difference between this approach and that of Darwin is stark – the care and diligence that was given to studying animal species in the 19th century is so evident, and it from this that we have evolutionary theory. But these countries also had people, but there was no attempt to understand their knowledge systems, the rules they had developed to manage various kinds of socio-ecological systems… Colonial powers assumed we have the answers, and destroyed social capital. Aid agencies, unfortunately, do much the same thing.
What are the biases of development aid that you see inhibiting the take-up of a more complex, realistic way of doing things?
Development aid asks the question: where can we pour money in to make the most difference in the most visible way (laughs). This is not especially amenable to complex ways of understanding the world. Most projects are 2-3 years, some are 7, but these are big engineering projects, and then they disappear.
‘Fitting’ is all important in this context. Many agencies today have blue prints for situation A, but they are so ingrained they can’t deal with B, C, D and E. Some employ very inspiring young people, but they are not keen to stay long in their organisation – 4-6 years max, they tend not to be sanguine about the future. This is understandable, but it also goes against what we know about bringing about social change.
Take the Sida work. We said, we want to understand the role you play in sustainable development – tell us what your best projects are. And we found that their best projects were relative failures because of exactly these issues.
The most fundamental change is to change the social science curriculum to change the way that development is taught. We need to get away from treating governance as top-down. The presumption of almost all work is that a hierarchy will work effectively, gather information from variety of sources and develop tactics of behaviour. In complex systems, there are many different areas, all moving in different directions and at different speeds, doing localised things which are relevant. The idea that a central processing unit that can gather up all of this information and make decisions about the whole system… the theories fall down.
I developed a framework to understand complex social-ecological systems, which builds on my work on governing the commons. This sets out the key design principles for complex systems which sit on the interface of society and ecology: watersheds, fisheries, increasingly the whole planet. Some of the reaction has been very enthusiastic – some people, the biologists, the ecologists, the complexity scientists, love it. Others hate it, they say it’s not science, it’s too complex.
What examples do you see of good development practice, which do take account of complexity?
I was at a conference recently in the north of Sweden, for the Childbirth Foundation, 1000 young people from 100 countries. They were trying to answer the question – how do you change the way the world works to develop more opportunities in developing countries. There were lots of ideas, using the market, ideas like cooking stoves and many others, all aimed at the broader goal of dealing with climate change, bringing about development. Some of these ideas have already been applied; some are still being tried out. But the key is that they are doing development in a way that has a chance of working.
And there were no international development agencies present. They should have been there, just to see what was being discussed. The key difference was that while international development agency way of thinking has seen a lot of failure, they haven’t picked up yet on the answer, which is that we must have multiple approaches, small and experimental and larger and more concrete. But apparently the taxpayer doesn’t like to see experimentation with their money!
Aid agencies tend to not involve staff in anything other than a project, and sometimes only for part of a project. And when the project ends, they leave. Mr Shivakumar, a colleague who worked on the Samaritan’s Dilemma, has done work with Action Aid in their Ethiopia programme. They will go to a site where they are trying to help farmers build up their capacity, say for public services. They are there for some time, but they try to do something 5 years before they are going to leave. They will call a meeting and say ‘we will fund 1 year for 100%, after that, we will drop to 80%, and you need to support 20%, then down to 60%, and so on… If we are doing something good, then you should want to carry it on. If not, that’s fine, the project closes. That is an example of an aid philosophy that takes account of complexity.
Look at Grameen Bank, that started off slowly, and if it was cut down after 2 years it would never have turned into the institution it is today. But it worked because it was a system within a system within a system. It didn’t have public official waiting for a report on a Friday afternoon before they could go home. It had lots of people in localised situations who presented and developed rules for how things would work, providing some basic structure for example, you have to meet every week, we have to put money on the table, we have to be forgiving at times… These small-scale units proved to be very innovative and creative. Small-scale units can be very adaptive in changing – look at family units when a child arrives, or a job changes. They can deal with the complex, but they are guided by a different philosophy to development agencies. They don’t have to come up with winning solutions, they can learn from their own successes and diversity of other approaches, they can change things if they are not working.
There is a growing interest in resilience in development circles. Do you see this a promising line of enquiry?
Resilience and sustainability are very similar – these systems have similar properties. It is another attempt to get this kind of thinking into institutions, and just the latest one. The work of the Stockholm Resilience Centre is very important here, and they have been successful in influencing a number of research agendas. But I think a lot of the time policy people are just using the language without knowing what they are talking about (waves hand in mock exasperation). When I did my work on social-ecological systems I was very careful to build on the work of ecologists and social scientists, so it was a truly integrated framework. The trouble with much of the development policy work around resilience I see is that so much of it doesn’t really try to engage with the science of resilience, but instead uses as a catch-all to further particular institutional interests. We need some real serious thinking on this issue if it is going to make a meaningful contribution.
What do you think are the implications of the science of complexity for big conferences like Planet Under Pressure and Rio+20?
We are lucky that there is growing interest in this area, from academics and researchers across the world. The work you have been leading on your book – I think this is work of immense value and importance for the development sector. The crucial question is whether international agencies are ready to hear the message and willing to act on the lessons. I know there are others leading similar work in other closely related sectors like environmental sustainability, community development and social entrepreneurship – about the complexity inherent in different resource systems and under different rules.
We need a broader approach to these systems. What we are lacking at the moment is a shared framework. Without this, how are we to ensure our knowledge accumulates? A shared framework of complex systems can help us ensure knowledge in these different fields is not isolated. There are more people working on this, and they are working together more, but not enough is being done yet.
