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Mapping politics (and the politics of maps)

Posted in Campaigns, Communications, Innovation, Public Policy, Research on November 7, 2012 | 25 Comments »

So after billions of dollars and several years of hard campaigning, the US elections are finally over. The typical map of the 2012 US election results looks like this:

Which is clearly not a million miles away from the 2008 equivalent.

In these maps, of which there are thousands online, on TV shows and in newspaper reports, the US states are coloured red or blue according to whether the majority of their voters were Republican or Democrat.

These maps, are, of course an illusion. They suggests that the ‘reds’ might have won because there is more red on the map, and that the reds and blues are sharply divided. Typical comments about such maps run along the lines of “what a huge sea of red”, “there you go, the liberal-conservative divide”, “it really is two different countries, isn’t it?”, and so on.

However, these maps fail to take account of some basic realities. First of all, there is no representation of population. The reality is that the population of the red states is on average significantly lower than that of the blue ones. So while the blue are small in area, they represent large numbers of voters. Second, more importantly for the results of elections, the maps take no account of the distribution of electoral college votes. Third, they take no account of the often fine-grained distribution of voter preferences within states.

Mark Newman, a noted complexity researcher, has done a lot of work on how we can get more realistic, less simplistic maps of complex, real-world phenomena. By drawing such cartograms, which enable maps to be re-scaled according to key variables like population, maps of the electoral spread can be made more realistic and detailed. They can also tell different, more subtle, stories about political allegiance.

By the sounds of things, he is busy working right now on maps of the 2012 election. Here is his depiction of the 2008 election using a population cartogram.

In this, the states have been squashed and stretched to give relative sizes while preserving the overall US structure. A similar thing can be done with the electoral college results. In the map below, the map scales the sizes of states to be proportional to their number of electoral votes in 2008.

As Newman writes:

The areas of red and blue on the cartogram are now proportional to the actual numbers of electoral votes won by each candidate. Thus this map shows at a glance both which states went to which candidate and which candidate won more electoral college votes – something that you cannot tell easily from the normal election-night red and blue map.

Newman and his colleagues went further to map the election results by county, the resulting images are even more striking. This is the equivalent of the first map above, with each county coloured red or blue according to the majority vote in 2008.

Again, the red appears to be in the majority. Using a cartogram of population gives this:

All of these maps are however also somewhat fictional as they pay no attention to the fact that no single state is in fact a sea of red or blue. Instead, as this election showed, every county and state contains quite closely balanced numbers of Republican and Democratic supporters. By using only two colours we lose any sense of this balance, and feed the myth of red states and blue states, and of sharp country-wide divides.

Newman and his colleagues have got around this by using red, blue, and shades of purple in between to indicate the nuance in voting patterns: different shades of purple indicate different splits of votes.

This is the county level map with this applied:

And this is the population cartogram:

As Newman explains:

As this map makes clear, large portions of the country are quite evenly divided, appearing in various shades of purple, although a number of strongly Democratic (blue) areas are visible too, mostly in the larger cities. There are also some strongly Republican areas, but most of them have relatively small populations and hence appear quite small on this map.

What I love about this work is that it clearly demonstrates the power of maps and visualisations to shape our thinking. These depictions pose direct and clear challenges to those lazy, pervasive but ultimately unhelpful narratives (“sea of red”, “lib-con divides”, “country of two parts”, etc, etc).

I think that these more realistic, sophisticated  representations should become much more commonplace in politics and indeed in development. Mark Newman set up the World Mapper project back in 2006, which has a whole host of similar maps, many of which have been widely used in presentations and reports.

Much of this work owes a debt – of sorts – to the infamous and controversial Gall-Peters projection, which provided a new visualisation of the earth using a more egalitarian and precise calculation of the relative landmass of developing countries.

Along broadly similar lines, a recent guest post on this blog looked at how we might use tools like fitness landscapes to more accurately represent non-linear development progress.

Perhaps such tools could slowly help change the way we think about a whole range of complex, routinely over-simplified, phenomena.

Who knows, one day they may even help inform some less divisive narratives about the US political landscape. As President Obama put it this morning in his acceptance speech:

We are not as divided as our politics suggest. We remain more than a collection of red states and blue states.”

Too right.

Postscript on 8th November 2012: the 2012 election maps are now done, and here is the 2012 county cartogram.

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Facebook, social media and the complexity of influence

Posted in Campaigns, Communications, Evaluation, Influence, Knowledge and learning, Leadership, Networks, Strategy on February 20, 2012 | 5 Comments »

Influence is a complex process in the development sector. We have known this for some time – the work of the RAPID programme at ODI on understanding how evidence influences policy is very clear on this. But the wider socio-economic system within which development cooperation is embedded is no less difficult to influence.  Many corporations, especially in new media, are turning to complexity and evolutionary sciences as a means of measuring influence. But there is considerable potential for misuse and abuse, as illustrated by a new report on Facebook’s contribution to the European economy, and a recent critique of the latest wave of social media analysis firms.

I: Facebook’s Impact on Europe

In a report published in January 2012, Facebook asked the global business advisory firm, Deloitte, to estimate the benefits it generated for the European economy. The report findings make intriguing reading for anyone with an interest in performance, accountability and transparency.

