These remarks were presented on June 10, 2010, to a conference sponsored by the Madrona Institute in Santa Fe, New Mexico.
When Merle Lefkoff asked me to give a presentation on Complexity Science – and in fact to open the discussion today – my first thought was to think it crazy to lead with comments by someone as new to Complexity as I am, especially when there are so many people in the Madrona circle who are so genuinely knowledgeable. I’m a lawyer and a policy wonk by training, and I have no specific science background. But as I mulled things over, I decided she wasn’t out of her mind after all.
I cannot pretend to understand Complexity applications as well as real experts in the room like Desmond Saunders-Newton, Stephen Guerin, or Aaron Frank, much less the deep mathematics of the field as practiced by Ralph Abraham. I can perhaps speak at least a little bit about Complexity’s challenges to the broader public policy community, however – in part precisely because I am so new to the field. Any perplexity or apprehension on my part is likely to reflect problems in how the broader policy community will be able to take on board insights gleaned from the “science of surprise.” And if even I prove able to gain any insights from Complexity, perhaps others will too.
Let me begin by saying that I think government policymakers at the most senior levels are notably behind the curve in recognizing that Complexity Science may have important implications for their work. At more specifically technological or programmatic levels – in certain defense and IT applications, for instance – some experts seem indeed to have made Complexity perspectives a part of their working world in government and as contractors and consultants.
This openness to Complexity is not common, however, and at any rate only goes so high; it scarcely touches grand strategy and other policymaking at the most senior levels of government. Policy formulation at those altitudes still seems stuck in older modes of thought that revolve around the idea that policymakers can systematically plan their way into the distant future. One school, which currently seems to be dominant, devotes itself to hitching policy formulation to the output of “scientific” expertise, particularly in social science research. This has been an important theme of the Progressive tradition over the last century or so, and is visible perhaps most obviously today in our government’s proliferation of unelected technocratic policy “czars,” and its devotion to “putting science in its proper place” – namely, ostensibly in the drivers’ seat of public policymaking. Those who don’t buy into this technocratic ideal, seeing policymaking as more of an art than a science, often prefer approaches that purport to derive operating principles from timeless verities about human nature, the character of power, or other aspects of “how the world works.”
Very few participants in top-level policymaking, however, seem at all prepared for the insights that it seems to me Complexity Science offers. Indeed, Complexity seems deeply subversive of these paradigms – both of which implicitly or explicitly assume, to one degree or another, that the policy environment is basically understandable and predictable, in the sense that right-minded officials can reliably steer the system to the outcomes they desire by following recipes that are themselves ascertainable through the exercise of reason and virtue. I’d like to say more about this subversiveness.
Before I go any further, however, let me note that not all of the interesting aspects of Complexity Science seem equally interesting from a policy perspective. One of the most important insights that I understand Complexity to offer in the biological sciences and computing, for instance, involves the phenomenon of “emergence” – the dynamic by which complex and sophisticated macro-level patterns of behavior can develop from the interactions of elements or components that themselves follow only very simple operating rules. This spontaneous self-organization of high-level complexity from low-level order is a remarkable thing.
From a policymakers’ perspective, however, the implications of emergence seem ambiguous, for it is not clear the degree to which emergence can be too useful a tool for high-level policymaking. It might be interesting and valuable for a workshop group at a Madrona Institute conference to study what “emerges” from participants’ interactions, but such a method seems a bit hit-or-miss for much acceptance in senior-level national policy-making.
We do not ask our leaders to “trust emergence” by sitting back to see what happens in the whirl of public policy contingency: we ask them to shape what happens. We ask them to do what they can to ensure that what happens next is “better” than what happened before, or what would have been the case had they not acted. The problem is that in Complexity Science, emergence seems interesting precisely to the extent that the high-level order it produces is not apparent – or perhaps even predictable at all – simply from scrutinizing the lower-order rules of interaction. Complexity just sort of happens all on its own, and emergence wouldn’t be so fascinating if you knew ahead of time what would emerge. The phenomenon of emergence is clearly a profound analytical insight, but I have not yet been persuaded that it has anything like the kind of relevance to senior-level policymaking that it does, for example, in evolutionary biology, systems analysis, or computer science.
