This map illustrates the evolution of scientific paradigms—from the linear, reductionist models of the past to the Complex Adaptive Systems of the 21st century.

While physics and biology moved into “Complexity Science” decades ago, current AI architecture is still largely relying on linear, probabilistic models. This creates an “Ontological Gap.” We are trying to use linear tools to solve non-linear human problems. This diagram shows why simply scaling compute won’t bridge that divide.