Open System Characteristics

Open system frameworks are essential to the evolution of life because they allow for the flow of energy and information between the system and its environment. Closed systems wither and die.

Open systems are dynamic and constantly changing, but can never reach equilibrium because of the inherent unpredictability and uncertainty of their environments, which in turn are open systems and because all systems undergo unpredictable, random fluctuations in accordance with quantum theory. This uncertainty continues to create an information differential, which the system must monitor and attempt to minimise by the acquisition of additional information and processing capacity, including learning, computational and structural modification. The further an open system is from equilibrium within its environment the more pressure it will be under to adapt and evolve to a new state of greater complexity.

A recent discovery in biology reveals that even bacteria engage in monitoring their environment and adapt directly to uncertainty through the process of ‘bet hedging’. This allows an organism to shift to a new configuration of its cellular networks and protein expression through nucleotide mutation and editing. This results in greater complexity of form, function and survivability because the new information selected is based on its potential capacity of the bacterium to create a larger and more efficient solution space.

The cybernetic law of requisite variety also requires that systems acquire sufficient information to match the information capacity of their environment. Therefore in order to survive a system must be coupled to its environment and that environment in turn is nested within a larger system in the manner of ‘Russian Dolls’. But as each system seeks to adapt and transform, it also triggers changes within its immediate environment, which ripple out to wider systems and environments. And so the process continues, with entropy increasing in the wider universe, but at the same time creating more information and greater complexity for life. This extends the life of each living system and therefore of life as a whole. Although life appears doomed in a particular universe when insufficient energy is available to generate the requisite information to negate entropy, according to the eminent physicist Frank Tipler, by processing an infinite amount of information in subjective time, life may extend its survival indefinitely.

All open systems are therefore connected with and exert influence on their external environments through boundary and network enmeshments. These networks are the equivalent of Loop Quantum Gravity spacetime networks at the Planck level. LQG networks encode their links as volumes and areas of space allowing information to pass from observer to observer, each with a partial view of reality. The network encodes processes by which information is conveyed from one part of the universe to another. But it is important to note that although LQG networks are modelled independently of any preferred set of spacetime coordinates, this level of abstraction can be extended further through decision networks. The information channels and decision nodes of the D-Net model are completely independent of any notion of physical space. Information is selected by the evolutionary network on the basis of its information value to the system in terms of its relationship to other systems.