What do you see as the key to the success of Rio+20?
There needs to be more connection around this challenge through a shared lens of complex social-ecological systems, and these large-scale events provide an opportunity to do this. The key principle informing all of this has to be taking a more evolutionary, polycentric approach to policy making.
This is the key challenge we face, and it is only going to grow with time. I am hopeful though. If there is one thing I think I have learned it is that just because we have a certain emphasis in our institutions today, it doesn’t mean we are stuck with it forever.
What three things would you change among aid agencies to get them to take more account of complex realities?
The number one thing is the ‘spend it or lose it’ mentality – it is common to most bureaucracies, but getting it changes is essential if aid is going to be tailored to the complex realities of development. This institutional change will allow many others to come about, and so it is a very important one.
Number two is getting aid agencies to be more of a learning enterprise and less of a doing enterprise. This means feedback, training, reflection. This means not assuming we have the answer. We need to create an environment where discussion and debate are openly welcomed, and where redundancy is not always seen as bad, just excessive redundancy.
Third, we need to reward people for developing imaginative ideas that draw on the complexity of the real world, that leave people in developing countries more autonomous, less dependent, and more capable of crafting their own future.
*
There are of course many tributes to Professor Ostrom, by people far more qualified than me to write them. For my own small part, I feel grateful to simply to have known her: for her time and support; for how generous she was with the benefits of her towering intellect; and for her gentle, playful sense of humour. The fact that someone of her stature could take the time and care to engage with and mentor me and so many others like me around the world speaks volumes about the extraordinary person she was.
She will be deeply missed – as the Indiana University president said in his statement, we have “lost an irreplaceable and magnificent treasure”.
“We have to think through how to choose a meaningful life
where we’re helping one another in ways that really help the Earth.”
Dr Brian Levyis a Public Sector Governance Advisor at the World Bank, andused to head up the unit responsible implementing the Bank’s governance and anti-corruption strategy.
In this guest post, cross-posted from here, he explores the relevance of complexity theory insights for South Africa. A fascinating read.
The edge of chaos is the balance point where the components of a system never quite lock into place, and yet never quite dissolve into turbulence, either…The edge of chaos is the constantly shifting battle zone between stagnation and anarchy, the one place where a complex system can be spontaneous, adaptive and alive…”
M. Mitchell Waldrop, Complexity.
We human beings do not like uncertainty. We seek to understand what events portend, taking comfort in coming up with an answer. So whenever something new in South Africa makes headlines – and that’s been happening quite often recently, the news not always happy – people ask me, “What do you think? Is the political settlement falling apart?”. And always, the expectation is for a definitive answer, one way or the other.
Yet sometimes there is more wisdom, and more comfort to be taken, in acknowledging a more humbling truth – that which of many alternative futures (including ones we cannot imagine) will come to pass is unknowable, is a product of decisions and actions that have not yet been made. This understanding of change as something ‘emergent’, evolving, which can unfold in far-reaching yet ex ante unpredictable directions, is the key insight of ‘complexity theory’ – an insight which can offer a useful dose of humility to governance prognosticators.
In a previous post, I described South Africa’s abiding tension between democracy and inequality. As that post suggested, one of the results of that tension could be a rise of patronage, personalized decision-making as to how to share the ‘spoils’ of power. Indeed, the strains on the country’s constitutional democracy are visible in the drumbeat of daily headlines, as I found when I recently spent some time in the country. Consider the following:
Over the past year, the country’s estimable Public Protector, Thuli Madonsela, investigated and made public compelling evidence of corruption on the part of two sitting cabinet ministers, and the chief of police. For many months, President Zuma did nothing – until October 24th 2011, when he unexpectedly fired the cabinet ministers, suspended the police chief, and announced the appointment of a judicial commission to re-investigate long festering allegations of corruption (including against himself) in a weapons procurement deal.
Then there’s the populist demagoguery of the leader of the ruling African National Congress’s Youth League, Julius Malema, whose political star, and polarizing influence on South Africa’s political discourse, seemed to be rising – until a disciplinary committee of the ANC announced on November 10th, 2011 that it had found Malema guilty of bringing the ANC into disrepute, and suspended him from the party for five years.
There’s the China connection. Across Africa, a context is raging between China and Africa’s erstwhile Western colonial (and post-colonial) hegemonies – for hearts, minds, natural resources, and business more generally. With its sophisticated institutions, and proud transition to constitutional democracy, it might be thought that South Africa would be unambiguously in the Western camp. So against that backdrop, the failure to grant the global human rights icon, the Dalai Lama, a visa in time to attend the October 2011 80th birthday celebration of his friend, Archbishop Desmond Tutu, is startling – and can best be explained by a desire to curry favor with the Chinese.
Finally, there’s the on-again, off-again – but then on again – Protection of Information Bill which (after numerous delays, and promises of consultation before finalization) was rushed through South Africa’s parliament on 22nd November 2011. Passage of the bill was seen as a catastrophe by many in South Africa’s civil rights community. Indeed, it signals a startling turn away from a post-apartheid commitment to openness. But no less an observer than The Economist, noting that the bill had been ‘vastly improved’ over earlier versions, suggested that some of the doomsday criticism ‘may be over the top’. And, in light of the ANC’s hitherto ironclad hold on the loyalties of its core constituencies, it is surely no small matter that the Congress of South African Trade Unions (a stalwart part of the ANC alliance) has threatened to take the bill to the Constitutional Court if it is not amended to incorporate a ‘public interest’ exception for whistleblowers.