Deloitte’s analysis looked at the direct economic impact of Facebook – such as paying tax, profits and wages. These are the so-called ‘narrow economic effects’ of on-site activities. These impacts are seen as Facebook’s value added, and are described as ‘analogous to contribution to GDP’.  Facebook also has a series of what Deloitte calls ‘ecosystem effects’ – namely, how Facebook enables other businesses to ‘reach customers, make sales, create and monetise apps and even boost demand for products such as broadband and smartphones.’ These ‘broad economic effects’ which result from the Facebook ecosystem give us a measure of Facebook’s influence. The diagram below sets the model out in more detail.

Facebook’s ‘narrow effects’ suggest that it has a narrow impact of €214m and supports 3,200 jobs. But its broad effects are considerably more. For Europe as a whole, the economic impact of Facebook was estimated as just over €15bn in revenues, supporting 229,000 jobs.

By far the largest part of this broader impact was seen as ‘the impact on business participation, where Facebook enables other businesses to advertise, promote their brand, raise awareness and therefore generate new sales… much of this effect is associated with the brand value created for organisations through the social links prevalent on Facebook and the new ways of engendering loyalty and interest that Facebook provides.’ [emphasis added]

Facebook Chief Operating Officer Sheryl Sandberg had this to say when launching the report:

Today’s report shows that Facebook is about a lot more than sharing pictures or keeping up with friends. Increasingly, social media means growth and jobs. Social media is proving particularly valuable for small- and medium-sized businesses, which form the backbone of the European economy.”

These are strong statements, and certainly in keeping with the ‘Facebook boom’ narrative that is so prominent in the media at the moment. In a time of economic gloom, Facebook seems to be one of the few glimmers of hope.

II: Spurious reasoning, dodgy numbers

However, Deloitte seems rather more measured than Sandberg. While clearly happy to put their name to and launch the report, the preamble to the report qualifies this in the following passage:

As set out in the contract, the scope of our work has been limited by the time, information and explanations made available to us. The information contained in this report has been obtained from Facebook Inc and third party sources… Deloitte has neither sought to corroborate this information nor to review its overall reasonableness… no responsibility or liability is or will be accepted by or on behalf of Deloitte… or any other person as to the accuracy, completeness or correctness of the information in this document or any oral information made available… [emphases added]

How about that for an object lesson in distancing oneself from ones work? But if we look at the detail of the analysis, we can start to see that the ‘ecosystem valuation’ is based on some very sketchy assumptions.

For example, Deloitte attributes €6.6bn of the €15.3bn European-wide economic impact of Facebook to “brand value”. This is based on the attribution of a fixed cash value of a Facebook fan of a particular product (€4.69), taken together with the total number of fans (4.2 billion), with some downward adjustments. While all of the numbers used are based on other studies, the overall calculation and final figures still seem fantastically overblown.

The report also suggests that Facebook contributes €5.5 billion to the European economy by generating technology sales. €0.4 billion of this is down to additional device sales, and the rest is seen as broadband. In effect, the report is saying that large numbers of Europeans are buying devices and signing up for broadband just to – or mostly to – use Facebook. Again, this is a claim that would be very hard to substantiate. These two figures alone make up €12.1 billion of the stated impact €15.3bn of Facebook.

III: Social media hyperbole

This is a particular form of social media spin, and is part of a wider movement described by Philip Sheldrake in the Guardian last week. Sheldrake argues that a whole spate of social media organisations are using and abusing the tools and ideas of complexity science in order to demonstrate their influence, all with an air of scientific credibility.

The rest of this post draws extensively from Sheldrake’s critique. He begins by describing what influence is:

You have been influenced when you think something you wouldn’t otherwise have thought, or do something you wouldn’t otherwise have done. …ultimately no one wants to communicate without influence; that wouldn’t be a good use of the communicator’s time and energy, or indeed that of those on the receiving end. The focus on making sure you’re influenced back is vital too… Individuals (and organisations) that best absorb the zeitgeist are heuristically more able to respond in ways their audiences (stakeholders) might well appreciate…

But things aren’t all that straightforward, and he turns to complexity science to show why:

Complexity is the phenomena that emerge from a collection of interacting objects. The interacting objects could be molecules of air and the phenomenon the weather. It could be vehicles and the phenomenon the traffic. Human objects could be the population of Cairo, the 99%, sports fans in a sports stadium, people who like photos of cats, your customers, or your employees; in fact, any collection of people interacting with each other, influencing each other. A characteristic of complexity is that studying the individual rarely betrays anything about the phenomena. You can’t learn much about the termite mound by studying the individual termite or the traffic jam by studying the car.

Sheldrake then relates the ideas of complexity science to the phenomenon of influence:

Take almost any of your recent thoughts or actions and try and decipher how in fact that thought or action came to be; what did you take into account, consciously and unconsciously, over what timescale? You soon begin to appreciate that your thoughts and actions are outputs of a complex system. You are reconciling multiple inputs, multiple influences.

The article points out that companies such as Klout, PeerIndex and PeopleBrowsr all claim to provide systematic insights into individual influence, using ideas of complex systems (specifically social network analysis). This is problematic, however:

In my opinion, complexity and network science will continue to unearth insights of important commercial and societal value, but I’m considerably less enamoured about seeming to translate today’s analytical capabilities into some kind of a score of an individual’s influence. Right now, we have no scalable facility to ascertain or infer who or what caused someone to change their mind or behaviour, without falling into some kind of last-click attribution trap, so how then can we pretend to score an individual’s likelihood to exert that influence, and as if they did so with apparent Newtonian simplicity? We’ve barely even attempted to correlate proxies for influence, assuming that universal correlates even exist. Today, these scores are apportioned in such naive fashion that your so-called influence changes following a fortnight offline.

