Machine Dreams Economics Becomes a Cyborg Science

Rating:
Summary: Undecidable econ vs. Perfect Rationality
Review: I've read about 250 pages and can recommend that anyone with an interest in economics and finance should read this fantastic book. The basis for the text are the contributions of Shannon, Turing, von Neumann, Wiener, Koopmans, Marshak, and Arrow. Mirowski tells us the main story of the interaction of the Cowles Commission with RAND, which Bernstein does not at all hint at in his Capital Ideas. Having praised the book, I will now concentrate mainly on a few points of disagreement. Undecidability should not be confused with noise in stochastic processes. Systems at the transition to chaos can define automata that can perform simple arithmetic. That 'cyborg' has it's origin in the physical sciences seems farfetched (the connection between Turing and physics is supposed to be via Maxwell's demon, but was Turing really motivated by the idea of Maxwell's demon?). Nonlinear dynamics and fractals ('chaos' and fractals) certainly did not evolve from cybernetics or 'system theory' ('system theory' was based at best on an awareness of equilibria and limit cycles of differential equations, and made vague, unjustifiable allusions to holism). Cybernetics cannot really be seen as the midwife of what is now loosely called 'complexity' either, rather, that (still undefined) field grew out of nonlinear dynamics, neural networks, computability theory and molecular biology. Mirowski is right that many scientists confuse simulations with experiment and observations. I have argued against this confusion in papers and books.

Mirowski paints an intriguing picture of (Gödel-influenced) von Neumann, RAND, researchers with awareness of information and computability limitations leading to agent-based modelling with some respect for empiricism on the one hand, and then, on the other hand, Arrow, the Cowles Commission and their later rejection of empirics, instead with emphasis on Bourbaki-style existence proofs leading to infinte demands on information requirements on Walrasian agents and noncomputable equilibria. We now know that agent-based modelling can easily lead to fat-tailed price distributions (as observed empirically), whereas in contrast the origin of the systematic head-in the-sand philosophy of the neo-classical economic theorists is made quite clear in this work. One can summarize the neo-clasical economic agent as follows: his dynamics are trivial (equilibrium, including Nash equilibria) but the information demands made on him to interact with other agents and locate an equilibrium point are impossible (noncomputable). Moreover, we now know that financial market statistics point toward the instability of Adam Smith's hand, so that the notion of dynamic equilibrium is complelety uninteresting so far as understanding markets is concerned.