In the face of all of these cross-currents, any claims of certainty as to where this interplay of forces will lead is surely illusory. Each of them could turn out to be a salutary example of checks and balances in action – of how democratic institutions can keep a country on track, even in the face of pressures to the contrary. But they could also be portents of a future that will become increasingly challenging for the country’s constitutional order.
But in South Africa’s case, and surely elsewhere, too. perhaps the lack of certainty is a source of comfort. Knowing that the future is not preordained can free us from endless preoccupation with what is inherently unknowable, enabling us instead to direct energy towards action, in service of a hopeful future that we can, perhaps, yet help to create.
The challenges of achieving global public policy consensus aside, new research is highlighting a range of other pressing concerns that need urgent attention.
Last week saw the launch of the summary of the IPCC special report on ‘Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation’ (SREX). This was the result of a two-and-a-half year long global collaboration between 220 scientists (full disclosure: I was one of the 220 & wrote sections of chapter 6 on managing climate risks at a national level).
One of the key messages of the IPCC report is that existing risk management and adaptation measures need to be improved dramatically. Many countries were found to be poorly adapted to current extremes and risks – let alone those projected for the future.
As recent Stockholm Resilience Centre research shows, this is more than just a technical issue. In fact, the study suggests the time is ripe for a serious rethink of the way resilience and adaptation measures are being designed and implemented.
Resilience is popular. Over the last year, I have being doing an increasing amount work on this ‘big new idea’ in international affairs – for DFID, ODI and others.
While it’s clear that there is a lot of value in this area for development and humanitarian efforts, there are some conceptual and operational challenges that need to be addressed. One widespread issue that I’ve noticed is that while aid agencies are embracing resilience, they are also tending to put the underlying theoretical framework of complex systems to one side as ‘too complicated’.
The study from experts at the Stockholm Resilience Centre shows that such conceptual simplifications of resilience can have considerable downsides – in the extreme, they can lead to interventions that actually diminish resilience.
There are now hundreds (if not thousands) of major public sector initiatives that have been developed in response to climate change, in high, middle and low income countries alike. Adaptation strategies include adjusting economic activities, changing land and energy use practices, and reforms to the design and implementation of infrastructure.
The study authors evaluated nine adaptation policy responses to assess how much they were affecting the resilience of various social-ecological systems. The findings were sobering: ‘Out of the nine initiatives analysed, only three had elements that could enhance resilience as much as reducing it. The other six had effects that predominantly reduced the resilience of a system.’
The reason? Many of the policy approaches to climate risks focused too much on short-term benefits and sought simple technological fixes to problems that were more complex. Such responses, designed with a focus on one single risk factor, can inadvertently undermine the capacity to address other stresses. As the authors put it:
There is growing evidence that current policy approaches… fail to significantly address multiple and interacting factors which affect system resilience and the needs of vulnerable populations.
Such over-simplistic efforts ‘create bizarre distortions in public policy’ precisely because climate vulnerabilities are created through multiple stresses, and not single factors. The problems went beyond how risks were defined – issues of governance, feedback and learning were also identified as critical. As the authors put it:
[In those] situations in which system stresses were defined as narrow, technical problems with short-term horizons… governance structures were top-down, did little to link actors at different scales, masked system feedbacks, and did not provide incentive or structure to promote learning…. In contrast, in the two examples where the issue was framed in a broader manner, policy implementation tended to enhance characteristics that supported the ability to manage resilience, including flexibility and learning.
Is there any explanation for this widespread focus on single risk factors? There are numerous reasons cited in the study. These include:
a desire for readily observable metrics
existing political structures and incentives
entrenched institutional cultures, and
long histories of dealing with social and ecological problems in narrow and limited ways
All these factors have been identified as systemic problems in international aid agencies, both on this blog and elsewhere. Indeed, some of the most troubling manifestations of the push for simplification were to be found in developing country case studies. For example, fisheries management in Uganda and drought responses in Kenya both highlighted the importance of local sources of resilience based knowledge of local ecosystems and social networks. But in both cases, the local sources of potential resilience were diminished by actors and forces operating at wider level.
Given this important new evidence, we are left with what seems like an obvious choice. To paraphrase the study authors, do we want efficient and effective adaptation measures, narrowly and technologically defined? Or do we want strategies that are more open-ended and innovative and seek to build resilience by understanding and strengthening local capacities?
The answer may seem obvious, but as global climate policy debates have repeatedly highlighted, in this realm the obvious choices are often the hardest agree upon. Politics and special interests clearly play a major role, and can all too often inhibit the space for evidence-based considerations.
One would hope that the adaptation issue is less entrenched than the battle that continues to be being waged around mitigation. At the very least, policy makers and practitioners alike need to become more aware of, and work with the key finding of the study – namely that:
dealing with specific risks without full accounting of the nature of system resilience leads to responses that can potentially undermine long–term resilience…”
Ricardo Hausmann of Harvard and Cesar Hidalgo of MIT (whose work I have blogged about previously here) have just published the deeply impressive Atlas of Economic Complexity. It is built around an innovative, network-based methodology for understanding economies and their potential for growth. It represents perhaps the most systematic and in-depth application of the ideas and methods of complexity research to issues of development to date. Readers can download the Atlas and experiment with a powerful interactive visualiser here.
Following an interview with Cesar Hidalgo last week, this extended post explores the implications of this important new work.
