The Afghanistan counterinsurgency causal loop diagram makes another appearance in this TED talk, in which Eric Berlow shows the hypnotized chickens the light:
I’m of two minds about this talk. I love that it embraces complexity rather than reacting with the knee-jerk “eeewww … gross” espoused by so many NYT commenters. The network view of the system highlights some interesting relationships, particularly when colored by the flavor of each sphere (military, ethnic, religious … ). Also, the generic categorization of variables that are actionable (unlike terrain) is useful. The insights from ecosystem simplification are potentially quite interesting, though we really only get a tantalizing hint at what might lie beneath.
However, I think the fundamental analogy between the system CLD and a food web or other network may only partially hold. That means that the insight, that influence typically lies within a few degrees of connectivity of the concept of interest, may not be generalizable. Generically, a dynamic model is a network of gains among state variables, and there are perhaps some reasons to think that, due to signal attenuation and so forth, that most influences are local. However, there are some important differences between the Afghan CLD and typical network diagrams.
In a food web, the nodes are all similar agents (species) which have a few generic relationships (eat or be eaten) with associated flows of information or resources. In a CLD, the nodes are a varied mix of agents, concepts, and resources. As a result, their interactions may differ wildly: the interaction between “relative popularity of insurgents” and “funding for insurgents” (from the diagram) is qualitatively different from that between “targeted strikes” and “perceived damages.” I suspect that in many models, the important behavior modes are driven by dynamics that span most of the diagram or model. That may be deliberate, because we’d like to construct models that describe a dynamic hypothesis, without a lot of extraneous material.
Probably the best way to confirm or deny my hypothesis would be to look at eigenvalue analysis of existing models. I don’t have time to dig into this, but Kampmann & Oliva’s analysis of Mass’ economic model is an interesting case study. In that model, the dominant structures responsible for oscillatory modes in the economy are a real mixed bag, with important contributions from both short and longish loops.
This bears further thought … please share yours, especially if you have a chance to look at Berlow’s PNAS article on food webs.
3 thoughts on “Return of the Afghan spaghetti”
Hi Tom, Thanks for you very thoughtful commentary. It is actually the most thoughtful comments I have seen regarding the talk. I completely agree with you. I struggled with the Afghan COIN diagram because it really has so many ‘apples vs. organges’ comparisons, with seemingly varied currencies among links. I very much appreciate that you read the PNAS paper on food webs, because that (and also in the Brose et al 2005 Ecology Letter paper) is where we really do see some drammatic examples of the spheres of influence remaining remarkably ‘local’. My goal in this talk was to stimulate some thought about how general this result might be. That said, I do strongly believe that the more general, conceptual, and not quantitative point I wanted to make generally rings true. Most of the time I spend advising students or consulting groups, etc. is spent getting them to get over their fear of embrace the complexity of a problem before diving in with a pet solution. But I agree that is a bit different.
Great find Tom,
It was indeed refreshing to see Eric embrace complexity instead of ridiculing people’s attempts to understand it. Communicating the insights of any model can be quite difficult in today’s tag line media, but I think he does a remarkable job in just a few minutes.
I have to agree that while there may be ample cases where influence can be remarkably local, there are just as many cases where higher leverage points exist further away or are inextricably linked with other import feedback loops. That said, I think pragmatic approaches to explaining complex problems are invaluable to reaching wider audience and this if fundamental to problems that are intertwined with society.
Yesterday I saw John Sterman present the C-ROADS work, which is a case in point for how simplified representations can not only be rigorous, but also more within reach of non-experts. Yet, even then was still left wanting more clarity in explanation of what the model was doing and why. I don’t know what the answer ultimately is, but I think exploring all these different paths is more on track then simply throwing your hands up.
Thanks for the shout-out about C-ROADS and the Climate Interactive project. It’s great that my talk left you wanting more clarity about the model — that’s the goal, of course: in any short presentation all I can hope to do is stimulate people’s curiosity to get under the hood, see what’s going on, and take the model out for a spin themselves. See http://climateinteractive.org for that opportunity.