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The strange thing about emergent phenomenon is that it can often seem like magic to even the most scientifically inclined person. I think it is largely because our minds evolved to be able to recognize and characterize certain kinds of patterns. Enormously complicated interconnected nonlinear systems were not one of the things our minds are naturally built to deal with. We like to understand systems as a series of rules where every action has a cause and effect. The problem with emergent systems is that they are often composed of many heterogeneous parts that act in nonlinear ways. This means that dissecting the tangent of causality in such systems is practically impossible, because it gets lost in a sea of other interactions that are affecting the system in often unpredictable ways.

I read somewhere that the butterfly effect really is not as significant as it would seem. In essence a butterfly could flap its wings and cause a storm halfway across the world, assuming the weather patterns are chaotic or highly sensitive to initial conditions. Yet to trace the line of causality to that specific butterfly would be impossible. The problem is that there are so many other variables in the system (other butterflies to start with) that are doing things to change the system, just like the hypothetical storm-causing butterfly. These lines of causality become completely tangled within this system and we lose our ability to say that a single butterfly at a specific point in space-time caused a horrific storm. Instead, all we are left with is the knowledge that, yes it could have been the butterfly, but it could have more likely been any number of other factors.

Complications in causality factors into many other complex dynamical systems. That's one of the reasons why fighting cancer is so hard. Cancer does not have a simple on-off switch. It is a complicated set of malfunctions and conditions that can change a cell from its normal healthy cell-type (or personality, say) into an unhealthy, voracious cell-type (or a psychopathic maniac). It is hard to trace the causes to a single gene or environmental factor. We do know that there are things that can tend to cause cancer, and there are many genes that have been identified as increasing the chance of getting cancer, but there is still no comprehensive understanding of the full set of underlying mechanisms and how different contributing factors have different causes and effects that lead up to cancer.

Other systems where lines of causality become tangled range from ecosystems, to economics, to the weather, and to biology in general. I wonder if it would be possible to develop a general framework to deal with these kinds of systems. It may be necessary to throw out a lot of our preconceptions about how to look at these kinds of systems. Science, for example, is very good at breaking up a system into pieces, examining the pieces, and seeing how they fit back together. The problem with this reductionist method is that it can miss out on higher level phenomenon that is only present when the system is functioning as a whole. Another example of this is in complicated signaling transduction pathways or gene networks, scientists often can not analyze the system as a whole, so they look at pieces of the system, and then try to put it together and reproduce the dynamics of the whole system.

I wonder if it is possible to come up with an evolving classification system for emergent phenomenon that would be able to recognize certain types of phenomenon and be able to predict the set of interactions underlying the phenomenon. If it could find an appropriate set of interactions, model, or even a suite of possible models, then it could be possible to be able to know the complicated lines of causality, or at least what the probable lines of causality were. The reason why the classification scheme of emergent phenomenon would have to be evolving in itself is because if it couldn't evolve there is no way it could deal with novel and unpredicted dynamics.

There is at least one huge potential problem with this classification scheme idea (and there are probably more). I've mentioned in my previous post The Adjacent Possible that there are an essentially infinite number of possible interactions, and therefore it is impossible to predict all possible configurations between objects in phase space. Hence, trying to catalog all emergent phenomenon may seem like a silly and useless idea. Yet, I have a hunch that there are certain types of interactions that are more likely to occur between objects than others, and that though there may be a large number of possible interactions and also a large number of potential objects, the distribution of objects and interaction is not uniform. There may be a few incredibly wacky interactions and even wackier objects (a conscious entity is a pretty wacky object in my opinion), but the majority of objects and interactions of interest fall into a relatively small number of classification schemes (at least in comparison to infinity). My justification for this hunch is largely based on the feeling that if the distribution of objects and interactions in the universe was entirely uniform, it would be impossible for complicated systems to develop.

The reasoning goes as follows: Stuart Kauffman discusses a hypothetical situation where all the biochemicals in all of biology were combined into a single vat. In the first few instants there would be an untold number of interactions between these biochemical objects. This would be similar to the case where the distribution of interactions and objects was made uniform from its natural non-uniform shape. Yet after a few instants this bubbling froth of biology would eventually create molecules that would hijack the entire system, poisoning most other molecules, until it finally reached a state where there were only a relatively small set of interactions occurring. Hence, biology has generated ways to keep the distribution of objects and interactions between objects very non-uniform...because if it ever approached uniformity everything would fall apart.

This seems to suggest to me that most emergent systems will not have a uniform distribution of underlying objects and interactions. In fact, the distribution of interactions and objects must be skewed in such a way as to give the system some sort of useful higher level property. Any sort of non-uniformity in the distribution of objects and interactions on any and all levels of an emergent system seems to suggest that though the number of possible interactions and objects is essentially infinite there is a much smaller number of interactions and objects that are actually implemented in reality.

More on this later...