I. What is the premise of the Atlas?
The basic idea underpinning the Atlas of Economic Complexity is straightforward. As Hausmann notes:
The fundamental proposition… is that the wealth of nations is driven by productive knowledge. Individuals are limited in the things they can effectively know and use in production so the only way a society can hold more knowledge is by distributing different chunks of knowledge to different people. To use the knowledge, these chunks need to be re-aggregated by connecting people through organizations and markets. The complex web of products and markets is the other side of the coin of the accumulating productive knowledge. [emphasis added]
The secret to modernity is that we collectively use large volumes of knowledge, while each one of us holds only a few bits of it. Society functions because its members form webs that allow them to specialize and share their knowledge with others.”
At the heart of the Atlas is the attempt to measure the amount of productive knowledge that each country holds by applying network analysis techniques to this complex web.
Much standard development – and economic – thinking doesn’t engage very well with the idea of webs and networks. As Hidalgo told me, such ideas run counter to much standard thinking, which seeks to identify differences between individuals and groups based on their inherent qualities – demographic criteria and suchlike. Experts then puzzle over why, for example, communities with the same criteria, or countries with very similar starting points end up with very different development pathways and social and wealth outcomes. It turns out that in many cases, their relationships and networks prove to be a key differentiating factor. If the data is available, it is possible to develop very precise and rigorous analysis of these differences.
II. How does the Atlas work?
So how does the Atlas make these ideas relevant to development economics? Well, for starters, it acknowledges that accumulating productive knowledge is difficult: “For the most part, it is not available in books or on the Internet. It is embedded in brains and human networks. It is tacit and hard to transmit and acquire. It comes from years of experience more than from years of schooling. Productive knowledge, therefore, cannot be learned easily like a song or a poem. It requires structural changes. Just like learning a language requires changes in the structure of the brain, developing a new industry requires changes in the patterns of interaction inside an organization or society.”
As readers will be well aware, the social accumulation of productive knowledge has not been universal: “The enormous income gaps between rich and poor nations are an expression of the vast differences in productive knowledge amassed by different nations.”
These differences are expressed in the diversity and sophistication of the things that each nation makes. In order to put knowledge into productive use, societies need to reassemble these distributed products through teams, organisations and markets. These issues are explored in detail in the Atlas, through the concept of the ‘product space’. This is a map which captures the products made by different countries in terms of their knowledge requirements. This maps provide a way of understanding how productive knowledge is accumulated.
As Hidalgo said in interview:
Knowledge doesn’t add up like capital. There is a lot of redundancy in knowledge. Some countries may have diverse knowledge but small populations. Product space is an expression of different kinds of knowledge – and its much better than other indicators.
Cesar’s TED talk from August 2010 gives more information about this idea and how it works.
The underlying notion of this analysis is that the complexity of an economy is related to the range of useful knowledge embedded in it:
For a complex society to exist, and to sustain itself, people who know about design, marketing, finance, technology, human resource management, operations and trade law must be able to interact and combine their knowledge to make products. These same products cannot be made in societies that are missing parts of this capability set. Economic complexity, therefore, is expressed in the composition of a country’s productive output and reflects the structures that emerge to hold and combine knowledge… Increased economic complexity is necessary for a society to be able to hold and use a larger amount of productive knowledge, and we can measure it from the mix of products that countries are able to make.”
III: What does it all mean?
So what does this give us in practical terms? As a starter, representing such a huge amount of data – covering 128 countries, 99% of world trade, 97% of the world GDP and 95% of the world population – in visual form is in itself a remarkable feat. As people like Hans Rosling have powerfully demonstrated, innovations in how we visualise data can yield tremendous new insights and ideas.
Here’s an example of a product space diagram, this one for the United States. To learn more about the diagrams and how to interpret them, I would strongly recommend having a play with the visualiser, then scanning the report, then having another play.
Hausmann, Hidalgo and their team have also developed an Index of Economic Complexity to represent their data systematically. This Index tells us about the richness of the product space of a given country, and by extension, is one useful indicator of the potential to grow. It can also be used to compare economic complexity across countries, as shown in this chart showing the ranking of different countries (from 1 to 128, highest is most red).
The authors acknowledge that these ideas are not always easy to grasp, and provide a useful thought-experiment to help readers get their heads around the implications of the Index.
Think of a particular country and consider a random product. Now, ask yourself the following question: If this country cannot make this product, in how many other countries can this product be made? If the answer is many countries, then this country probably does not have a complex economy. On the other hand, if few other countries are able to make a product that this country cannot make, this would suggest that this is a complex economy.
So for example, Japan and Germany are the two countries with the highest levels of economic complexity and if a good cannot be produced there, the list of other potential countries is likely to be very short. Conversely if a product cannot be made in Mauritania or Sudan, the list of other potential countries is likely to be a long one.
One useful way of understanding the benefits of the Atlas is to think about what the analysis adds to some of the key questions in growth economics. One of the classic comparisons made in the growth literature is between African and East Asian countries – which were at comparable levels of development in the 1950s-1970s, but which are now literally worlds apart.
Hausmann and Hidalgo give their take on this by comparing the Economic Complexity Index for Ghana and Thailand. The lessons are resonant for aid agencies. Both countries had similar levels of schooling in 1970, and Ghana expanded education more vigorously than Thailand in the subsequent 40 years, supported of course by external assistance and policy recommendations.
