CONCEPT
The Scaling Exponent
The single number that determines whether a system grows sublinearly toward death or superlinearly toward open-ended transformation — the slope of the line on a log-log plot, and the diagnostic instrument at the heart of West's framework.
The scaling exponent is the slope of the line that appears when a system's output is plotted against its size on logarithmic axes. An exponent of 1.0 means linear scaling — doubling the input doubles the output. An exponent below 1.0 means sublinear scaling — doubling the input produces less than doubling of output, and the system becomes more efficient per unit but accumulates the structural features that lead to stagnation and mortality. An exponent above 1.0 means superlinear scaling — doubling the input more than doubles the output, producing accelerating returns and open-ended growth. The difference between 0.85 and 1.15 is the difference between a system that ages toward death and one that accelerates toward transformation, and the exponent is determined not by technology or talent or strategy but by the topology of the network through which resources flow.
In The You On AI Field Guide
The mathematical precision of the exponent distinguishes West's framework