IV: Navigate complexity, don’t ignore it

This seems to be precisely the kind of thinking that can be seen as underpinning the ‘Facebook ecosystem’. On this basis, we might say that the Deloitte analysis was weak not merely because they did not seek ‘to corroborate this information nor to review its overall reasonableness’. It also falls into the trap of attributing benefits to Facebook in far too simplistic and straightforward a manner, through over-use of the metaphor of  ‘ecosystem’. To cite Sheldrake again:

Perhaps these companies attempt a measure at online popularity, or perhaps online authority, or more exactly the likelihood to have one’s online output shared/forwarded, but not one’s influence. Nor indeed one’s trustworthiness.

Sheldrake also cites Duncan Watts, noted network expert, who has argued against such applications of network and complexity science:

Influentials don’t govern person-to-person communication. We all do. If society is ready to embrace a trend, almost anyone can start one – and if it isn’t, then almost no one can.

This is not great news for Facebook and other social marketeers: ‘many [of whom] have claimed to be able to identify the influentials, get to know them, and influence them. They are effectively claiming to be the influencer of influencers, a sort of influencer-in-chief if you like.’

Sheldrake closes with a message for marketing and PR consultants that is equally pertinent for development and humanitarian agencies seeking to demonstrate their influence:

However, successful [organisations] of the 21st-century will avoid such simplistic thinking, such hyperbole, and recognise complexity and navigate it appropriately.’ (emphasis added)

Facebook and other firms who are well advanced in their use of complexity science ideas should be paying careful attention to Sheldrakes’ assessment. Those of us in the development sector – despite being at much earlier stages in both our efforts to use complexity science and analyse influence – would perhaps also do well to take note.

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What are leaders really for?

Posted in Accountability, Campaigns, Conflict and peace building, Evolution, Financial crisis, Innovation, Knowledge and learning, Leadership, Networks, Self organisation on December 7, 2011 | 5 Comments »

A continuing theme on this blog has been the issue of leadership. Many reports and studies call for it, reforms are seen as impossible without it, critical challenges will not be met without it, and we are all ready to point out the lack of it (in others, at least).

Despite the fact that leadership is one of the most researched topics in management literature (or perhaps because of this fact) , our understanding of leadership remains vague and ambiguous.

A blog on HBR by Duncan Watts of Yahoo’s Human Social Dynamics research group eloquently explores the concept and ideas with reference to recent social movements.

His argument resonates strongly with ideas of complex adaptive leadership explored in a previous post here.

The Occupy Wall Street movement has both perplexed and frustrated observers and analysts by its persistent refusal to nominate an identifiable leadership who can in turn articulate a coherent agenda. What is the point, these critics wonder, of a movement that can’t figure out where it’s trying to go, and how can it get there without anyone to lead it?

It’s a reasonable question, but it says at least as much about what we want from our social movements as it does about the way movements actually succeed.

Typically, the way we think of social change is some variant of the “great man” theory of history: that remarkable events are driven by correspondingly remarkable individuals whose vision and leadership inspire and coordinate the actions of the many. Sometimes these individuals occupy traditional roles of leadership, like presidents, CEOs, or generals, while at other times they emerge from the rank and file; but regardless of where they come from, their presence is necessary for real social change to begin. As Margaret Meade is supposed to have said: “Never doubt that a small group of thoughtful, committed citizens can change the world. Indeed, it is the only thing that ever has.”

It’s an inspiring idea, but over 100 years ago in his early classic of social psychology, “The Crowd,” the French social critic Gustave LeBon, argued that the role of the leader was more subtle and indirect. According to LeBon, it was the crowd, not the princes and generals, that had become the driving force of social change. Leaders still mattered, but it wasn’t because they themselves put their shoulders to the wheel of history; rather it was because they were quick to recognize the forces at work and adept at placing themselves in the forefront.

Even before LeBon, no less an observer of history than Tolstoy presented an even more jaundiced view of the great man theory. In a celebrated essay on Tolstoy’s War and Peace, the philosopher Isaiah Berlin summed up Tolstoy’s central insight this way: “the higher the soldiers or statesmen are in the pyramid of authority, the farther they must be from its base, which consists of those ordinary men and women whose lives are the actual stuff of history; and, consequently, the smaller the effect of the words and acts of such remote personages, despite all their theoretical authority, upon that history.” According to Tolstoy, in other words, the accounts of historians are borderline fabrications, glossing over the vast majority of what actually happens in favor of a convenient storyline focused on the skill and leadership of the great generals.

Thinkers like Le Bon and Tolstoy and Berlin therefore lead us to a radically alternative hypothesis of social change: that successful movements succeed for reasons other than the presence of a great leader, who is as much a consequence of the movement’s success as its cause. Explanations of historically important events that focus on the actions of a special few therefore misunderstand their true causes, which are invariably complex and often depend on the actions of a great many individuals whose names are lost to history.