Despite this, “Ghana’s economic complexity and income stagnated as it remained an exporter of cocoa, aluminium, fish and forest products. By contrast, between 1970 and 1985 Thailand underwent a massive increase in economic complexity, equivalent to a change of one standard deviation in the Economic Complexity Index. This caused a sustained economic boom in Thailand after 1985. As a consequence, the level of income per capita between Ghana and Thailand has since diverged dramatically.”
The Economic Complexity Index has been shown to be a better predictor of economic growth than a number of other existing development indicators. For example, as reported in the Economist last week, it outstrips the WEF index of competitiveness by a factor of 10 in terms of the accuracy of its predictions. It also outperforms the World Governance Indicators and the standard variable used to measure human capital as predictors of growth.
There are many other rich and varied insights from the work which cannot be covered in detail here. There is also tremendous potential to build on and extend this data and analysis in the future. One of the areas I have been working on recently is on resilience, both as a means of reducing the impact of future crises and disasters, and as a means of securing development gains. This issue is understandably at the forefront of many policymakers’ minds at the moment. The network analysis underpinning the Atlas could be used as a very useful comparative indicator of economic resilience, comparing the sustainability of growth in different countries, and help us think through growth scenarios which might enhance or diminish resilience.
There may also be scope to use this kind of thinking to bring more rigour and realism to problems of industrial reform. Take for example the ubiquitous issue of how we move to low-carbon industrial strategies. It would need more data and analysis, but the product space is clearly a powerful way to start to think about the key issues in a systematic and data driven fashion. There are numerous climate change benchmarks out there but none – as far as I know – employ the kind of network analysis used in the Atlas, and so a key aspect of how industrial economies work is missed out. By understanding better the carbon reliance of a particular countries product space, it is possible to think through the implications – the likely successes and failures – of existing adaptation policies.
IV: In conclusion
Perhaps the most important contribution of the Atlas is the analytical rigour that it brings to the complex and dynamic nature of economic growth, and the ability it gives us to ask new and challenging questions more precisely. Cesar summed it up for me as follows:
What we really want to do is to inspire a new kind of conversation. Our traditional approach to economics has retained measures developed in 1930s and 1940s to deal with the situations and crises we faced back then. We think there should be a new breed of measures – that bring much more precision and resolution, and that mean we don’t continue to build our analysis on the over-simplification of a complex system.
Let’s hope we see more of this way of thinking in development debates. While there will inevitably be a degree of resistance from the old guard, it seems to me that the underlying premise of the report is something that no one could disagree with:
Ultimately, this Atlas views economic development as a social learning process, but one that is rife with pitfalls and dangers. Countries accumulate productive knowledge by developing the capacity to make a larger variety of products of increasing complexity. This process involves trial and error. It is a risky journey in search of the possible.”
Such lessons clearly need to play a much more central role in development policy and practice. Haussman, Hidalgo and their team have done us a real service with this work.
One of the areas where complexity thinking has entered the mainstream of development policy and practice is in resilience thinking. Much of this work owes a debt to C.S. ‘Buzz’ Holling, whose work on resilience of ecologies in the 1970s provided the intellectual underpinning to much recent work. Holling was recently awarded an honorary doctorate by Simon Fraser University, in Vancouver, Canada. His acceptance speech is reproduced below.
Sixty years ago I was where you graduates are now, but graduating from the University of Toronto. By the time I got my PhD a few years later, I was well launched on a goal to understand population processes. It was the unknown that beckoned me and simple curiosity that motivated me.
The goal was to develop suites of models and experiments that could yield explanations and understanding that were simultaneously precise, realistic, holistic and general. For that time, just before computers became available, that was viewed as being unnecessarily complex. After all, one distinguished ecologist asked me, if you are interested in the time a ball takes rolling downhill, why worry about anything more than the height of the hill and its slope? General laws of physics will provide the answer.
But I was stubbornly curious about the path down the hill, the bumps and valleys that the ball might encounter and the momentary pauses as the ball encountered, or even, over several runs, created a shallow valley. That led to really delightful experimental studies of predators and prey leading to generalized models and sudden discoveries from them. The beasts used in the experiments depended on the question of the moment – Preying Mantis, deer mice, shrews, then birds, fish and stalking lions. The early computers and languages like Fortran suddenly provided the language that could use the experimental and field results. Models plus reality combined to yield broadened, generalized understanding of a small number of classes of predation.
That is when I discovered multi-stable states – population systems were not driven only by attraction to a single equilibrium state but, instead, there were several equilibrium states that determined their existence. And the goal for understanding and managing living resources and their physical world, was not sustainability but simple persistence. I learned, for example, that we could have detected and averted a collapse of cod populations off Newfoundland, avoiding the social and economic upheaval that in fact occurred. Or, we could have anticipated and avoided a western sub-continental outbreak of bark beetles that are now destroying stands of lodge pole pine throughout British Columbia and Alberta. Both of these examples were dominantly caused by the slow consequence of earlier development and exploitation, by the ingenious, but myopic foraging of fishers and harvesters, and by decades long fire protection policies.
Those slowly and invisibly led to reduced resilience, poising the systems on the edge of an instability state which began to unravel in a stutter of local spatial collapses and outbreaks, each stutter hidden by fast and innovative fishers and tree harvesters, until the whole system followed the stutters and collapsed at all scales.
That has forced a new paradigm that led to theories of resilience, to adaptive complex systems, to integration across scales from fast and small to very slow and big– from the needles of trees over months, to the boreal forest over millennia, That new resilience paradigm led to management of resources that was adaptive, where the unknown was large, alternatives could be proposed and monitoring was essential.
