NETWORK THEORY, “NOISE” AND AL QAIDA
Dr. Von commented on a post by John Robb that dealt with a network theory research paper by Alexander Franks on the evolution of rule-sets in noisy environments (i.e. environments with many competing distractions or a high level of disorder). John’s evaluation of the paper:
“This is an interesting topic since it is not at all obvious how open source networks develop cohesive rules sets — this in contrast to hierarchical systems that can propagate rules through central direction. In sum, his work suggests that one or two widely held rules (greater than 50% adoption) provide the basis for the evolution of an entire set. All rules that have affinity to those founding rules evolve until they are widely adopted. All minority rules that do not have much affinity are flushed. This has interesting applicability to open source warfare.
It suggests that the plausible promise (the idea that starts the open source warfare community) provides a center of gravity that attracts rules that advance it and repels those that don’t. Any additional work on this topic is welcome. “
Von has expanded on this beginning and brought up several noteworthy observations:
“What research has shown, though, is that in a perfect, noise-free environment, the majority rule will fail to reach global consensus, even if there is some amount of longer-range crosslinks within the network (meaning that some small number of individual agents not only see some number of nearest neighbors, but an occasional link to another agent outside the local boundary defined in the initial conditions). However, the boundaries between local pockets of differing viewpoints does breakdown when noise is introduced into the environment. This is, of course, a better simulation of what the real world is like anyhow. Noise, in the context of simulation work, means that there can be miscommunication between neighbors. This allows for incorrect information to be passed along and will influence agents to switch their state.”
The greater the systemic disorder of the environment the more likely the distortion within a network attempting to forge a consensus on rule-sets. Dr. Von offers some practical caveats for policy makers who must deal with non-state, decentralized, opponents like al Qaida:
“Lesson 1: Network formation takes time. Time can be an enemy or an ally, depending on circumstances.
Lesson 2: In social networks, law and order and security reduce environmental noise. If you do not maintain low noise levels, the local boundaries between those in the network who agree with you and those who disagree with you break down.”
“The key is that the noise in the main network as well as the loose ties to other networks has broken down boundaries and allowed widespread consensus to be reached, leading to an insurgency that apparently has surprised most military personnel and war planners. It is time that traditional war games, planning and training need to move on and research into areas like network theory must become much more prominent. Perhaps the results coming out of network and organizational theory research would have changed some minds and resulted in a more prepared occupancy of Iraq.”
The point here by Von has widespread implications for policy makers and military planners.
First, we see that slow devolution toward state failure or a catastrophic system perturbation attack creates an environment favorable to the emergence of entirely new organizations and what Dr. Barnett calls a “ rule-set reset“. However, while the shock of a perturbation preps the system for a rule-set reset by overcoming the system’s level of resiliency, Iraq would appear to demonstrate that the window of opportunity to control this process in the moment where system’s adherents would be accepting of change is extremely brief. Given any lag time between the perturbation and the introduction of new, systemically enforced rule-sets , the system will naturally begins to evolve its own solutions in an open-source manner. Once that genie is out of the bottle, the system will have competing rule-sets engaged in a Darwinian struggle for supremacy.
Secondly, on the smaller scale, understanding the formation of rule-sets by networks will make the behavior of decentralized, scale-free networked actors more predictable and subject to influence. To avoid that kind of evolutionary ” shaping” by state enemies, network leaders will have to retreat to older, more hierarchical forms of organization that we understand, can track and can counter very well, thus losing some critical advantages.