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An independent forum for a critical discussion of the integral philosophy of Ken Wilber
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A Reply to DeGracia
Andrew P. Smith
Evolutionary complexity develops primarily through socialization, by which I mean the association of what Wilber calls holons.
Donald DeGracia begins his article “Evolution: Chance or Dynamics?” with the claim that “the discussions about evolution are rather dated”. Maybe he didn't read all the discussions. In my article “Does Evolution have a Direction?” I discussed the role of constraints in evolution, and in particular noted how not only the dynamics but the structure of networks may be constrained by certain rules. In fact, a central theme of my argument, discussed in far greater detail in the book The Dimensions of Experience, is that evolutionary complexity develops primarily through socialization, by which I mean the association of what Wilber calls holons—atoms, molecules, cells, organisms, for example—into networks.
As DeGracia notes, “In a network, most of the configurations are unstable.” But since, as he also notes, the number of possible configurations increases rapidly with the number of nodes, so it turns out does the number of stable or functional ones. This is why socialization is such a powerful force in creating complexity, which I define operationally as the number of different states in which a system can exist.
DeGracia argues that “it is likely that evolution by intrinsic network constraints is a much more important factor than selection by random mutation is [in] the production of new species.” He seems to be conflating the two key elements of Darwinism—random variation and natural selection—when in fact they can operate independently.
Thus scale-free networks, which I discuss in “Does Evolution Have a Direction?” (and which also feature prominently in Huang's article that DeGracia refers to), are an example of a constraint-driven process, but they definitely have properties that enhance survival and which therefore can be subject to selection (Huang makes this point as well). Scale-free organization in the mammalian brain increases the efficiency of communication among neurons—thus minimizing metabolic requirements—and also reduces the likelihood that focal lesions or injuries will have a major impact of the network's global properties. Conversely, as McShea (2005) has pointed out, there are other types of complexity-increasing processes that involve random variation but which proceed in the absence of selection.
I think all evolutionists today are well aware of the relative value of holistic and reductionist approaches, and probably all accept that at least some evolution is driven by constraint (though they may debate fiercely over its significance). In fact, there is so much interaction or potential for interaction between random variation and constraint-driven evolution that it may not be meaningful to argue that one or the other is more important. The emergence of scale-free structure was apparently critical in the evolution of the human brain as well as in the evolution of human societies, but in both types of organization random changes in the nodes (neurons or individuals) may have powerful effects on the properties or potentialities of the networks. This is particularly evident in modern human societies, where new ideas can spread much more quickly than was the case even a few decades ago.
Conversely, this type of organization could only arise in the first place from certain kinds of cells or organisms, namely, those that are capable of communicating with hundreds if not thousands of other similar cells or organisms. So—in this specific but very important instance—random variation and intrinsic constraints may be thought of as two kinds of processes that have periodically been capable of synergizing.
Finally, I hope this new appreciation for networks is not confined to those within cells. Networks exist within networks within networks—in other words, there is a hierarchical organization of networks. At the very end of his article, Huang seems to recognize this, as he notes that
the detailed behaviour of a single [intra]cellular network [within a particular cell] would not matter, while sloppiness [i.e., variation] within the network of individual cells may even be beneficial for the behaviour of tissues. Finally, at the tissue level, there is another network: the cell–cell communication network
Indeed, and at the organism level, there is what we call the human social communication network. All three of these networks—the metabolic networks within a single cell (Jeong et al. 2000; Wuchty 2001; Yook et al. 2004); the cell-cell networks within the brain (Hilgetag et al. 2000; Sporns and Zwi 2004; Achard et al. 2006); and human social interactions (Yook et al. 2002; Ebel et al. 2002; Davidsen et al. 2002)—prominently feature Barabasi's small world, frequently scale-free, organization. Why is this? Each network represents the highest, most complex form of organization on its particular level. Its formation is critical to the emergence of a new, higher-level holon, beginning the process of socialization again. Clearly, certain general strategies are used reiteratively at multiple levels of evolution.
Achard S, Salvador, R, Whitcher, B, Suckling, J, Bullmore, E (2006) A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. J Neurosci 26: 63-72.
Davidsen J, Ebel, H, Bornholdt, S (2002) Emergence of a small world from local interactions: modeling acquaintance networks. Phys Rev E Stat Nonlin Soft Matter Phys 88: 128701.
Ebel H, Mielsch, LI, Bornholdt, S (2002) Scale-free topology of e-mail networks. Phys Rev E Stat Nonlin Soft Matter Phys 66 (3 Pt 2A): 035103.
Hilgetag CC, Burns, GAPC, O'Neill, MAO, Scannell, JW, Young, MP (2000) Anatomical connectivity defines the organization of clusters of cortical areas in the macaque monkey and the cat. Philos Trans R Soc Lond B Biol Sci 355: 91-110.
Jeong H, Tombor, B, Albert, R, Oltvai, ZN, Barabasi, AL (2000) The large-scale organization of metabolic networks. Nature 407: 651-654.
McShea DW (2005) The evolution of complexity without natural selection, a possible large-scale trend of the fourth kind. Paleobiology 31: 146-156.
Sporns O, Zwi, JD (2004) The small world of the cerebral cortex. Neuroinformatics 2: 145-162.
Wuchty S (2001) Scale-free behavior in protein domain networks. Mol. Biol. Evol. 18: 1694-1702.
Yook SH, Jeong, H, Barabasi, AL (2002) Modeling the Internet's large-scale topology. Proc Nat Acad Sci USA 99: 13382-113386.
Yook SH, Oltvai, ZN, Barabasi, AL (2004) Functional and topological characteristics of protein interaction networks. Proteonomics 4: 928-942.