That is all part of complex adaptive system theory. It reflects humanity’s partial knowledge, fast inventions for dealing with surprises, and persistent learning.
It applies to the present turbulence in the world now. Slow economic processes have led us to the big surprises now appearing on a global scale. Financial collapse, debts threatening nations, European deep instability, and climate change.
Since the Berlin Wall fell, and the Soviet Union collapsed, corporations began to focus on fast economic variables and on globalization. That led to an emphasis on expanding efficiency but also to the emergence of slowly increasing debt, and hidden forces caused by diversified, subdivided and fragmented investments. No one knew where they were, or what they cost. That eventually triggered a collapse that exposed the reality that slow, invisible changes had decreased the resilience of the world economy. Globalization spread the collapse. What was presumed to be efficient began to be realized as being myopic.
At this turbulent time of crises, you and I have a real purpose. We need to help minimize and slow the spread of the collapses in the face of resistance from lobbies and from accumulated wealth. Banks and investment firms need regulation and a richer paradigm, but that need is opposed by the entrenched powers of corporations and banks that are caught in a rigidity trap. Nations of the European Union, and the Euro, need an integrated, multi-scalar inter-relationship, but one that now encounters the loss of resilience that comes in part from the inability to devalue a single nation’s currency and little control on debt inflamed growth. Carbon dioxide emissions need to be inhibited, but that encounters the opposition from the fossil fuel corporations- particularly oil.
Our aboriginal cultures and small communities here on the west coast are discovering and protecting treasured histories and traditions of local cultures. They now need to also add and create novel new ways to see and act beyond their traditional scales at the mouths of rivers and to connect to others across scales. Does fear stop them? Could their traditional theory (and myths) combine with adaptive resilience theory (and myths) as an emerging synthesis?
The answer is to keep trying, keep talking, keep communicating, but recognize it is a frustratingly slow process. Understand the traps- poverty traps like Haiti, rigidity traps like Fascism, lock-in traps of mega agriculture, and gilded traps from external subsidies.
And here is a program specifically for you. Encourage and support experiments, a multiplicity of experiments that search for and deepen new paradigms. Be entrepreneurs, alone and cooperatively together. And make the experiments global and cross scale. The internet and its novel ways of helping people to interact lets us reach or create groups of participants independent of where they live, ones from multiple patches and multiple time senses.
Many experiments will fail, but make them safe in their failure. Look for rare synergisms between a few successes. When enough people and experiences have accumulated, then protest publicly, non-violently and simultaneously against the defenders of the old paradigm that created the crash, the flip.
Following the Japanese earthquake, the Philippines government have announced plans to explore the use of complexity science in better understanding disaster vulnerability and risk.
Senator Edgardo Angara, Chair of Congressional Commission was quoted in a press release making a clear connection between the Japanese earthquake and this new initiative. He said that the tragedy served as another wake up call for the Philippines to invest in the science of disaster management and preparedness. The Senator also said that this will be taken forward as an international collaboration with Japan, Taiwan and others.
A particular inspiration for this work has been the OECD’s report from the 2009 global science forum, which highlighted resilience and vulnerability to extreme events as areas that could benefit from the application of complexity science (Click here for more on the report).
This is the latest example of a growing trend to apply complexity science in disasters, as noted in a previous Aid on the Edge of Chaos post. Complexity-inspired approaches are increasingly being put forward as alternatives to the ‘classic’ ways of analysing and understanding disasters. Indeed, one of the studies quoted in that earlier post suggested that:
…complexity theory is highly relevant for disaster studies because it provides the entry point to describe disasters as the interactions between sub-systems of nature and society or hazard and vulnerability… Disasters caused by natural hazards result from the complex interactions of nature and society…”
One grim example focused on Manila itself:
Consider the following three ingredients: a mega-city in a poor, Pacific rim nation; seasonal monsoon rains; a huge garbage dump. Mix these ingredients in the following way: move impoverished people to the dump, where they build shanty towns and scavenge for a living in the mountain of garbage; saturate the dump with changing monsoon rain patterns; collapse the weakened slopes of garbage and send debris flows to inundate the shanty towns. That particular disaster, which took place outside of Manila in July 2000… was not inherent in any of the three ingredients of that tragedy; it emerged from their interaction’ (Sarewitz and Pielke, 2001 cited in Ramalingam et al, 2008, emphasis added).
More recently Wired magazine ran a fascinating account of an attempt to understand the catastrophic interconnections between hurricanes, deforestation and the 2010 Haiti earthquake (available here). The following is an excerpt from this excellent write-up:
…cause and effect in Earth systems is distinctly nonlinear. Inputs and outputs may not be proportional: a cause with ever-so-slightly different parameters than the previous instance might result in a wildly different effect. Additionally, systems and their component sub-systems interact to produce feedback loops that can either amplify or stabilize resulting effects. Feedbacks blur the line of what is cause and what is effect…”
There is much for this important initiative to consider going forward, not least how the scientists involved will work to get international aid agencies – often insensitive to history, context and dynamics of change - to take account of the emerging findings.
More on this important new initiative to follow soon.
Positive deviance (PD) is a fascinating approach, a decade and a half old, and the focus of growing interest in health, education and numerous other sectors in domestic public policy. Interestingly, given PD saw first widespread application in an aid programme, it is still less well known than it should be across the international community.
This post compiles information from a variety of sources into Q&A form to explore the ideas and assumptions of positive deviance. Rather randomly, it is posted on the same day as another PD-related post, by Duncan Green.
What is Positive Deviance?
