BOOKIES HAVE A SAYING, "There are three horses who have never come in win, place, or even show. Their names are Coulda, Woulda, and Shoulda." Bookies live--and sometimes die--by the accuracy or inaccuracy of their predictions. Their performance is immediately obvious to all involved.
The same, however, cannot be said of many academics, even less so of pop-science writers. Despite what you've heard about the hypothetico-deductive method being the touchstone of science, it is the exception when predictions by academics are put to the empirical test and they have to live or die by the results. It's all too easy for them to come up with 'supplementary hypotheses' to explain their way out. (Try out a supplementary hypothesis on Tony the Crippler when he knocks on your door to collect the two grand you dropped on a pony that finished dead last. You'll soon drop dead). This lack of accountability is further parlayed as one moves from the physical sciences, to the biological, to the behavioral, to the social sciences, reaching the level of a dead cert in literary studies.
The worst such abuses occur when terms that have a clearly defined meaning, usually mathematical, in the physical sciences are imported into literary studies as metaphors. By the time they reach pop books, a good skeptic's baloney detector should be red-lining. Latest to make this transition are the two C-words--Chaos and Complexity, and their hybrid offspring, Contingency and Counterfactuals. Together they are the academic counterparts of Coulda, Shoulda, and Woulda. They are the four hobby horses of Chaostory. What makes this jockeying all the easier is that the restricted, stipulative definitions of these terms, if not the opposite, are certainly a long way from our understanding of them in everyday discourse.
CHAOS: IT'S ANYTHING BUT HELTER SKELTER
Let's start with chaos. The dictionary defines it as: "(1) utter confusion or disorder; (2) the formless matter supposed to have preceded the existence of the universe." Roget's Thesaurus gives "disorder, derangement, and anarchy" as synonyms, and "order, uniformity, regularity, and symmetry" as antonyms. But in the world of Chaos/Complexity theory one encounters such terms as "deterministic chaos" which results from "deterministic dynamical equations." Conceptually, we are told, "chaos is intrinsic to the system and clearly distinguished from the effects of random or 'stochastic' fluctuations in the external environment." Therefore, distinguishing deterministic chaos from stochastic ('true') chaos "is one of the principal hurdles that confronts 'chaologists'--scientists working with potentially chaotic systems."  What is the difference between deterministic chaos and stochastic ('true') chaos? The answer is the Attractor, which can be either a Fixed Point Attractor or a Strange Attractor. This all really makes sense within the world of physics and non-linear mathematics (see Pigliucci's article in this issue for definitions and an explanation), but becomes meaningless chaobabble when applied elsewhere.
COMPLEXITY: THE SEARCH FOR SIMPLICITY
My dictionary defines complexity as "intricate, knotty, or perplexing." Its use in Chaos/Complexity theory certainly is perplexing, because there it means a search for simple rules that can explain how the universe can "start with a few types of elementary particles at the big bang, and end up with life, history, economics, and literature."  How can this happen? The answer offered is self-organized criticality (criticality, another C-word), "the tendency of large systems with many components to evolve into a poised, 'critical' state, way out of balance, where minor disturbances may lead to events called avalanches. Most changes take place through catastrophic events rather than by following a smooth gradual path"  (Catastrophic--yet another C word).
If the butterfly flapping its wings in Brazil and setting off a tornado in Texas has become the mantra of Chaos theory (even though there's no evidence that a gaggle of butterflies has ever so much as generated a zephyr), Per Bak's Child's Sand Pile is the icon of Complexity theory (FIGURE 1). He describes it as follows:
In the beginning, the pile is flat, and the individual grains remain dose to where they land. Their motion can be understood in terms of their physical properties. As the process continues, the pile becomes steeper, and there will be little sand slides. As times goes on, the sand slides become bigger and bigger. Eventually, some of the sand slides may even span all or most of the pile. At that point, the system is far out of balance, and its behavior can no longer be understood in terms of the behavior of the individual grains. The avalanches form a dynamic of their own which can be understood only from a holistic description of the properties of the entire pile rather than from a reductionist …