Interestingly, in the natural world we don’t find this sort of explanation controversial. When we hear that a raging forest fire has consumed millions of acres of California forest, we don’t assume that there was anything special about the initial spark. Quite to the contrary, we understand that in context of the large-scale environmental conditions — prolonged drought, a buildup of flammable undergrowth, strong winds, rugged terrain, and on so — that truly drive fires, the nature of the spark itself is close to irrelevant.

Yet when it comes to the social equivalent of the forest fire, we do in effect insist that there must have been something special about the spark that started it. Because our experience tells us that leadership matters in small groups such as Army platoons or start-up companies, we assume that it matters in the same way for the very largest groups as well. Thus when we witness some successful movement or organization, it seems obvious to us that whoever the leader is, his or her particular combination of personality, vision, and leadership style must have supplied the critical X factor, where the larger and more successful the movement, the more important the leader will appear.

By refusing to name a leader, Occupy Wall Street presents a challenge to this view. With no one figure to credit or blame, with no face to put on a sprawling inchoate movement, and with no hierarchy of power, we simply don’t know how to process what “it” is, and therefore how to think about it. And because this absence of a familiar personality-centric narrative makes us uncomfortable, we are tempted to reject the whole thing as somehow not real. Or instead, we insist that in order to be taken seriously, the movement must first change to reflect what we expect from serious organizations — namely a charismatic leader to whom we can attribute everything.

In the case of Occupy Wall Street, we will probably get our wish, for two reasons. First, if OWS grows large enough to deliver any lasting social change, some hierarchy will become necessary in order to coordinate its increasingly diverse activities; and a hierarchy by nature requires a leader. And second, precisely because the outside world wants a leader — to negotiate with, to hold responsible, and ultimately to lionize — the temptation to be that person will eventually prove irresistible.

Leaders, in other words, are necessary, but not because they are the source of social change. Rather their real function is to occupy the role that allows the rest of us to make sense of what is happening — just as Tolstoy suspected. For better and worse, telling stories is how we make sense of the world, and it’s hard to tell a story without focal actors around which to center the action.

But as we witness a succession of popular movements, from the Arab Spring to Occupy Wall Street, we can at least pause to appreciate the real story, which is the remarkable phenomenon of a great many ordinary individuals coming together to change the world.

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Six Theories of Policy Change

Posted in Campaigns, Evaluation, Knowledge and learning, Public Policy, Strategy on April 20, 2011 | 3 Comments »

Many of us working in foreign aid struggle with the idea of theories of change. The ubiquitous logical framework has an implicit theory of change that we recognise to be flawed, or at the very least, extremely limited. But alternatives are thin and often poorly articulated. A new briefing from Organisation Research Services sets out some very useful ideas and illustrations which might help expand and extend our models of  how policy change happens.

As the authors put it: ”understanding different theories about policy change can help organizations more effectively choose advocacy strategies, focus evaluation efforts on the right outcomes, and avoid the “kitchen sink” syndrome of doing a little bit of everything and unrealistically expecting change in all areas.” Although developed with US policy in mind, there is much of  relevant for development and humanitarian efforts here. To cite directly:

[new] theories can inform the development of advocacy theories of change and logic models. Just as academics develop theories, advocates have their own ideas about what will help them achieve or move toward a policy “win.”  These internal ideas or assumptions about policymaking, also called theories of change, can be documented as visual diagrams that express the relationships between advocacy actions and hoped-for results. When articulated, these strategy and belief system roadmaps can clarify expectations internally and externally, and facilitate more effective planning and evaluation. Knowing about and incorporating existing social science theories into our strategies can sharpen our thinking [and] provide new ways of looking at the policy world…

The table below summarises the six theories and when they might be most applicable.

Download the full briefing here.

H/T Jeff Knezovich

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Complexity with a human face

Posted in Campaigns, Financial crisis, Leadership, Networks, Resilience, Self organisation on February 4, 2011 | 5 Comments »

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.

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How do you solve a problem like Malaria?

Posted in Biology, Campaigns, Evaluation, Evolution, Healthcare, Innovation, Institutions, Knowledge and learning, Malaria, Public Policy, Strategy, Uncategorized on January 27, 2011 | 9 Comments »

Big thanks to Alanna Shaikh and Bill Brieger for feedback and comments.

Debates about malaria eradication in the aid blogosphere, along with recent scientific evidence, highlight the urgent need to improve our understanding of the complex dynamics of this terrible affliction and to use it to adapt ongoing eradication programmes.

A nearly hopeless case?

According to the WHO, one in every five childhood deaths in Africa is due to the effects of the disease and an African child has on average between 1.6 and 5.4 episodes of malaria fever each year. A child dies every 30 seconds of malaria. The latest estimate from the 2010 World Malaria Report is that in 2009 the disease killed almost 800,000 people and afflicted 225 million others. And while a 2009 global malaria risk map suggests that while risks are worst in Africa, there are  clear indications of dangers in many other countries too.

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Last week Chris Blattman posted a justifiably scathing response to an article in Guernica, which had suggested that attempts to eradicate malaria are ‘nearly hopeless‘, and that current global attempts to do so are doing more harm than good.

Chris put forward an eloquent and moving counter-argument which included the following points (a) disease eradication is one of the few successes of big aid (b) we can’t simply let malaria take its toll and do nothing (c) presenting malaria as a symbol of African honour – as the Guernica article does – is at best inaccurate and misleading and (d) development is the key to successful eradication.