According to Richard Pascale, co-author of The Power of Positive Deviance:
It’s an oxymoronic term, in a way, but it’s a very simple observation that in many situations—both in companies and in societies—there are problems that seem absolutely intractable, where you tried everything and you can’t get anything to work, and you just end up accepting things by saying, “that’s just the way it is.” Yet in almost every one of those situations there usually are a few people with the same resources as everyone else, who, against all odds, are succeeding when everyone else is not. So the simple idea is to look at those people who are deviant in a positive direction, and who are prevailing when the conventional wisdom says you can’t.
Where did Positive Deviance come from?
From the PD website:
In 1991, the Jerry and Monica Sternin faced what seemed like an insurmountable challenge in Vietnam. As new Director of Save the Children in Vietnam, Jerry was asked by government officials to create an effective, large-scale program to combat child malnutrition and to show results within six months. More than 65 percent of all children living in Vietnamese villages were malnourished at the time. The Vietnamese government realized that the results achieved by traditional supplemental feeding programs were rarely maintained after the programs ended. The Sternins were mandated by the government to come up with an approach that would enable the community to improve and sustain their young children’s health status…and quickly!
Building on Marian Zeitlin’s ideas of positive deviance, working with four communities and a population of 2,000 children under the age of three, the Sternins invited the community to identify poor families who had managed to avoid malnutrition despite all odds, facing the same challenges and obstacles as their neighbors and without access to any special resources. These families were the positive deviants. They were “positive” because they were doing things right, and “deviants” because they engaged in behaviors that most others did not. The Sternins and the community discovered together that caregivers in the PD families collected tiny shrimps and crabs from paddy fields, and added those, along with sweet potato greens, to their children’s meals. These foods were accessible to everyone, but most community members believed they were inappropriate for young children. The PD families were also feeding their children three to four times a day, rather than twice a day, which was customary.
The communities developed an activity which enabled all of the families with malnourished children to rehabilitate their children and to learn how to sustain their children at home on their own, by inviting them to practice the demonstrably successful but uncommon behaviors which they had discovered in their communities. The pilot project resulted in the sustained rehabilitation of several hundred malnourished children and the promotion of social change in their communities. (PD website)
So it’s basically a way of identifying best practices? Great, just what we need!
Steady on there, not so fast.
Of course the initial reaction of any hierarchical organization is, “this is a best practice, let’s do it everywhere.” The strong counsel of both the villagers and Jerry and Monique Sternin was, “Absolutely not. Every community has to be curious about the question. They have to accept the invitation, if you will, to do something about a problem they regard as really essential. They’ve got to be at the front end to figure out what’s going on, what’s working.
Then they’ve got to find the other positive deviants and learn what they’re doing. Then they have to figure out to disperse this information within their community. But if you go out and say to people in another village, ‘Gather and eat shrimps, crabs, and greens,’ they’re going to say something like, ‘You know, we’re different. Those guys eat weird things.’ You’ve got to get the community to own it.”
So what differentiates this from best practices in most applications is that there is always this invitation, an authentic invitation, that has to be accepted by the target group. (Richard Pascale in interview)
So what are the principles behind Positive Deviance?
It’s pretty simple:
…The standard model… is this hierarchical principle of experts and people in authority having the answers to our problems. That notion seems to be baked into the human psyche. It’s just generally true throughout the world. You always begin, and not wrongly, with looking for a technical solution. So [vaccines are] a great answer, and you don’t really need a lot of community mobilization if you’ve come up with a silver bullet and can prove that it works—that’s not a particularly hard sell.
But really hard problems—what we call adaptive problems—are imbedded in a complex social system. They require behavioral change, and they’re rife with unintended consequences. These kinds of problems, like the ones that we’re facing all around the world: developed societies with governments that can no longer afford the social safety net, the healthcare problems in the United States, and any number of issues like that, are not just technical problems. They’re really adaptive problems.
You try the technical solutions. For reasons that are imbedded in the complex social system and behavior, they don’t work. When you impose them in a top-down fashion, you don’t get closer to anticipating all the unintended consequences. So they don’t work.
More philosophically, this is a quote from the PD website, from Lao Tzu
Learn from the people
Plan with the people
Begin with what they have
Build on what they know
Of the best leaders
When the task is accomplished
The people all remark
We have done it ourselves.”
~Lao-Tzu Tao Te Ching
That all sounds very good. But what impact has it actually had on the ground?
Here’s the great bit. The successful application of the PD approach has been documented in more than 41 countries in nutrition and a variety of other sectors from public health to education to business. The following is an illustrative sample of PD-informed program impacts over the 15 years:
Sustained 65 to 80% reduction in childhood malnutrition in Vietnamese communities, reaching a population of 2.2 million people.
Significant reduction in childhood malnutrition in communities in over 40 countries around the world.
Reduction in neo-natal mortality & morbidity in Pashtun communities in Pakistan and minority communities in Vietnam with near universal adoption of protective behaviors and social change.
Estimated 50% increase in primary school student retention in 10 participating schools in Missiones, Argentina.
Documented reduction in girl trafficking in impoverished communities in East Java, Indonesia.
Thousands of documented female circumcisions averted in Egypt and the formation of 12 “FGM free” communities.
In the Spring of 2005 Merck Mexico began a project to address the issue that only 13 out of 21 districts at Merck Mexico had a sales coverage of 100% or greater. Within 8 months all districts (100%) were covering their sales target.
Wow. So how exactly does PD relate to traditional approaches to innovation?
