A Meta-layer for Restoring Democracy and Open Society: Part One, Conceptual
March 27, 2012 - 1:00am ET
It's hardly news that there’s a very wide chasm between voters, lawmakers and political parties. The rage in America reflected in the Republican primary contests is palpable. And there's also rage among progressives as well, though it's not finding an outlet in the Democratic Party. The same is true in Europe, where we see unrest in many nations. People in developing nations are demanding democracy, and making some progress too. But, everywhere one looks in developed countries, democracy is retreating, and Michels's (p. 400) “Iron Law of Oligarchy” is triumphant.
In the U.S. most Americans believe lawmakers don't care what they think, Congress's approval rating is at an all-time low, and most Americans believe the major parties won't represent them. Neither tries to match its policies to a majority of voters’ preferences, and both continuously support laws that seem designed to benefit large corporate interests and the 1%, but not working Americans. There are now more unaffiliated voters than party-affiliated ones, and major party candidates often win elections with only 25% of potential voters.
Most voters want most federal incumbents defeated, but legal constraints on minor parties and candidates typically ensure their defeat, whether they are “insurgents” from within the party, or candidates from third parties. This skewing of electoral outcomes leads voters to think that they have to vote for major party candidates, or “waste” their vote. Angry voters alternate election cycles between major party candidates to “punish” incumbents. But the new “winners” ignore what voters want, just as the old ones did. So, how can we repair this disconnect? How can we make office holders accountable and representative again?
Complex Adaptive Systems: Features and Significance
A mechanistic world view is unlikely to work in reforming our political systems, because they're not clockworks, “orange” or otherwise. We need models for transformation using perspectives of complexity theory, focused on the significance of co-intelligence and deliberative democracy in tackling legislative problems.
In working with complexity theory, it's common to try to define “Complex Adaptive System” (CAS). But, I think it's better just to list their features. The first of these is coherence in the face of change, or “identity.” Coherence refers to maintenance of the characteristic pattern of organization of a CAS.
Second, CASs are diverse in both form and capability. They range from adaptive software agents to the International Social System, and include one-celled living systems, immune systems, and many others of diverse form, varying capability and degrees of complexity.
Third, CASs are populated with agents (members) who learn, individually and collectively. Fourth, distributed problem-solving and knowledge processing is an important feature of CASs. Individual agents in CASs solve their own problems. In doing so, they contribute to solving CAS problems in a distributed, but organized way.
Fifth, CASs are marked by extensive interactions among their agents. Intermittent interactions are not sufficient to establish a CAS pattern with its complex patterning of feedback loops and reinforcements that maintains the CAS at “the edge of chaos.”
Sixth, CAS agents self-organize to produce emergent global behavior at the CAS level. This is one of the most important features of a CAS. The key idea is that agents comprising it act in accordance with their own purposes and motives, in pursuit of their own goals, and that their actions produce self-organized emergent global patterns that identify the CAS.
Seventh, CASs behave and learn partly in accordance with knowledge which can be modeled as ‘rules.’ Eighth, they also adapt by creating and using new rules as they continuously attempt to fit themselves to their environments. The process of arriving at new rules is “creative” or “evolutionary” learning. It involves “blind” generation of rules and recombination of components of old, well-established rules. Once new rules are formulated, they are subject to selection through interaction among CAS agents and interaction of the CAS with its environment.
Ninth, the ability of CASs to successfully learn and develop new rules, or knowledge, is greater to the extent that their constituent agents are operating in problem-solving and distributed knowledge processing environments marked by relative “openness.” “Openness” must apply across various phases of the problem-solving process. It has at least two important dimensions. The first is internal transparency (availability and accessibility of information across CAS agents); the second is epistemic inclusiveness, equal opportunity for all autonomous CAS agents to participate and interact in the problem-solving and distributed knowledge processing of the system, so that it can be more effective. Both are always found in high-performance CASs. An example taken from outside the human domain helps illustrate a pattern of (uncontaminated) epistemic inclusiveness.
Ant colonies illustrate ‘native’ CASs that rely on distributed knowledge processing informed by the individual experiences of their members, and global behaviors at the CAS level determined as a consequence of information flow among these members. There is no centralized planning or control producing collective behavior in such systems. All knowledge created by individual ants contributes to the pattern of collective knowledge reflected in changed behavioral predispositions of the ant colony, and in the pattern of pheramone trails emerging at the level of the collective. Knowledge at the global level is entirely distributed or “bottom-up” in origin, as is the learning that produces it.
Social CASs created by humans are unlike ant colonies. Agents in human CASs distinguish, to a much greater degree than ants do, power, authority, or influence relations, and concentrations of such relations, and of the resources that are at the basis of them. These are an emergent reality affecting human CAS interaction. The existence of such relations is an important factor distinguishing social CASs comprised of human agents, and their interactions, from other types of CASs.
Human CASs, are subject to human attempts to change the patterns of interaction and outcomes that their CASs are predisposed to produce. In fact, politics, management, and leadership is frequently about attempting to treat organizations as though they were, or ought to behave like, mechanical systems, subject to determinate cause-and-effect relations, rather than as CASs whose adaptive global behavior results from self-organization and distributed knowledge processing.
Such attempts produce continual conflict between predispositions produced by interacting agents within self-organizing processes, and other predispositions produced by efforts of the powerful and influential to realize their own visions of the future through command-and-control interventions. So, human CASs constitute a type we will call Promethean CASs (PCASs), because, their normal predispositions toward behavior and distributed knowledge processing are subject to the “god-like” intervention of powerful and influential agents. That's why Michels's “Iron Law of Oligarchy” is often predictive of politics in political parties and democracies.
PCASs, the Movement Toward Oligarchy, and Open Society
The movement toward oligarchy in human-based systems happens because powerful people and institutions don't like continuous self-organization, and the appearance of new ideas, ideologies, and power structures that come along with it. So, they intervene to stop or regulate it, and, in doing so, destroy the essence of democracy; the ability of people to always organize anew and disturb and even displace the policies, power structures, elites, and institutions of the past with new ones, more adaptive in solving the problems of the present and future.
The task of any CAS system is to maintain itself at “the edge of chaos.” This is difficult enough in the face of environmental influences that tend to transition PCASs either to chaotic dynamics, or to closed systems inexorably driven toward a sterile mechanical equilibrium. It is even more difficult in the context of continuing political or management interventions that frequently may amplify the strength of tendencies toward one extreme or another by changing the internal environment affecting self-organization. management, leadership, and politics.
In the context of Open Enterprises and Open Societies, the task is about implementing policies and programs that will support self-organization in distributed knowledge processing and problem-solving by maintaining openness in problem recognition, developing alternative solutions, and error elimination, as well as openness in communicating and diffusing new solutions across the enterprise or across society. Conversely leadership, management, and politics in such systems that undermines self-organization by repressing or otherwise manipulating it, will transition human PCASs away from openness and democracy, and towards extreme conflict systems, or authoritarian or totalitarian oligarchies.
So, for democratic societies today, an important question hangs in the balance: How can we counter tendencies toward oligarchy in our democracies by restoring self-organization and distributed knowledge processing to their proper place in reinforcing open society, democracy, and adaptiveness to environmental and societal change?
Many are looking to e-participation innovations in democracy to provide an answer to this question. But if e-participation is to serve that purpose, rather than the purpose of elite astro-turfing manufacturing consent within a totalitarian oligarchy, then e-participation platforms must fulfill certain requirements. We'll turn to those in the second part of this series.
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