Many (myself included) would agree wholeheartedly. Evidence suggests that the cessation of malaria control programmes can lead to severe epidemics, as in Swaziland in 1984-85, or Madagascar in 1987-88. Shortfalls in ongoing responses have also led to resurgences in Zambia and Rwanda. Much of what is presented in the Guernica article can be dismissed as bizarre, confused or just plain wrong. However, one point made is worth looking at in more detail.

Premature pronouncements and cheap mainstays

The author suggests that current approaches to malaria tend to be narrowly focused on a limited number of technical solutions, or the search for such solutions. Think bednets, drugs or the investment in the development of vaccines.

In fact, this narrowness in the focus of malaria programmes appears to have been a relatively constant feature over the last 40-50 years. In 1969, the Pearson Commission (the source of the ubiquitous 0.7% of GDP aid target for donor countries) pronounced the disease ‘virtually eliminated’. Today it is hard not to see this declaration alongside Chamberlain’s ‘peace for our time’ as one of the most premature statements ever (as well as a little disingenuous from the standpoint of developing countries).

A 2008 Lancet review cited in Malaria Matters tells us more about the failures of the first eradication effort:

[the 1960s eradication campaign] was far too monodimensional, relied too much on DDT [insecticide] spraying, and  neglected the palpable problem that the delivery infrastructure was not  in place in too many parts of the malarious world.”

It goes on:

The emergence of widespread mosquito resistance to DDT, and parasite resistance to the cheap mainstay of therapy compounded the difficulties.” (emphasis added)

In short, narrowness of responses allowed evolutionary dynamics to play out at various levels, changing the efficacy of those responses. This problem has not gone away. As clinical microbiologists Richard Carter and Kamini Mendis see it, for the most part, the types of tools that are available and are used for malaria control today are the same as those which were available during the ‘virtual elimination’ era.

This point does need some nuancing. There was one approved insecticide during the first eradication effort, whereas there are now a dozen. The use of treated nets – which weren’t around in the 1960s – has been responsible for large drops in some countries. But even in those countries there is growing acknowledgement of the need for a better combination of responses to make further progress. ‘Cheap mainstays’ will not do the trick. As noted on Malaria Matters:

The malaria lifecycle is complex, and health systems designed to deliver malaria interventions [are] equally complex (and challenging), which means we cannot and should not expect a magic bullet in the near future.

If we want to better understand the complexity of malaria, a good place to start would be to understand the evolutionary dynamics at play.

Exploring evolutionary dynamics

Resistance to responses – whether among mosquitoes or the parasite itself – has been identified as an evolutionary phenomenon. Biology 101 tells us that all populations of organisms display genetic variation across members which enable some to handle particular environmental stresses and opportunities better than others. Natural selection has been shown to favour the evolution of pathogen populations that can resist the drugs and insecticides in their environments.

As the Lancet article cited above notes, resistance has evolved at two distinct levels. The malaria parasite evolves, developing drug resistance. One team of researchers has found that “Drug development programs exhibit a high attrition rate and parasite resistance to… drugs exacerbate the problem. Strategies that limit the development of resistance and minimize host side-effects are therefore of major importance.”

Specific parasites also adapt at the molecular level, according to the antibodies encountered in the host’s immune system. There is also the prospect of inter-species infections, whereby – for example – parasites mainly responsible for malaria among chimpanzees find ways to adapt to new human hosts, facilitated by greater human penetration of forest environments.

Mosquitoes also evolve to adapt to changing physical environments, human behaviour and pesticides. As described by Bill Brieger on his excellent Malaria Matters blog:

…Resistance to insecticides in [a mosquito sub-species] is receiving increasing attention because it threatens the sustainability of malaria vector control programs in sub-Saharan Africa. An understanding of the molecular mechanisms conferring… resistance gives insight into the processes of evolution of adaptive traits and facilitates the development of simple monitoring tools and novel strategies to restore the efficacy of insecticides…”

There have been numerous calls for more studies into how insects exposed to pesticides undergo strong natural selection and develop various adaptive mechanisms to survive.

Of course, human populations have also have co-evolved with malaria, and developed different kinds of resistance. The protective effects of the sickle cell trait is certainly the best known example, but there are others that have been identified, including genetic variations in the populations of Thailand and New Guinea which prevent against malaria-induced miscarriages. However, humans adapt genetically less quickly than the malaria parasite or the mosquito – waiting for or relying human evolution of resistance (as the Guernica piece seems to imply) is clearly not an adequate fall-back option.

Professor Karen Day, who has studied the historical evolution of malaria, is clear about the importance of this line of inquiry:

…From Ronald Ross’s discovery that malaria is transmitted by mosquitoes came the idea that we could control malaria by impacting the life span of the mosquito. If we can better understand the evolution and diversity of malaria, we may find an Achilles heel in the parasite or new ways to thinking about control….”

Slow take-up, slow scale-up?

However, while there is some basic research attempting to bring an understanding of evolutionary dynamics to the design of better drugs, pesticides, and even vaccines, there are still questions as to whether this knowledge is ready to be applied in programmes and at the necessary scale. The overall global malaria response may still be relatively limited in terms of its repertoire of responses.

