Prolegomena to Plan & Act on the Edge of Chaos

 

Philippe COUTURE, May 2019 – Read Time: 6’:30”

     The 20th century witnessed a triumph of science and technology, increasing human capacities by several order of magnitude.

    The 21st century unveils the hidden costs and fragility of this victory, in a perpetual global war against all limitations of Nature, waged at industrial scale. Now, resources depletion, destruction of ecosystems and climate emergency are reshaping conditions of survival for organized societies.

“We cannot solve our problems with the same thinking we used when we created them,” warned A. Einstein. Without radical new paradigms, we will not escape unscathed the turbulence announced by the increasingly dramatic IPCC’s reports.

    Pushing Growth and Competitiveness over everything else threaten not only humanity with terminal consequences. We might have to reexamine even more fundamental assumptions, such as quantifying and simplifying all problems to produce scaleable solutions with linear beneficial outputs, abstracting Principles of Causality from specific local initial conditions or expecting punctual efficiency to guarantee global well being. These are reductive assumptions that leave externalities out of the equations. And these externalities, outside of sanitized laboratories, seem inclined to spawn catastrophes of biblical proportions.

Henri Poincaré demonstrated, mathematically, that reality is not reducible to mathematical objects. The universe is not made of cogs and wheels, with impeccable chains of causality.

    100.000 years of technological progress have equipped us with extraordinary sophisticated and efficient machines. However we merely invented extraordinary Complicated Systems, Also known as industries.

In 3.7 billions of years, natural co-evolution designed intricate dynamic networks. It evol Complex Adaptive Systems, broadly identified as life.

    We know that Complicated Systems and Complex Adaptive Systems are different in essence:

  • No matter how sophisticated, Complicated Systems are predictable. They are conceived with limited scopes in space and time. They are never autonomous. They are economic, efficient and rational constructs. But if only one part fails they stop functioning altogether. Even if repairable by their designer, they remain in essence fragile systems. Still their short term predictability and benefits make them deceivingly reassuring.

  • Complex Self-Adaptive Systems encompass all living systems, from bacterial colonies to city sprawls, from macro-economies to forest ecosystems. They are auto-generated and self-organized. Their outputs are emergent and unpredictable by the agents that composed them. Their behaviors are dynamic and non-linear. They seem to be inextricably interdependent of sub and meta systems, which make them extremely resilient to punctual disruption. But because they are autonomous with a high degree of uncertainty, some would say “creativity”, they are unsettling, often frightening.
     

    Despite still being a loosely organized academic field, the study of Complex Systems has attracted researchers from all fields, from quantum physic to social science, from computer science to ecology. Though not yet a science by itself, Complexity Theory exhibits recurrent characteristics and enunciates definitions:

  • Complex Adaptive Systems are sets of interactive and interdependent entities, real or abstract, forming an integrated whole, that together are able to respond to environmental changes.

  • A Complex Adaptive System is a system in which a perfect understanding of its individual parts does not convey a perfect understanding of the whole system behavior.

  • Individual parts are most often themselves sub-adaptive systems.

  • Complex Adaptive Systems seem to intuitively evolve toward a regime near the boundary between chaos and order, between entropy and complex auto-organization called “neg-entropy”. This transition zone, spatial or temporal, is called the Edge of Chaos.
     

    Many disciplines are considering the Edge of Chaos as the next frontier, conceptually as well as physically. It makes perfect sense from urban planning to epidemiology, sociology, artificial intelligence, social media, biology and ecology, mathematics and physics.

The Edge of Chaos seems to be the place where organisms mutate to adapt, a space where creativity and risks are at the highest level.

 

    It is a space that exhibits perpetual novelty.

    Complex Adaptive Systems, in perpetual non-linear dynamics, are difficult, maybe impossible, to predict with accuracy. The Edge of Chaos might be the original ground for life to develop and evolve: the narrow space where information makes sense, new ideas elaborate, between noise and silent monotony, where diversity emerge.

    If Complexity Theory is to be the new paradigm for understanding reality, how do we plan, make decisions and act on the Edge of Chaos?

    Agriculture, husbandry and fisheries, organized as industries, despite dealing with living beings as raw material, became major causes of biosphere degradation. Soil destruction and erosion, water pollution, gas emission and biodiversity impoverishment (to name a few), are the collateral damage of these industries ostensibly meant to breed life and feed us. This damage is today of sufficient scope to provoke systemic failures on global scale.

In theory, market anticipations, multi-annual plans, global objectives and centralized rational regulations are driving these sectors.

In reality, they are subjected to weather disruption, ecological interactions, conflicting interests of stakeholders, price fluctuations etc, all being complex and unpredictable interconnected systems.