The very unpredictability of emergence, however, points us to a powerful Complexity insight that I think is of enormous importance to policymakers – and one I think the policy community should find deeply challenging. I refer to the deep notion of outcome-unknowability that seems inextricably bound up with Complexity Science. In this regard, I see as the iconic scientific illustration the “sand pile” experiments conducted in the 1980s by the Danish theoretical physicist Per Bak and his colleagues.
I hope that one of you will correct me if I get the science wrong here, but as I understand these experiments, they involved dropping grains of sand continuously onto a table and observing the characteristic sand piles that result. At some point the growing pile will partially collapse, through the occurrence of various large or small avalanches. In a given period of time, there may be a certain number of avalanches – and any given grain of sand might perhaps cause one – but it is posited to be literally unpredictable when a cascade will occur and how big it will be.
As I understand things, this is taken at some level to be illustrative of the behavior of all complex systems, including complex adaptive systems, a special case of complex systems in which the interconnected elements have some capacity to change and “learn” from the experience of their interaction. Since human society is understood to be a complex adaptive system – and more specifically, a complex adaptive social system, in which we are the interconnected elements – this presumably has implications in the policy world as well. Complex adaptive systems are generally relatively resilient in the face of perturbations (e.g., a new grain of sand, or a particular policy input) but every once in a while even a small addition can catalyze a dramatic phase transformation (e.g., an avalanche, or sweeping systemic change in the socio-political order).
This certainly seems to make Complexity relevant to policy-making, but it also suggests why Complexity is so challenging. To wit, it appears to be the case with complex adaptive systems that whether a phase transformation will occur, and what sort of transformation it will be, are things that are fundamentally unpredictable – and, crucially, not just unknowable because as a practical matter we cannot gather and manage enough data about initial conditions, but in some sense unknowable even in principle.
And since society is itself a complex adaptive system, it seems to me that Complexity is therefore deeply subversive of all traditional ways of approaching policymaking. It pulls the conceptual rug out from under the feet of the “scientific” technocrat and the policy “artist” alike, by undermining our faith in the ability of deliberate and purposeful policy inputs reliably to produce predictable situational outcomes. Through the lens of Complexity, traditional policymaking starts to look like hubris on a colossal scale.
If coherent policy formulation is to survive the insights of Complexity, therefore, I would think we need to re-learn policy-making at a pretty basic level. To my eye, the “science of surprise” would seem to push us powerfully away from traditional modes of government planning and strategy and into more scenario-based thinking. This is a shift that we have discussed in previous Madrona Dialogues, one that private industry began some time ago, and one that our military also understands quite well. It is a change, however, the need for which top-level government officials and other political leaders as yet show little sign of understanding.
To borrow a term from Nassim Nicholas Taleb, we may need to bring more of a “Black Swan” sensibility to top-level policymaking, in which it becomes a focus of policy responsibility less to plan out specific paths into specific desired and predicted futures than to maximize our preparation for the unforeseen opportunities and perils we can be quite certain will at some point come along. This might be, for instance, a world in which policy choices are prized as much for their likelihood of providing acceptable results if their animating assumptions turn out to be quite wrong as for any outcomes they promise on their face. (Which policy postures, in other words, degrade well? Which ones could most elegantly handle their own mistakenness?) The future of policymaking might thus turn out to be as much about improvisational opportunism and hedging strategies as about any sort of “strategic planning” in the traditional sense.
Well, enough speculation. These are necessarily tentative thoughts, but I think they give a feel for the ways in which it seems to me that Complexity can – and perhaps must – revolutionize high-level policymaking and grand strategy. I’d love to see us pursue these questions in greater depth at this conference, and I look forward to hearing what all of you have to say.
-- Christopher Ford