For example, a 2009 study notes that the Global Malaria Action Plan (GMAP) of the Roll Back Malaria initiative sought to spray 172 million houses annually, and distribute 730 million insecticide-impregnated bed nets. The study concluded that if this was implemented with existing insecticides, with no acknowledgement of the scope for evolutionary response, the program would create unprecedented opportunities for the development of resistance among mosquitoes, and may also create new variants of mosquitoes.

The World Malaria Report 2010 shows that global efforts to prevent malaria through bednets and sprays reduced cases from 233m in 2000 to 225m in 2009 and 985k deaths in 2000 compared to 781k deaths in 2009. However, tellingly, the statistics also show that several African countries saw a resurgence of the disease – in part because of resistance and changing contextual factors.

Researchers at Maastricht University have argued that a fundamental issue is that much malaria modelling does not take into account evolutionary dynamics. By modelling global malaria as a complex adaptive system, the researchers have been able to review the efficacy of malaria strategies, and were also able to assess the potential implications of climate change.

Overall, their conclusion was that continued changes in human behaviour (such as in agricultural methods or urbanisation, which presents its own set of challenges), as well as human impact on the environment, will mean malaria will continue to evolve and confound current interventions in areas of high prevalence. They also make a complementary point to Professor Karen Day’s – eradication and control strategies that do not take account of these complex evolutionary dynamics may well make things worse, and could ‘substantially exacerbate the significance of malaria in coming decades’.

Some of these fears may be becoming reality. An article published in Science magazine in October 2010 suggested that the mosquito strain that is responsible for most disease transmission is in the process of rapidly evolving into two genetically distinct species. The hypothesis is that the two species are evolving in different directions in reaction to differences in environment and the challenges they face. The Imperial College researchers confirmed fears that this development is likely undermine efforts to control and treat malaria – conventional strategies are unlikely to be effective against both strains.

So what?

Forty years ago, malaria eradication failed at least in part because of a lack of diversity in the mechanisms employed, and the related evolution of resistance. Although global responses are broader than before, there are still questions about whether they are diverse enough, and whether the full breadth of approaches and knowledge are being applied at scale. Narrowness in responses may, in the worst case scenarios, be making human populations more vulnerable to malaria.

This means supporters of eradication and control programmes must continue to fund research that advances an evolutionary understanding and use it to keep ahead of the disease. This makes the levelling off of aid commitments reported in World Malaria Report 2010 all the more worrying, because much hope now lies in more funding for innovative basic and applied research. At least some of this research should start with the premise that the dynamics of malaria requires a rethinking of global efforts, with a special focus on capacity of existing health systems to deliver a broader range of treatments.

In this area, like in so many other aspects of international aid, silver bullets may well be red herrings. But history and recent research suggests that this is not a battle that should be conceded easily. Rather, as Chris Blattman notes, we can take some heart and some lessons from previous eradication programmes.

Smallpox was famously wiped out in the 1970s, with the last case being in Merca, Somalia in 1977. When the eradication was announced in 1980, the campaign was described “a triumph of management, not medicine”. This was an especially unusual pronouncement given it was made by the-then Director-General of the WHO.

But what exactly did this mean? According to one major account, the DG was referring to the emergent process of adaptation and learning – the evolutionary process within the programme itself – which

…more than any other element in the campaign, [was] the key explanatory factor of the ultimate success of the program… ”

What eventually eliminated smallpox was the combined approach of top-down problem-solving—mass vaccination to reduce disease incidence to certain levels —and bottom-up emergent experimental innovations in early detection, isolation and control - to push towards complete eradication.

Of course, smallpox is a very different disease, and may have been a better candidate for eradication than malaria – exactly because of the evolutionary nature of malaria.

But there is an interesting message here: if we want to deal with the evolving problem of malaria, we also need the global response to adapt and evolve, for organisations involved to think and act ‘outside the box’.

It is not clear what this would look like yet, of course – but it is worth noting that the eventual strategy for dealing with smallpox eradication was not originally employed or even envisaged by the implementing organisations.

Whether current efforts are able and willing to take on such an adaptive management mentality remains to be seen.

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When Can Crowds Outperform Aid Experts?

Posted in Biology, Campaigns, Evaluation, Innovation, Knowledge and learning, Natural disasters, Networks, Organisations, Self organisation, Technology on January 3, 2011 | 5 Comments »

When does crowdsourcing work best? New research from the Institute for Human Development provides answers which may be of relevance for aid projects and programmes.

There has been a lot written, spoken and blogged about the power of crowds in making decisions. In James Surowiecki‘s bestselling Wisdom of Crowds, published in 2004, the central thesis was that diverse groups are likely to make certain types of decisions and predictions better than individuals – even those with specialist expertise. As Surowiecki noted:

…under the right circumstances, groups are remarkably intelligent, and are often smarter than the smartest people in them”.

The six years since the Wisdom of Crowds was published have seen the rise and rise of online social networking and related technologies. Social media and the power of the crowd have been at the heart of everything from political resistance movements to presidential elections (and indeed, resistance movements following presidential elections). The term crowdsourcing was coined in 2006 to describe an organisational approach that harnesses the creative solutions of a distributed network of individuals. As one of the originators put it:

Simply defined, crowdsourcing represents the act of a company or institution taking a function once performed by employees and outsourcing it to an undefined (and generally large) network of people in the form of an open call. This can take the form of peer-production (when the job is per formed collaboratively), but is also often undertaken by sole individuals. The crucial prerequisite is the use of the open call format and the large network of potential laborers.”

