Sensing risk, fearing uncertainty: systems science approach to change.

Front Comput Neurosci

Foundation for Systems Research and Education New York, NY, USA.

Published: April 2014

Background: Medicine devotes its primary focus to understanding change, from cells to network relationships; observations of non-linearity are inescapable. Recent events provide extraordinary examples of major non-linear surprises within the societal system: human genome-from anticipated 100,000+ genes to only 20,000+; junk DNA-initially ignored but now proven to control genetic processes; economic reversals-bursting of bubbles in technology, housing, finance; foreign wars; relentless rise in obesity, neurodegenerative diseases. There are two attributes of systems science that are especially relevant to this research: One-it offers a method for creating a structural context with a guiding path to pragmatic knowledge; and, two-it gives pre-eminence to sensory input capable to register, evaluate, and react to change.

Materials/methods: Public domain records of change, during the last 50 years, have been studied in the context of systems science, the dynamic systems model, and various cycles.

Results/conclusions: Change is dynamic, ever-present, never isolated, and of variable impact; it reflects innumerable relationships among contextual systems; change can be perceived as risk or uncertainty depending upon how the assessment is made; risk is quantifiable by sensory input and generates a degree of rational optimism; uncertainty is not quantifiable and evokes fear; trust is key to sharing risk; the measurable financial credit can be a proxy for societal trust; expanding credit dilutes trust; when a credit bubble bursts, so will trust; absence of trust paralyzes systems' relationships leading to disorganized complexity which prevents value creation and heightens the probability of random events; disappearance of value, accompanied by chaos, threatens all systems. From personal health to economic sustainability and collective rationality, most examined components of the societal system were found not to be optimized and trust was not in evidence.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3978314PMC
http://dx.doi.org/10.3389/fncom.2014.00030DOI Listing

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