Still the human factor, equipped with its tremendous technological power, remains the driving force for potential disasters. Therefore, understanding the way it perceives reality, takes decisions and implements those decisions is essential. Yet it might be the most volatile and unpredictable agent.

    Socio-Ecosystems are Complex Systems, combining diverse communities interacting with their natural environments. Communities are themselves sub-Complex Systems constituted by other layers of complex agents, such as interest groups, professional guilds or families, which themselves are also composed of individuals, with divergent interests, sometime rationals but most often not. If we believe Spinoza, human’s “conatus” (what make them act) is essentially emotional, erstwhile “aspirational”, built on affects and passions, which are in turn produced by historical social interactions.

As a society, how do we then make optimal decisions with faulty decision makers?

     Dynamics of Complex Systems are results of all actions taken by each individual agent in the system. No one in the system has direct control over the agents. Not even autocrats. No agent has perfect and total understanding of reality. Not even expert polymaths. So when it comes to community betterment, searching for competent leadership in pyramidal power structures, might be just an enduring illusory quest.

Much research study has proven that group intelligence is significantly superior when it comes to perceiving reality and acting accordingly. Divergent perceptions and opinions complement each other and are necessary to get over subjectivity and “Bounded Rationality”. Effective perception of the environment is a social construct. It acts as a sensory system’s extension and diversification of groups as coherent entities.

Optimal communication among all stakeholders is crucial to solve problems. To optimize environmental adaptation, it is necessary to bring together agents from various backgrounds, with potentially conflicting goals. Without this, groups remain “cogito inerte”.

    It is a negotiation process, the pertinence of which should be gauged to environmental fluctuation and feedback. Resulting decisions must be proved by trial-and-error implementations, allowing permanent iterative adjustments. The process then tends to reveal groups or individuals with out-of-the-box successful solutions. They are mutation’s precursors, also called Positive Deviants.

How do we facilitate practical experimental spaces, conducive to the emergence of Positive Deviants?

Stakeholders occupy different positions in the hierarchy of the actual social order. Positional prerogatives tend to distort the legitimacy of more accurate judgments and paralyze the system to preserve the status quo.

    Positive Deviance is rarely permanently incarnated in a single group or person.

     How do we get over power struggles and particular interests?

It seems that 100,000 years of small group hunting-gathering did not prepare our prefrontal cortex to embrace the scope, complexity and impacts of the last 200 years exponential industrial development. The emergent industrial power has outgrown our individual biological capacity of comprehension. Now science and technology, catching up with complexity, might make their next most significant contribution by enabling human-machine hybrid decision-making.

    The first widely published modeling of global complex system by Jay Forrester, 40 years ago, was for “The Limits to Growth” report. It proved eerily accurate. Since then, other new algorithms have expanded and fine tuned complementary modeling approaches, from System Dynamics, to Bayesian Belief Network, to Fuzzy Cognitive Mapping and Agent Based Modeling.

    Computer Simulation of Complex Systems allows better understanding of apparently chaotic behavior. Computational power has never been so pervasively available across societal layers.

A growing range of Open Source software allows virtual simulation of complex issues and a safe exploration of alternative scenarios with different priorities. This process stimulates the building of complex mental models, for stakeholders to perceive many of the varied trade-offs involved in multi-party negotiations. It clarifies, objectifies and plays down respective positions.

Gamification and/or simplification of User Interfaces (UI) of these Open Source Modeling platform could be the next decisive step. It would permit to non-expert stakeholders transparent access to Participative Complex Modeling.

    A rapid decentralization of such platforms, coupled with data distribution, could generate new types of perception that would transform the way we understand and take decisions. In the same way the microscope or social media transformed the way we understand and interact, it could mitigate power dominance in the existing social structure, triggering the next level of social complexity. It could allow the necessary mutation of society by empowering its agents to engage in real open-heart discussions, enabling more cooperation and less competition.

 

    The viral democratization of personal computers, Internet access, interactive communication, remote sensing technology and Artificial Intelligence, opens up new perspectives for hope. Nonetheless, the concurrent rapid degradation of all sectors of our biosphere might invite us to regroup and concentrate efforts to apply these tools in the most sensitive sectors: water management, food security, community building and restoration of biodiversity.

Local Direct Participative Decision-Making coupled with Complex System Modeling seems a promising path, worth exploring, all the more so when applied in the field to fine tune solutions, bridging the resources and knowledge of global and local communities, listening, observing and combining, in search of Positive Deviance emergence. We must venture outside our comfort zone, welcome uncertainty and outgrow our fear of failure. We need to fail, fail again and fail better. That is how evolution happens. Small failures prevent massive ones, and there is an emergency imperative to do so.

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