Rating:
Summary: A weak case
Review: Recognizing apprehension about current developments in technology and the "closed worlds" of the "brave new world of electronic surveillance and control centers", and the presence of anti-cheerleader/antagonists towards artificial intelligence and its supposed tendency to reduce the complexity of humanity to "a very small part", the author of this book attempts to step beyond this and give an historical overview of the influence of what might be called (and these are words of this reviewer), a "cyborg epistemology" in the field of economics. The evidence cited is on the whole anecdotal, and what results is a view of economics that could more properly be called "deterministic". If economics is to be labeled "cyborg science", then this labeling might have many different meanings depending on the attitudes and background of the reader. For this reviewer, the decision to read this book was based on the belief that it might shed some light on how intelligent machines are being used either to develop new economic theories or to understand the vast amounts of empirical economic data currently available.
Luckily though the author does not intend to give the reader another neo-Luddite treatise on the perils of technology. He lets the reader know early on in the book that this is not his intent, in spite of the first few pages of the book, which might lead a reader to think otherwise. The author describes "cyborg science" as a description, taken by historians and sociologists of science, of the manner in which science has been transformed as an institution since World War II. According to the author, this designation is due to Donna Haraway, a contemporary sociologist of science, and applied by many other researchers whom he lists. In order to be fair to the author's use of the term as delineated by these researchers, one would need to study their works. This reviewer has not read any of these, but concentrated instead on the arguments put forward by the author himself, independent of any prior analysis or works of others he depends on. And it is the opinion of this reviewer that although the author might have respected the goals and opinions of all of these researchers in their concept of "cyborg science", it does not conform to the concept of "cyborg" as viewed (in general) in artificial intelligence. The concept of cyborg as an "automaton" is one that the author had in mind, but thinking of machines as automatons takes place in only a few small circles in the field of artificial intelligence. Further, the "attack of the cyborgs", which labels one section of the book, is a theme of many Hollywood movies, but it is an exaggerated and even comical view of artificial intelligence, and does not deserve inclusion in any serious study of the history of the influence of artificial intelligence on economic theory.
The author begins his "cyborg genealogy" with Charles Babbage and quickly moves on to von Neumann, Claude Shannon and Norbert Wiener, Alan Turing, the main instigators (consciously or not) to the "cyborg science" of post-war economics. Throughout the book one can see clearly how the field of operations research was influenced by these individuals, and how ideas from physics, in particular from thermodynamics and statistical physics, found their way into economics. Babbage is described as someone who saw no reason why the human mental faculties could not be "economized" with the assistance of machinery. His portent of the future is certainly remarkable, given the trend in the last decade of low-level machine intelligence replacing hundreds of tasks typically done by humans. The "Second Industrial Revolution" spoken of by Norbert Wiener, and currently advertised with gusto by the new technophilic generation of inventor/visionary Ray Kurzweil, is fully in place, and shows every indication of having extreme social consequences.
One must not however exaggerate the influence of well-known individuals in science and technology in bringing out true changes in society. The ideas of these individuals are widely quoted, but their efficacy is usually tested by many unknown individuals, whose sole interest is in the applicability and marketability of these ideas. The author spends too much time elaborating on the contributions of a small collection of people, ignoring those who were (causally) responsible for the rise of the information age and machine intelligence. In addition, the anecdotal comments attributed to Babbage, von Neumann, Shannon, Turing, and Weiner, that the author believes proves their view of economics as a "cyborg science" does not mean it has actually become one. The author does not propose any criteria, independent of these anecdotes, for establishing his case that post-war economic theory should be characterized as such. These criteria would have to involve the use of statistical sampling and tests, which is completely absent in this book. A much stronger, and more interesting case could be made if the author did not shy away from these techniques.
So no, this book is not one of the reactionary anti-technology polemics that are beginning to proliferate the bookstores. But it is clear when reading the book that the author is expressing anxiety about the current state of technology and he makes a deliberate attempt in the last pages of the book to engage in philosophical value judgments. The "raw emotions" he says he felt in the development of his ideas compel him to make moral commentary on the state of economic theory. He does not see sinister plots behind military funding of economics, but he does hold the researchers obtaining this funding accountable for their results, and we should not believe them when they say they were working independently and without outside interference or pressure. The author though does show some traces of the post-hermeneutic criticism that has in large measure dominated the humanities. His worries of viewing markets as machines are in the opinion of this reviewer unjustified if one is to go solely by the content of the book.
The (thinking) machines of today are making markets, but not controlling them.

Rating:
Summary: Note added later
Review: The suggestion made in the last chapter is to try to identify an automaton that describes a particular market. This program will not work because of lack of uniqueness, as is explained by the work on generating partitions in nonlinear dynamics. Given any sttistical distribution, one can find infinitely-many different automata that can be programmed to generate that distribution. Mirowski's suggestion cannot be carried out in any meaningful sense for that reason. In finance theory we have recently (with Gunaratne) deduced a particular stochastic dynamics from market histograms, and there we also have faced nonuniqueness in identifying the underlying dynamics. The bigger and more immediate problem is to find nonfinancial economic data that are accurate enough to draw any meaningful conclusion from the purely empirical histograms.

Now for the irritation. I find it academically irresponsible in this day and age to equate Newtonian mechanics with 'equilibrium'. From the beginning, Newtonian mechanics was about periodic and quasiperiodic orbits. The orbits that were studied prior to 1900 typically have neutral equilibria. To be 'in equilibrium' in such a case, the earth (for example) would have to sit at the center of the sun. Poincare' discovered chaos in Hamiltonian systems around 1900. In a chaotic system all equilibria are unstable but the orbits are bounded. See Ivars Peterson's 'Newton's Clock' for a description of the history of the discovery of chaos in the solar system. Toffoli and Fredkin discovered Turing machine-level complexity in a Newtonian system (constructed of billiard balls) around 1983, and Chris Moore (now at the Santa Fe Institite) showed around 1993 that certain area preserving maps are equivalent to Turing machines. In other words, Newtonian systems can exhibit not merely chaos but maximum complexity as well. The misidentification of Newtonian mechanics with 'equilibrium' or simple mechanics should now be laid to rest once and for all. It would be more accurate to say that the economists borrowed the idea of static equilibrium from Archimedes. Also, take note please that every digital computer is a Newtonian electromechanical system.