There is a growing – some would say evangelistic – enthusiasm for crowdsourcing as the answer to a whole range of problems. Just a few initiatives off the top of my head: fundraising for socially responsible films, the development of transit planning in urban areas, combating corruption, creating markets for innovations, expanding scientific peer review processes. A quick Google illustrates just how expansive this agenda is.

The potential for crowdsourcing to contribute to international aid has also attracted a lot of attention, with perhaps the most prominent example being the role of new innovative technologies in the aftermath of disasters. The following is a typical example of the arguments made by the ‘pro-crowd’ camp:

The rapid proliferation of broadband, wireless and cell phones, coupled with new crowdsourcing technology, is completely changing the face of disaster relief. Everyone with a computer can provide crucial assistance, sifting through satellite photos, translating messages or updating maps, and most people are happy to do this free of charge — contributing to life-saving relief efforts is a powerful motivator… At a fraction of the cost of most relief budgets, crowdsourcing can solve coordination problems on the ground.

As many readers will be aware, crowdsourcing in disaster responses has been the focus of a passionate, sometimes vehement, and at times rather distracting debate.

My intention isn’t to retread ground that has already been well covered – and occasionally angrily stamped on – elsewhere. Instead, I want to explore evidence that tries to explain – following Surowiecki – the specific conditions under which a crowd is effective. Does recent research on decision-making yield any lessons or ideas worth a closer look?

Certainly, some of the crowdsourcing argument is borne out by the evidence. Numerous disciplines – from anthropology, cognitive psychology and evolutionary biology – suggest that collective decision making can help group members cope more effectively with unfamiliar contexts, and it is almost a cliche to say that humanitarian disasters are the archetypal unfamiliar context. However, reviews of this literature suggest many of these studies lack testable, well-structured concepts and hypotheses to explain exactly what collective decision making involves when compared to other kinds of decision making. They also often fail to examine the implications of different kinds of decision-making processes for the accuracy of decisions. These issues echo the challenges that have been put to the crowdsourcing community.

One recent exception to the above is simulation-based research that has been undertaken by analysts at the Institute for Human Development in Berlin. This work looks at a range of decision making processes, and suggests that there are two distinct ways in which groups can work to provide solutions to a problem.

First, individuals can follow specific ‘leaders’ in the crowd. This usually means drawing on those experts with information particularly relevant to the decision at hand. This is comparable to the typical aid decision-making process.

Second, crowds can work to aggregate information from the members, which is then made available to the crowd itself or to a third party. This enables decision making to be enhanced through ‘collective cognition’, a concept that underpins many of the arguments for crowdsourcing. This collective cognition can be unconscious emergent property, or it might be facilitated consciously through network interactions within the crowd.

The work by the HDI suggests a number of findings which are pertinent for the aid crowdsourcing debates:

  • a number of conditions influence when groups use ‘follow an expert’ or ‘wisdom of the crowd’ strategies. Specifically, the researchers found that the diversity of the group, the quality of individual information and group size all had a bearing on which approach is chosen.
  • in so-called single-shot decisions, experts are almost always more accurate than the collective across a range of conditions. However, for repeated decisions – where individuals should be able to consider the success of previous decision outcomes – the collective’s aggregated information is almost always superior
  • regardless of the decision-making approach taken, groups must have the potential to acquire information through social interaction, respond positively to those who possess pertinent information, and update their approaches based on the success of the previous decisions
  • In ephemeral and unstable social groups that make collective decisions only occasionally, individuals tend to follow the most informed individual. Stable social groups that encounter repeated decision points would do well to use some information aggregating process.

At the risk of over-generalising, the above suggests an emerging hypothesis – that for many simple or complicated issues where only one attempt is needed – ‘puzzles’ or ‘problems’, as a previous Aid on the Edge post put it – there is potential for experts to outperform crowds. The best illustration is to point out all those problems Malcolm Gladwell covered in Blink – detecting if a work of art was a fake, whether a teenager was carrying a gun, whether a fire would lead to a building collapsing, and so on.

In complex problems that require ‘multiple shots’, crowds can help augment expert perspectives by developing emergent solutions to evolving problems. The processes of information aggregation, transparent decision-making and effective feedback loops are essential here – all concepts which will be familiar to those interested in complex systems thinking.

Although the research is narrow, preliminary and based on mostly on theoretical simulations, the HDI work does point towards a more structured way of understanding the limits and possibilities of crowdsourcing. As such, it could be a constructive way to start to navigate some of the entrenched debates we have seen to date. Ultimately the research suggests that we shouldn’t be asking ‘does crowdsourcing work or not?’, but rather ‘when does it work, why, how, and with what benefits?’

This is not to say the answers will always be clear-cut or unambiguous, but asking the right questions will surely get us closer.

Now all we need is for some aid researchers to pick these concepts and questions up and run with them.

Or maybe an aid crowd would be better?

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Gazing at the fingerprints of chaos in the UK elections

Posted in Campaigns, Chaos, Institutions, Leadership, Public Policy on May 10, 2010 | Leave a Comment »

In the middle of the 19th century, one of the most widely publicised scientific struggles was to predict the motion of planetary bodies. Using Newtonian mechanics, it was simple enough to calculate the trajectory of one or two planets. However, when a third was added into the mix, the equations become complex and incomprehensible.

