The constrained disorder principle and the law of increasing functional information: The elephant versus the Moeritherium

The laws of classical physics describe universal behavior in macroscopic systems. However, these laws cannot explain all readily observed natural phenomena. Numerous dynamic evolving systems exist in the natural world, so it seems odd that rules describing their behavior have not emerged. According to the constrained disorder principle (CDP), all systems exhibit varying degrees of variability, constrained by dynamic boundaries. These boundaries of variability are essential for proper response to perturbations, enabling adaptation to changing environments. According to a recent law known as the "law of increasing functional information" (LIFI), a system progresses if multiple configurable options are selected for various functions. These two laws share some similarities. However, their vital differences reveal some fundamental aspects of natural laws. This paper explores the differences between the CDP and the LIFI in their approach to system functionality. The LIFI examines the selection pressures that determine the advantageous configurations of systems over time. Like other laws of physics, the CDP does not personify natural systems or link subjective phenomena with functionality. Per the CDP, natural systems lack desires. LIFI is based on time trajectory, whereas CDP sees variability and system changes as fundamental properties of natural systems and, thus, time-independent. Each law proposes a method for improvement. CDPs enable system intervention by altering the degree of disorder. Second-generation artificial intelligence systems based on CDP effectively overcome human malfunctions, improving outcomes. Implementing these laws will be dissected in future studies to enhance the functionality of systems.