1.3. Need for a paradigm shift
1.3.1. The shift from simple thinking to complex thinking
We live according to the principles of disjunction, reduction and abstraction of Cartesian mechanistic logic. The supremacy of a cognition fragmented and divided into disciplines frequently gets in the way of our ability to connect the parts to the whole and so understand complex everyday phenomena, blinkering our view of the long-term consequences of our actions. The Cartesian view of the world as a machine (Figure 3a) is no longer compatible with our mental learning models. The enormous changes being produced from day to day on a planetary scale require modern models of thought in order to interpret the world as a whole, as a living being (Figure 3b). Complex thinking, based on non-linearity, organicity and multidimensionality, offers the most contemporary focus as an alternative to Cartesian mechanistic thought.
Complex or systemic thinking in fact enables us to understand events incorrectly termed financial or banking crises for what they really are: systemic crises that must be resolved at the structural rather than the symptomatic level. The application of this complex thinking to our lives, and to the economy, is leaving behind the old ways of understanding systems and beginning to understand them as complex systems. It is leaving behind the fragmented view and unsustainability (Figure 4a), and evolving toward the holistic view and full sustainability (Figures 4b and 4c).
One of the most important changes to occur in scientific thought in recent decades has been recognizing and understanding that the nature of complex phenomena is not linear, nor is it predictable, mechanical, Cartesian or fragmentable. The intrinsic interconnection between economic, social, cultural and ecological processes makes them remarkably non-linear and significantly uncertain.
Complex systems are systems whose components are interdependent in such a way that no one component can be isolated or modified independently of the others. A complex system is characterized by a dense network of interdependencies and energy flows between its elements, which can be diverse in nature. A system is considered more complex in relation to the number of relationships and feedback mechanisms existing among its elements.
Decades of study of natural ecosystems have led to a mathematical understanding of how a network structure affects the long-term viability of an ecosystem, according to the system’s “efficiency” or ability to process information, quantities of material and energy flows, and its “resilience” or ability to recover after disturbances. These studies demonstrate that nature does not act in order to achieve maximum efficiency, but rather to find the optimum point of balance between efficiency and resilience. The curve of sustainability with its emergent properties presents a certain asymmetry, showing that resilience is twice as important as efficiency to achieve the optimal point (Figure 5). Notwithstanding, all ecosystems present conditions which are still sustainable within a narrow, specific range, known as the window of viability.
