In Defense of Chaos (eBook)

The more complex a system is, the more numerous are the types of fluctuations that threaten its stability.—Prigogine and Stengers

Science is competent to establish what is. It can never dictate what ought to be.—Ludwig von Mises

Science is organized unpredictability.—Freeman Dyson, physicist

Why did the shooting of hundreds of Russian protesters in 1905—an incident known as Bloody Sunday—produce the opposite of its desired effect, and significantly increase opposition to the Czar? Why did the unemployment rate for the disabled rise a few years after President George H. W. Bush signed the Americans with Disabilities Act (ADA) in 1990—a law enacted to improve working conditions for the disabled?1 And why did illegal entry continue to increase after the U.S. Congress passed a series of reforms in 1992 designed to curb immigration from Mexico? After all, the decision–makers in Washington, D.C. had tripled the budget of the Immigration and Naturalization Service (INS), bringing it to $4 billion, and had doubled the number of border patrol agents, to 7,000. But the new law seemed only to do the exact opposite of its proponents’ intent, contorting to a sort of “political jiu-jitsu,” as coined by political scientist Gene Sharp.2

What these backfiring missteps reveal is that nature always sides with hidden flaws and uncertainty. As so aptly stated by Murphy’s Law, “if anything can go wrong, it will.” Things don’t always go as planned, because complex systems operate in a specialization-vacuum mode in which information is often encapsulated—preventing or distorting feedback. Complexity clouds or camouflages what resources should be used, as well as what determines “the legitimate values of the system,” contends systems scientist and professor C. West Churchman in The Systems Approach.3

In other words, bad information inevitably leads to bad choices. Worse still, most information is usually highly decentralized, based on the localized conditions, which makes feedback almost meaningless to systems dependent upon linear-inclined centralization. Even if a thread of information is particularly accurate, the possessor has little way of knowing its priority or importance. Complexity has the propensity to overload systems, making the relevance of a particular piece of information not statistically significant. And when an array of mind-numbing factors is added into the equation, theory and models rarely conform to reality. That is because the more complex the structure, the more vulnerable it becomes to system failure. But the complexity by itself is not the catalyst in which a system might crash. Rather, it is how the complexity emerges in a system that determines whether that system will do what it was intended to do or morph into an unworkable organization clogged by bottlenecks and blockages. Does the system emerge through a natural course of events vetted by trial and error, or does it emerge by artificial means that detach the system from its external, self-assembled process?

In 1936, the man most often credited for popularizing the concept of why things backfire, sociologist Robert K. Merton, referred to this phenomenon as “the law of unforeseen consequences.” In an influential paper, “The Unanticipated Consequences of Purposive Social Action,”4 Merton identified five sources of unanticipated consequences. The first two are the most relevant: ignorance and error. The third one, “imperious immediacy of interest,” is a situation in which someone is so eager to do something that he will purposely ignore any possible failure from side effects. The next one involves America’s old-fashioned Protestant work ethic. Labeling this concept “basic values,” Merton wrote that asceticism “paradoxically leads to its own decline through the accumulation of wealth and possessions.” The final source is the “self-defeating prediction.” This unintended consequence occurs when predictions of possible future change cause people to alter their ways. Similar to a scientist’s altering of an experiment simply by observing it, the prediction in and of itself can change the course of history, taking it to new, but unexpected alternatives.

In Systemantics: How Systems Work and Especially How They Fail, pediatrician John Gall took a hard-hitting approach to explaining why many large-scale international organizations fail. Gall contended that “the larger and more complex the system, the less the resemblance between the true function and the name it bears.”5 He maintained that “complex systems are beyond human capacity to evaluate,” and that as they grow in size, they tend to oppose their stated function and begin to “encroach.”

One of Gall’s most ironic examples was the federal government’s policy to subsidize farmers in order to prop up food prices, while simultaneously issuing food stamps to the poor because food prices are too high. Throw in the bizarre policy of funding the efforts of the National Institutes of Health to battle obesity, and it would appear that some sort of “mad politician disease” had contaminated Washington, D.C.

But Gall’s greatest revelation was that complex systems tend to function as “problem reprocessing machines.” When systems are unable to make progress (i.e., when they fail), administrators and central planners find it convenient to transform persistent problems into problems of another type, so as to make them almost undetectable to economic indicators. In other words, they misguide or relabel what the system was originally set up to do, validating the old adage, “Bureaucrats do not change the course of the ship of state—they merely adjust the compass.” In this way, a failure can be redefined as having been a success, which coincidentally has the effect of preserving jobs for the bureaucracy and “staffocracy.” Or, to put it in a more skeptical context, every system will do what it must to justify its own existence. In many cases, the biggest successes of government are actually failures that don’t instantly materialize.

But relabeling failure as success has other problems. The double-edged sword cuts both ways. Actually, reaching the ultimate goal risks loss of one’s source of income. If crime could be completely eradicated, would there still be a need for police? If fires no longer plagued mankind, would anyone require the services of firefighters? And if every possible crisis were to be amicably resolved, would the system of governance become obsolete and needless? Systems walk a fine line between success and failure. Too much of either one can lead to undesirable consequences. This aphorism perfectly reflects the “[Clay] Shirky Principle” whereby “institutions will try to preserve the problem to which they are the solution.”

John Gall is best known for his Gall’s Law, which states, “A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works and cannot be patched up to make it work. You have to start over with a working simple system.”

Similarly, another popular law that explains why systems continuously fail has been attributed to science fiction writer Jerry Pournelle: the “iron law of bureaucracy.” Pournelle argues that in “any bureaucratic organization there will be two kinds of people: those who work to further the actual goals of the organization, and those who work for the organization itself.” The tendency is for the second type of person to gradually take control, moving the group in a direction counter to the organization’s stated goals. After all, organizations are organized for the benefit of the organizers.

Another book dealing with failure is Why Most Things Fail: Evolution, Extinction and Economics, by Paul Ormerod,6 who taught economics at the Universities of London and Manchester. Inspired by recent advances in evolutionary theory and biology, Ormerod writes:

Failure is pervasive. Failure is everywhere, across time, across place and across different aspects of life; 99.99 percent of all biological species that have ever existed are now extinct. More than 10 percent of all the companies in America disappear each year.

Delving into the concepts of creative destruction and adaptive evolution, Ormerod argues that for an entity lacking the ability to evolve to meet new challenges, failure is almost unavoidable. He maintains that the best-laid plans do not provide a perfect equilibrium, but instead trap biological species and human systems within a continuity that’s locked down and static. This situation makes long-term predictions almost useless. And the principle behind this is obvious: What you can’t predict, you can’t avoid. Although corporate executives plan ahead extensively, plants and animals do not. Yet companies are just as vulnerable to sudden extinction as was the dodo bird.

The System Failure Phenomenon

With almost surrealistic consistency, governmental policies, business projects, and everyday plans routinely backfire in grotesquely spectacular but often karmic ways. This particular phenomenon is now recognized as the “boomerang effect.”

So what causes such boomerang effect episodes? Primarily, it is a system failure pumped up on steroids. These failures surface...