Both system characteristics and environmental
parameters can influence the transition from social norms to a total system
breakdown. Behavioral patterns evolve naturally over time, and changes within a
system often remain invisible until critical points are reached. The figure
below highlights the gap between a stable social standard and a state of
complete breakdown. Biological and Non-Biological Systems develop progressively
along a trajectory of expected performance standards. When operations adhere to
consistent parameters, the system exhibits stability and harmonic balance,
known as Mode 1 (M1).
In Biological Systems, unknown external
entities can disrupt this balance. System elements may override established
decision-making processes, deviating from the standard evolutionary path into
Mode 2 (M2). In this mode, invisible forces alter processes and disrupt the average
balance (Mode 3 or M3).
This disruption in M3 can lead to countless
side effects. Three potential outcomes of system adjustments are depicted in
figures M4-0, M4-1, and M4-2. Mode 4-0 involves increased parameter complexity
across multiple channels, while presumptive side effects (M4-1 and M4-2) are
often disregarded in the system’s default settings. Even a single side effect
can lead to the development of complex, interconnected structures, known as
Complexity Mapping Patterns (Mode 5 or M5).
These patterns of complexity hinder system
progress and trigger pathophysiological mechanisms that impair performance. A
severe system crash can occur, disabling restore functions (Mode 6 or M6). The system becomes vulnerable without functional recovery, and even critical
data storage may be lost. The system may become trapped in a cycle resembling
obsessive-compulsive behavior, where outputs are suppressed, but inputs remain
largely unaffected.
A Non-Biological System may begin collecting
override values across all layers via process inputs (Mode 7 or M7). However,
it struggles to integrate these values fully. In contrast, a Biological System
may enter a suspended state (Mode 8 or M8) and cannot reboot or restore itself
fully. The system remains stuck, and rational optimization efforts are unlikely
to produce a recovery key, rendering the system incapable of returning to a
stable state.
Observation:
Optimization always reverts the current mode setting to the
previous one. For instance, optimizing in Mode 7 shifts the system status back
to Mode 6. However, rational suboptimization struggles to change the system
status from Mode 8 to Mode 6. System developers must adopt a heightened
awareness of system status, particularly when the system is positioned between
discrepancy modes and total breakdown.
Observation:
Rational optimization involves a logical testing approach that
avoids involving other subcomponents and their set properties’ factors
beyond the life-cycle process.