Steven Strogatz described the three body problem in a 2009 article:

It’s notoriously intractable, especially in the astronomical context where it first arose. After Newton solved the… equations for the two-body problem (thus explaining why the planets move in elliptical orbits around the sun), he turned his attention to the three-body problem for the sun, earth and moon. He couldn’t solve it, and neither could anyone else. It later turned out that the three-body problem contains the seeds of chaos, rendering its behavior unpredictable in the long run.

Newton knew nothing about chaotic dynamics, but he did tell his friend Edmund Halley that the three-body problem had “made his head ache, and kept him awake so often, that he would think of it no more.”

Newton wasn’t the only one. Two centuries on, in honour of his 60th birthday, Oscar II, King of Sweden established a prize for anyone who could find the solution to the so-called three-body problem.

The prize was eventually given to French Mathematician Henri Poincaré. Poincaré did not in fact manage to solve the three body problem. But as one of the judges put it ‘while this work cannot indeed be considered as furnishing the complete solution of the question proposed… it is nevertheless of such importance that its publication will inaugurate a new era in the history of celestial mechanics.’

Poincare found the trajectory of planets in the three body system to be one of ‘awesome complexity’ (Capra, 1996), and in describing it he inadvertently developed one of the first fractals. As he described it:

When we try to represent the figure formed by these [planets] and their infinitely many intersections, [they] form a type of trellis, tissue, or grid with infinitely fine mesh [which] bends back upon itself in a very complex manner… I shall not even try to draw it, [yet] nothing is more suitable for providing us with an idea of the complex nature of the three-body problem.

Poincare was, in the poetic words of Fritjof Capra, ’gazing at the fingerprints of chaos’. With the advent of computers over a hundred years later, scientists were at last able to represent Poincare’s figures. Here’s an early example, with each of the three colors represents the trajectory of a distinct body:

3body.jpg

(for more on this, and exotic-sounding things such phase space and strange attractors, see the ODI working paper on complexity and aid – concept 7)

The comparison between such systems and social, economic and political issues is not a perfect one. But as Deborah Barlow has written, as a catch all for what lives outside our model of reality, the three-body problem is at least a useful metaphor.

Certainly, the turbulence that has been experienced in the past few weeks of British politics, and the way the situation is continuing to unfold, is analogous to a two body problem evolving into a three body problem.

We saw this in the debates, when the surprising popularity of the Lib Dem leader left pundits struggling to assess the outcome of the election – ‘the most unpredictable in a generation’. We saw it on election night, when the distribution of votes confounded all attempts by the exhausted TV presenters to explain what was happening. And we are seeing it now in the negotiations, with each party having to think through a range of possible future permutations and combinations, with each move potentially triggering a dizzying number of consequences. We also have to look forward to the potential complexity of the legislative and policy-making arrangements under a hung parliament with three parties.

Get it right, and it could make for the most interesting and tranformative period in British politics for decades. Get it wrong, and things could descend into turbulence and chaos.

Newton, one imagines, would be chuckling to himself in the grave.

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Lessons in Distributed Leadership from the Obama Campaign

Posted in Campaigns, Knowledge and learning, Leadership, Networks, Organisations, Public Policy, Strategy on December 4, 2009 | 4 Comments »

The Obama presidential campaign owed its victory not to a single charismatic candidate, but to the efforts of a disciplined and motivated organisation whose influences go back to landmark civil rights movements. Many of the principles were consistent with the emerging ideas of ‘complex adaptive leadership’.

A recent MIT lecture featured Marshall Ganz, veteran of the 1960s civil rights movement and key activist in the Obama election campaign, who described how the principles and practices he learned over decades of voluntary organising and leadership were applied in last years ‘against the odds’ victory.

Ganz’s view was that leadership involves “taking responsibility to enable others to achieve purpose in the face of uncertainty.” Leaders “recruit, motivate and develop others, constructing a community around common interests, and building capacity from within the community”. Effective volunteer-based organisations cannot rely on rigid hierarchies or command-and-control strutures but must instead engage and enable lots of people to become innovators who are adaptive in the face of uncertainty.

Such “distributed leadership” draws from and resonates with emerging theories  of complex adaptive leadership. From this perspective, leadership is not about a person, but is rather an interactive dynamic, within which any particular person will participate as leader or a follower at different times and for different purposes. Leadership is not limited to a formal managerial role, but rather emerges in the systemic interactions between diverse actors. As Charles Heskscher puts it:

There is a growing sense that effective organization change has its own dynamic, a process that cannot simply follow strategic shifts and that is longer and subtler than can be managed by any single leader. It is generated by the insights of many people trying to improve the whole, and it accumulates over [time]” 

This kind of “distributed leadership” is precisely what the Obama campaign cultivated and invested in, says Ganz. Thousands of people acquired the skills and practiced “the arts of leadership necessary to self-govern in democracy.”

Some unique conditions made this campaign so successful, including Obama’s story of hope, which drew on a persuasive personal narrative. There was also the campaign’s strategy of developing grassroots capacity to win caucuses and close primaries; its use of the Internet to attract an army of small-scale, repeat contributors; and its capacity for “continual learning” about what was and was not working.

Ganz’s 90 minute lecture can be seen here: http://mitworld.mit.edu/video/662

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