Considering how to conceive of complexity, with particular emphasis on the lessons of the performance of the U.S. financial system in the early 21st century…
Imagine two classes of complexity. In the first class, entities are numerous but connected by relatively few links and these links are more oriented toward cooperation (i.e., working at the same level) than control. Stability is low; creativity is high; but consequently failure is also high. Adaptation is rapid, and the rate of emergence is high.
In the second class, everything is reversed – adaptation tends to be controlled, efficient, according to plan, with many links. These links offer effectiveness, predictability, and consistency at the expense of…great expense.
Class 1 systems are dangerous but exciting and interesting, in a word, chaotic. Class 2 systems function at the edge of chaos, so in truth they are likely to be courting disaster despite appearing totally controlled so that, until they trip, they appear utterly secure. Imagine a continuum of complex systems with Class 1 at one end and Class 2 at the other end. One may hypothesize that as one moves toward Class 1 conditions, one is regularly faced with more danger but of the day-to-day variety, with which system components are familiar: an environment of constant small crises. Conversely, as one moves toward Class 2 conditions, the number of crises drops but any crises that do occur tend to be very destructive.
Complexity sounds wonderful, bringing, as it does, wealth and capability. Implicit in this assumption is the desirability of pushing complexity to its limit, of mourning any movement in the direction of collapse. Thus, a Wall Street CEO might brag about the rapid emergence of new forms of financial complexity – derivatives, CDOs, synthetic CDOs, ad infinitum. But, with Tainter, “the increased costs of sociopolitical evolution frequently reach a point of diminishing marginal returns” [Joseph A. Tainter, The Collapse of Complex Societies (Cambridge: Cambridge University Press, 1988) 93]…a gentlemanly way of referring to the Recession of 2008.
Although it may be nearly beyond the capacity of human psychology to quit while winning, the theoretically obvious danger of falling off the cliff on which one is running should prompt us to think about the conditions under which voluntarily slowing down might be the better part of wisdom, as Sheila Baer and Elizabeth Warren famously tried to point out.
In brief, how might a society figure out that it is time to reduce its complexity voluntarily—not accept collapse but accept the need to move a few measured steps in the direction of collapse in order to shore things up?
The insight that seems most immediately to flow from asking this impertinent question is that any argument that might be offered by a hubris-infected Western believer in progress to the effect that “team players” would never be so pessimistic as to advocate caution is immediately dismissed. That is, the very issue of whether complexity is good or bad is nothing but a straw man. A second dimension, in addition to the dimension of complexity, must be introduced, and for me that dimension is the social good (realizing, of course, that other dimensions might be selected, e.g., protection of the hive or godliness). In essence, then, the second dimension is some measure of “quality” or “performance.” All manner of fairly obvious questions flow from this: How well is the system functioning? For whom is it functioning? How sustainable is it? Such questions will inform our understanding of the degree to which the level of complexity and rate of complexification of any given system are desirable.
The essential point to make the case for the significance of complexity as a critical perspective for decision-makers is straightforward, albeit very challenging to understand: complexity implies nonlinearity. Rather than assuming tomorrow will resemble today, in a complex system, the wise assume that tomorrow, the world may change. This is the seemingly simple message that the Neo-Cons failed to digest when they launched the 2003 invasion of Iraq anticipating that the Iraqis would “welcome us with flowers.” A day after the near-instantaneous U.S. battlefield victory, that might have indeed been the case; then the Baghdad Museum was trashed under the eyes of the new conqueror, the electricity failed to come back on, and four thousand GIs died before the U.S. retreated. Similarly, this message about the inevitability of nonlinearity was missed by all the brilliant finance geeks of Wall St. as they pushed the envelope of U.S. financial system complexity during the first eight years of the new century.
First, things changed by exponential behavior. If that was not bad enough, the various interacting variables of course had different rates and direction of exponential change with all sorts of delays. Worse, the rate of any given variable changed over time, so any projected exponential curve soon trailed off into the twilight zone of computer models completely detached from reality. From a theoretical perspective, none of this was remotely surprising, but the U.S. political, military, and financial elites were trained to worship at the shrine of linearity: big powers rule, strong armies win, the rich just keep getting richer, growth has no limits.
And even if someone understood the fallacies underlying these increasingly naive assumptions, one of course still had no good way of determining when “enough was enough.”