According to the classic diffusion-based approach, innovation is based on the following principles:
it comes from the ‘outside’
it is pushed and promoted by a change agency anf through expert and knowledgeable change agents
these agents use persuasive communication strategies to plug existing knowledge-attitude -practice (KAP)
gaps among the client / user audience
they harnessing the influence of charismatic opinion-leaders, who serve as visible role models of adoption for the non-adopters.
PD turns this model on its head. As one account puts it:
We are not suggesting the PD approach substitute for the classical diffusion of innovations paradigm. Rather, we argue that the PD approach provides additional options. We believe that often the wisdom to solve intractable social problems lies within the community. Diffusion in the PD approach is an “inside-out” process, in contrast to the classical dominant framework of “outside-in” diffusion.
As Pascale and Sternin put in a 2005 HBR article:
When identification of a superior method is imposed, not self-discovered, cries of “We’re not them” or “It just won’t work here” predictably limit acceptance. By contrast, a design that allows a community to learn from its own hidden wisdom is, among other things, respectful. Innovator and adopter share the same DNA. Community members invest sweat, and, in the process, they become partners to change.
Of course not. When there are proven remedies to technical problems—the Salk vaccine to polio, supply chain management practices, hardware and software solutions—companies can use them to work harder, faster, or smarter. And problems that rely on brainpower but that don’t require major behavioural adjustments are unsuitable for the positive deviance approach.
The method works best when behavioral and attitudinal changes are called for—that is when there is no apparent off-the-shelf remedy and successful coping strategies remain isolated and concealed. In such cases, change from within, discovered, celebrated, and implemented by the people who need to do the work. People are much more likely to act their way into a new way of thinking than to think their way into a new way of acting.
Sounds a bit familiar. So what’s the connection to complexity and evolutionary sciences?
the [PD] process excels over most alternatives when addressing problems that (1) are enmeshed in a complex social system, (2) require social and behavioral change, and (3) entail solutions that are rife with unforeseeable or unintended consequences. It provides a fresh alternative when problems are viewed as intractable (i.e., other solutions haven’t worked).
And later on:
PD works like nature works… this isn’t an analogy; it is the way it is… nature tinkers with a different shaped bird beak or a slightly larger brian… natural selection does the rest, favouring variations that improve access to food and reproduction… In nature, this all plays out in evolutionary timescales of centuries or millennia. Emploring identical principles, the PD process achieves change within months or a few years…
A piece in yesterday’s New Scientist titled ‘Can Complexity Theory Explain Egypt’s Crisis?’ explores ideas of complexity in the context of the ongoing events in Egypt. It draws on the insights of two noted complexity thinkers – Yaneer Bar-Yam and Thomas Homer-Dixon. Excerpts are reproduced below with permission:
Egyptians are the world’s biggest wheat importers and consumers, and most are poor. As a result, the government maintains order with heavy subsidies for bread. It also runs the ports where imported wheat arrives, the trucks that haul it, the flour mills and bakeries…
[Such systems] are fine so long as the top of the hierarchy is in place, and can recover quickly. But take the top away – as is happening in Egypt – and the entire system risks collapse.
The early signs of this are showing. Bread is getting scarce in Egypt’s capital, Cairo. Bakeries are closing for lack of flour… Imported wheat is sitting in ports as cranes and lorries stand idle. The interlocking dependencies that tie modern economies together spread dislocation further. Even where there is food, Egyptians have little money to buy it, as businesses and banks close, cash machines empty and wages dry up…
…The stresses of decades of dictatorship might have turned the entire Middle East into a “self-organised critical system”… The build-up of stresses makes such systems vulnerable to cascades of change triggered by relatively small disruptions…
The key argument of the article is that a hierarchical system (like the Egyptian government) facing a dynamic and interconnected problem is - in the extreme - prone to catastrophic collapse.
Regular Aid on the Edge of Chaos readers will know that this resonates strongly with previous reflections on this blog. The growing interconnectedness between finance, fuel and food systems was the focus of a recent piece exploring the ‘Globalisation of Vulnerability’. The maladaptive nature of organisational and governance systems in the face of change have also been covered on numerous occasions, including in a piece on ‘History on the Edge of Chaos’.
However, there is another vital dimension to complex adaptive systems that does not get sufficient coverage in the New Scientist piece. The author does briefly acknowledge that there are two sides to complex interdependencies: as well as collapse, they can also generate cascading change. (For an example, see the lessons from the Obama Presidential Campaign as recounted by veteran civil rights activist Marshall Ganz.) But the article misses out on the opportunity to reflect on the remarkable efforts of the anti-government protestors across Egypt through a complexity lens.
Without a doubt the most astonishing feature of the unfolding events in Egypt has been the leaderless, self-organised, networked movement that emerged and managed to maintain a peaceful and resilient presence – despite the efforts of the pro-Mubarak contingents.
As well as insights into collapse, complexity science can tell us something about how such movements happen, and give insights into the dynamic social processes that play out. It can tell us something about resilience in the face of oppression. It gives insights into the information and communication networks that feed and shape a movement. The ideas of complex adaptive systems can help us learn more about emergent collective action, and – through this – about how beliefs are reinforced, about how passion is shared and about how courage builds.
And – as we have seen repeatedly since January 25th - cascading, unpredictable change can have a profoundly human face.
Complexity science does more just than provide new ways to theorise descent, freefall and collapse. It can also help further our understanding of what human beings are capable of achieving. As Thomas Homer-Dixon, mentioned above, put it in the title of his book: there is an Upside to Down.
