18/07/2016 by Elena Goryunova
What is Reality? Looking at the World Through a Complexity Lens
“Reality is merely an illusion, albeit a very persistent one.”
Our vision of reality determines who we are, our life’s goals, principles and morals. It is our internal guiding system that helps us to navigate through the challenges and uncertainties of human existence. If our mental map of reality is inadequate or incomplete, then we are unlikely to achieve our individual and collective goals (e.g., prosperity and sustainability).
Some prominent economists believe that “the economic crisis is a crisis for economic theory” (1) and “bad or over-simplistic and overconfident economics helped create the crisis” (2). This signifies that the global problems and crises we face today as a society are the signals of the misfit or informational gap between our collective representation of the world and the ultimate nature of reality. We need a new understanding of the universe, a more accurate knowledge of ourselves and living phenomena to become more successful and sustainable in our collective endeavors.
This new worldview has recently emerged thanks to the accumulation of knowledge in many scientific disciplines and significant progress in research technologies. A new science of complexity has brought to light a powerful, all-encompassing picture of the world that has potential to revisit our taken-for-granted assumptions (cultural beliefs) about the nature of reality and causality.
Here I present some key features of this emergent complexity vision of reality:
Nested hierarchic architecture
The essential feature of complexity worldview is that our reality can be represented as a hierarchical multi-level structure where relatively simple components (i.e., biomolecules, neurons, individuals, species) self-organize into more complex systems (cells, brains, social groups and organizations, ecosystems) with more powerful capabilities for learning, adaptation and survival.
These complex systems (e.g., cells, brains, organizations, societies) can be represented as networks of heterogeneous, simultaneously interacting agents (biomolecules, brain cells, individuals, etc.) that can be considered as complex systems themselves—“at any level of analysis, order is an emergent property of individual interactions at a lower level of aggregation”(3). Because each complex system constitutes a “building block” for a higher-order system, which is more complex than its constituent parts, “most complex structures found in the world are enormously redundant, and we can use this redundancy to simplify their description, and even to “see” such systems and their parts” (4).
Interactions as the building blocks of nature
At each level of analysis, complex patterns of macroscopic behavior emerge as the product of simultaneous microscopic interactions. Extensive interactions within the system and between the system and its larger environment are the key for understanding the emergence and persistence of complex higher-order phenomena.
For example, an in-depth exploration of physical matter revealed that there is no such thing as “hard matter” but only strong interactions that hold subatomic particles together, which are in turn composed of even smaller elementary particles binded together with a much greater force or interactions. In the realm of biological systems, a living cell is the product of non-linear interactions among biomolecules where more than 3000 reactions are organized in a way “that between them each reaction—inputs and constraints—is supported by the outputs of others” (5). An even more impressive amount of interactions can be found at the level of human brain, which is made up of over 200 billion neurons connected to one another via hundreds of trillions of synapses.
These interactions in complex systems operate simultaneously where “all elements compute their next activities at the same time”, thus explaining the emergence of qualitatively different higher-order properties (e.g., living cell, consciousness) that cannot be deduced from the properties of individual parts (biomolecules, neurons).
Information as the common currency of the universe
Interactions can be seen as continuous exchanges of energy or information (information = energy) between a system/agent and its larger environment. For example, physical non-living matter is capable of capturing and using information (e.g., light energy) from the environment, under the right conditions, to self-organize into more complex living configurations (6). Biological systems (cells, organisms) harvest energy stored in the chemical bonds of food to power their ongoing life processes (7).
Cognitive systems (brains) are able to process a vast amount of information, to compress hidden regularities (e.g., grammar, rhythm, rules, etc.) into a kind of schemata or heuristics and then to act, make a choice, interpret new information on the basis of newly acquired “processing rules” without even noticing that something new has been learned (8). Business systems capture hidden patterns of information (trends) in consumer preferences, technology and/or society’s needs to fuel their product or service development processes and thus assure their business survival. Societies accumulate a vast amount of cultural information and lessons from their history to transmit them to new generations in order to structure their behavior in a way that make a society possible (9).
