The most manifest characteristic of human beings is their diversity. The freer an economy is, the more this human diversity of knowledge will be manifested. By contrast, political power originates in top-down processes—governments, monopolies, regulators, elite institutions, all attempting to quell human diversity and impose order. Thus power always seeks centralization.

Capitalism is not chiefly an incentive system but an information system. We continue with the recognition, explained by the most powerful science of the epoch, that information itself is best defined as surprise: by what we cannot predict rather than by what we can. The key to economic growth is not acquisition of things by the pursuit of monetary rewards but the expansion of wealth through learning and discovery. The economy grows not by manipulating greed and fear through bribes and punishments but by accumulating surprising knowledge through the conduct of the falsifiable experiments of free enterprises. Crucial to this learning process is the possibility of failure and bankruptcy. In this model, wealth is defined as knowledge, and growth is defined as learning.

Because the system is based more on ideas than on incentives, it is not a process changeable only over generations of Sisysphean effort. An economy is a noosphere (a mind-based system) and it can revive as fast as minds and policies can change.

That new economics—the information theory of capitalism—is already at work in disguise. Concealed behind an elaborate mathematical apparatus, sequestered by its creators in what is called information technology, the new theory drives the most powerful machines and networks of the era. Information theory treats human creations or communications as transmissions through a channel, whether a wire or the world, in the face of the power of noise, and gauges the outcomes by their news or surprise, defined as “entropy” and consummated as knowledge. Now it is ready to come out into the open and to transform economics as it has already transformed the world economy itself.

All information is surprise; only surprise qualifies as information. This is the fundamental axiom of information theory. Information is the change between what we knew before the transmission and what we know after it.

Let us imagine the lineaments of an economics of disorder, disequilibrium, and surprise that could explain and measure the contributions of entrepreneurs. Such an economics would begin with the Smithian mold of order and equilibrium. Smith himself spoke of property rights, free trade, sound currency, and modest taxation as crucial elements of an environment for prosperity. Smith was right: An arena of disorder, disequilibrium, chaos, and noise would drown the feats of creation that engender growth. The ultimate physical entropy envisaged as the heat death of the universe, in its total disorder, affords no room for invention or surprise. But entrepreneurial disorder is not chaos or mere noise. Entrepreneurial disorder is some combination of order and upheaval that might be termed “informative disorder.”

Shannon defined information in terms of digital bits and measured it by the concept of information entropy: unexpected or surprising bits... Shannon’s entropy is governed by a logarithmic equation nearly identical to the thermodynamic equation of Rudolf Clausius that describes physical entropy. But the parallels between the two entropies conceal several pitfalls that have ensnared many. Physical entropy is maximized when all the molecules in a physical system are at an equal temperature (and thus cannot yield any more energy). Shannon entropy is maximized when all the bits in a message are equally improbable (and thus cannot be further compressed without loss of
information). These two identical equations point to a deeper affinity that MIT physicist Seth Lloyd identifies as the foundation of all material reality—at the beginning was the entropic bit.
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The accomplishment of Information Theory was to create a rigorous mathematical discipline for the definition and measurement of the information in the message sent down the channel. Shannon entropy or surprisal defines and quantifies the information in a message. In close similarity with physical entropy, information entropy is always a positive number measured by minus the base two logarithm of its probability. Information in Shannon’s scheme is quantified in terms of a probability because Shannon interpreted the message as a selection or choice from a limited alphabet. Entropy is thus a measure of freedom of choice. In the simplest case of maximum entropy of equally probable elements, the uncertainty is merely the inverse of the number of elements or symbols.
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Linking innovation, surprise, and profit, learning and growth, Shannon entropy stands at the heart of the economics of information theory. Signaling the arrival of an invention or disruptive innovation is first its surprisal, then its yield beyond the interest rate—its profit, a further form of Shannon entropy. As a new item is absorbed by the market, however, its entropy declines until its margins converge with prevailing risk adjusted interest rates. The entrepreneur must move on to new surprises. The economics of entropy depict the process by which the entrepreneur translates his idea into a practical form from the realms of imaginative creation. In those visionary realms, entropy is essentially infinite and unconstrained, and thus irrelevant to economic models. But to make the imagined practical, the entrepreneur must make specific choices among existing resources and strategic possibilities. Entropy here signifies his freedom of choice.

As Shannon understood, the creation process itself escapes every logical and mathematical system. It springs not from secure knowledge but from falsifiable tests of commercial hypotheses. It is not an expression of past knowledge but of the fertility of consciousness, will, discipline, imagination, and art.