Life After Google: A Slow Fall from Grace
Responding to my information theory of economics, some critics wonder, where is the beef? Or even the bun?
I say wealth is knowledge — thoughts. They say it is money or “capital” — things.
I say growth is learning — through the testing of ideas; they say growth is the accumulation of things.
I say money is time as a measuring stick. They say money is a sovereign tool of government, a commodity providing a medium of exchange and store of value.
My version spiels a lot of fine fruity words and concepts, they say, but it fails to yield provably predictive models or rigorous mathematics.
In response, I contend that only information theory can address the complexities of a modern economy driven by technology.
In recent prophecies I have written of the biotech breakthroughs of Matthew Scholz of Immusoft, Oisin, and OncoSenX. I have discussed Compugen, Evogene, and other companies launched by entrepreneur Martin Gerstel. I also told the story of Kary Mullis, the late inventor of the polymerase chain reaction (PCR) machines at Cetus Corporation. PCR is now widely used to test for COVID.
These pioneers are essentially computer scientists or engineers with a learned grasp of the information theory that unites and explains biotech, computers, and networks. As Mullis explained, “I knew computer programming and from that I understood the power of a reiterative mathematical procedure” (such as recursion).
All these companies are committed to a regime that they call computational biology. They are unified by their roots in the information theory of biology that identifies DNA patterns as codes directly analogous to software codes in computers and networks.
Since these are the dominant disciplines of contemporary technology, the theory of information that unites and explains them is a driving force in every modern economy. I believe that it unites and explains all systems of economics as well.
A Lesson from Claude Shannon
In 1938, Claude Shannon formulated the information theory behind the computer in “A Symbolic Analysis of Relay and Switching Circuits.” This pioneering paper demonstrated that these circuits could perform Boolean algebra by processing binary code consisting of “bits” and “bytes.”
Shannon went on in 1948 to explain the laws of networks in his “Mathematical Theory of Communications,” which developed ideas of information theory he pioneered during World War II, when he wrote a paper, immediately classified, on the theory of cryptography.
A kind of inverted information theory using codes initially to hide rather than to transmit information, cryptography is now providing the foundation for the Cryptocosm of the blockchain and cryptocurrencies. These technologies address the two key crises of our economy: the hacking of the internet by bezzles and spies, and the hacking of world monies by central banks.
Shannon always believed that his concepts also applied to the coded DNA system in biology and wrote a paper estimating the information in the genetic code called an “Algebra for Theoretical Genetics.” If information theory can explain biology, it can also illuminate the economic exchanges that sustain the lives of biological beings.
In my view, the failure of economists to grasp the importance of these theories for their own profession has been crippling both to its scientific validity and to the survival of free economic institutions.
By treating capitalism not as an information system but as an incentive system, driven by rewards and punishments, the prevailing economics provides no simple way to answer the socialist charges that capitalism feeds on greed. These theories of “capitalism” originated in Karl Marx’s Das Capital in 1857. In current forms, the incentive model fosters the absurd idea that entrepreneurs need to make billions to motivate or reward themselves.
Seeking to replicate the determinism of Newtonian physics, economists have eclipsed the creativity of entrepreneurs, which as Albert Hirschman of Princeton told us “always comes as a surprise to us.” Banishing surprise from economic models, economists banished creativity as well.
Surprise, however, is central to Shannon’s information theory. It defines information as entropy, which measures surprisal. It is also directly linked to liberty: surprisal depends on the degrees of freedom of the creator of the message. As knowledge grows through learning, Shannon’s measure of unexpected bits can capture economic advance through freedom.
Far from failing to provide mathematical models, Shannon’s theory is fraught with mathematics at every point and enables calculation of the information bearing capabilities of specific computers and networks and the information content of computational data or life.
The complaint against the lack of a deterministic mathematical model repeats the same claim that conventional economists have always mounted against the Austrian school, from Ludwig von Mises and Friedrich Hayek to Joseph Schumpeter and Mark Skousen.
In a real sense, ironically denied by many current day “Austrians,” who tend to reduce their school to a set of narrow doctrines about business cycles, information theory entered economics through Hayek’s canonical essay “The Use of Knowledge in Society.” Published in the American Economic Review in September 1945, it ignited a conflagration of insights that won at least two Nobel Prizes.
In Knowledge and Decisions, published in 1971, Thomas Sowell expounded the argument that wealth is essentially knowledge, not material resources, thoughts not things. He wrote, as I recall vividly today: “The Neanderthal in his cave had access to all the material resources we have today. The difference between our age and the stone age is entirely the accumulation of knowledge.”
Many economists have written about knowledge and learning curves in economics and business. But they have not seen the applicability of the now fully established science of information and communications to economics.
In questioning the utility of my efforts, and the kindred insights of the Austrian school, they offer the contrast of predictive Keynesian mathematical models. The question, however, is not whether a theory can exactly predict the future. No economic theory can do that. The question is whether it is right and useful for analyzing economic phenomena and guiding economic policy.
Now, building on the more partial insights of William Nordhaus and others, Gale Pooley and Marian Tupy have introduced time-prices as a radical new and simpler way to measure all economic activity. Their fascinating and revolutionary book will be out later this year. It obviates all the consumer price indices, GDP deflators, purchasing power parities, and other contentious devices that established economists use to compare prices and values across time and space.
It asserts that true prices are measured in hours and minutes — the time you have to spend working to buy anything.
The information theory marches on to new pinnacles of usefulness and authority. From learning curves to new gauges of value, it is giving all investors a new panoply of tools to enhance their powers. This prophecy could not do without it.
Editor, Gilder’s Daily Prophecy