Therefore, information structures and governs the behavior of complex systems, supplies them with energy or resources to thrive and evolve in an open-ended, ever-changing world.
Language (laws) specific to each complex system
Each complex system is built on a different kind of information or uses its own language. For example, we use mathematical equations to describe and predict the behavior of physical matter; chemical formulas of reactions and equations to explain the behavior of biochemical molecules; a genotype and gut microbiota might be useful to understand the development and changes in biological organisms; verbal and non-verbal information compressed into mental schemata underlies cognitive activities; organizational routines or culture govern the behavior of business systems; cultural values embedded in social institutions, traditions and laws might explain the complex behavior of social systems (nations and civilizations).
Figure 2. Hierarchy of complex systems and their languages
It should be noted that a language (laws) of a higher-order system, while encompasses the laws of a low-level system, contains its own regularities that should be studied “in addition to the laws of the former. At each level there are laws to be discovered, important to their own right”(10). In other words, we cannot use the language of mathematics or biology to understand and explain the behavior of more complex social systems. By reducing the complexity of higher-order social systems to the language of low-level systems, we not only distort our vision of reality (for example, economic indicators such as GDP cannot account for important social outcomes while the cultural value of equality provides a much more accurate prediction) but, most importantly, we create a breeding ground for human far-reaching disasters.
As one cancer researcher explains, “Nazism is nothing more than “applied biology.” The Nazis used the language of genetics and inheritance to launch, justify and sustain their political agenda of “genetic cleansing” and racial extermination (11). Similarly, the current system of financial capitalism in nothing more than “applied mathematics” where public and business policies are built on the assumption of limitless economic growth and profit-maximization while completely ignoring non-measurable or difficult to express mathematically aspects of reality such as beauty of nature, biodiversity or human well-being.
To understand how information propagates through a system and affects its overall behavior, it is important to keep in mind various time scales for different types of interactions in complex systems. In general, speed of change in complex systems depends on the extent of coupling in a system; that is “intra-component linkages are generally stronger than intercomponent linkages” (12). To put it simply, changes at the lower level of agents’ interaction are more rapid than at the higher level.
For example, time required for firing of neurons is “extremely small on the order of tens of milliseconds” (13) so new information may instantly affect the structure or patterns of neuronal connectivity in human brain. However, brain-to-brain interactions generally take much more time and changes in social or business organizations requires from months to years to occur (14). At the level of nations, important changes are triggered over span of years and decades, while the rise and fall of civilizations may last from centuries to millenniums of cultural interaction (15).
Spiral or circular causality
The global pattern of system behavior is “the result of a dynamical causal loop” or interplay between microscopic non-linear interactions and macroscopic properties of the whole system where “the slower, more extended processes [at the macro-level] set conditions and constraints for faster, less extended processes [at the micro-level], while products of these latter accumulate to alter the slower, more extended processes” (16).
For example, technological progress is the accumulated product of microscopic human learning and adaptation that eventually impacts the macro-level context for human interactions through the widespread use of new technologies. Similarly, economic crisis is the result of “a long-term endogenous build up, with exogenous events acting merely as triggers” (17). The only difference between the two social processes is that while technological progress often leads to positive outcomes for social systems (e.g., more efficient use of resources, new jobs, etc.), economic crisis has a deleterious impact on business or economic systems (e.g., liquidity crisis, unemployment) and deteriorates overall social performance. This difference can be explained by the values that underlie human decisions and behaviors (see four states of collective behavior).
From the perspective of complexity science, our reality is essentially composed of hierarchically organized complex systems (physical, biological, cognitive, social, ecological, etc.) that maintain their complex patterns of collective behavior thanks to different kinds of interactions— from infinitely strong or rapid interactions at the level of subatomic particles to extremely weak or extended in space and time interactions at the level of ecosystems and even celestial bodies. These interactions represent continuous flows of information. If we decipher the language or regularities that these complex systems use in their interactions or information exchange, then we can understand the complex patterns of their collective behavior and rules that underlie their long-term performance.
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