From the archive, originally posted by: [ spectre ]…

3 Americans win Nobel in economics

The award is for their studies of how markets work when buyers and
sellers have incomplete information.

By Maura Reynolds  /  October 16, 2007

WASHINGTON — Three American scholars who study how markets work when
buyers and sellers have incomplete information were awarded the Nobel
prize in economics Monday. Among the winners was a 90-year-old retired
professor from the University of Minnesota who is the oldest person in
the history of the prize to become a laureate.

“I really didn’t expect it,” Leonid Hurwicz told reporters who
gathered at his Minneapolis home after the announcement. “There were
times when other people said I was on the short list, but as time
passed and nothing happened, I didn’t expect the recognition would
come because people who were familiar with my work were slowly dying

Hurwicz was honored along with Eric S. Maskin, 56, of the Institute
for Advanced Study in Princeton, N.J., and Roger B. Myerson, 56, of
the University of Chicago. The three will share the $1.56-million

The Royal Swedish Academy of Sciences praised the three scholars for
laying the foundations of a theory that has led to “major
breakthroughs in many areas of economics, including regulation theory,
corporate finance, the theory of taxation and voting procedures.”

They analyzed ways to organize markets and other economic mechanisms
so they function optimally even when buyers and sellers have access to
different information. Their work has been applied to a wide variety
of situations, including cap-and-trade systems for reducing carbon
pollution and auctions of bandwidth for television and mobile phones.

Traditional economics is based on assumptions that don’t exist in the
real world. One such assumption is that all actors in the marketplace
have the same information. In the 1960s, Hurwicz began to grapple with
the problem of how markets function — or fail — when buyers and
sellers don’t know the same things.

His co-winners said that in 1972 Hurwicz wrote a seminal paper that
described the importance of creating incentives for people to divulge
private information that would make economic outcomes more efficient.

“People of my generation — we pounced on this. Hurwicz had opened
something up,” Myerson said at a news conference.

“He changed the course of my life,” Maskin said in an interview.

What Hurwicz pioneered and Maskin and Myerson helped build was a
branch of game theory known as “mechanism design”: how to structure
systems, including markets, so they include incentives for the kind of
information sharing that maximizes outcomes. Those outcomes could
include economic goals, such as efficiency, or social goals such as
reducing pollution.

Real-world applications of mechanism design theory include deductibles
to prevent overuse of insurance.

Hurwicz, a naturalized American, was born in Moscow a few months
before the Bolshevik Revolution in 1917 to a Polish family, who
returned to Poland in 1919. Hurwicz earned a law degree from Warsaw
University in 1938, but his interest in economics had been sparked by
a course in the subject.

After graduation, he was accepted at the London School of Economics.
He was in Switzerland in 1939 when Adolf Hitler invaded Poland, and
while his family was interned in Soviet labor camps, Hurwicz emigrated
to the United States. He completed his studies at the University of
Chicago and Harvard.

Maskin, originally from New York, and Myerson, a native of Boston,
both received doctorates in applied mathematics from Harvard
University in 1976.

The economics prize is the only one of the Nobel prizes that was not
created by Swedish industrialist Alfred Nobel. It was established in
1968 and is formally known as the Sveriges Riksbank Prize in Economic
Sciences in Memory of Alfred Nobel.

Regents Professor Emeritus Leo Hurwicz received his LL.M. from Warsaw
University – Poland in 1938. He teaches in the areas of theory,
welfare economics, public economics, mechanisms and institutions, and
mathematical economics. Professor Hurwicz’s current research includes
comparison and analysis of systems and techniques of economic
organization, welfare economics, game-theoretic implementation of
social choice goals, and modeling economic institutions.,,2191731,00.html

What is mechanism design theory?
Richard Adams  /  October 15, 2007

The gap in knowledge between buyers and sellers, and the costs and
consequences for the efficient operation of a market, is at the heart
of the groundbreaking research by the winners of this year’s Nobel
prize in economics.

Three US-based economists – the game theory pioneer Leo Hurwicz, along
with Eric Maskin and Roger Myerson – were today awarded the 2007 prize
for work spanning 50 years in a branch of game theory that has come to
be known as mechanism design.

In its statement announcing the award, the Nobel committee said: “The
theory allows us to distinguish situations in which markets work well
from those in which they do not. It has helped economists identify
efficient trading mechanisms, regulation schemes and voting

While highly abstract and mathematical, mechanism design theory has
concrete applications in the real world. It can provide important
justifications for government intervention in the operation of markets
such as health care, as well as helping to construct rules that
attempt to avoid the disparity in information between groups of buyers
and sellers.

That gap in knowledge is known in economics as “information asymmetry”
and it has become one of the most widely studied aspects of the

In recent years economists such as George Akerlof and Joseph Stiglitz
have been awarded Nobel prizes for their work in the field.

Because sellers have an incentive to seek the highest possible sale
price, and buyers have the opposite incentive, and both parties have
different levels of knowledge about the overall value of the
transaction, the final outcome may not efficient for the economy as a
whole. Mechanism design theory attempts to identify these breakdowns
and avoid them where possible.

The influence of mechanism design theory can be seen in the structure
of auctions, such as the UK government’s sale of 3G mobile phone
licenses in 2000, which netted the exchequer more than £22bn in
revenue. That was thanks to an innovative procedure designed to
squeeze potential buyers into making bids that reflected what they saw
as the true worth of the licences, and prevented them colluding to pay
lower prices.

Prof Hurwicz began working on forms of game theory with the
influential economist Kenneth Arrow, who first outlined the pitfalls
of information asymmetry in the 1960s and was awarded the Nobel prize
in economics in 1972. But Arrow’s work built on some of Hurwicz’s
research in the 1950s, and Hurwicz was regarded as having been
overlooked, until now.

Myerson is a prolific author of academic papers and computer software
tackling the subject. He is best known as one of the authors of an
influential principle in mechanism design theory, the Myerson-
Satterthwaite theorem, which finds that one side of a transaction
stands to make a loss of some kind when two parties trade a good where
they each have hidden and differing information.

Maskin has worked on the optimal design of auctions, alongside his
colleague John Riley, and was hired to advise the Italian government
on the operation of its bond auctions. He has previously worked as a
research student and visiting fellow at Cambridge University.

The Road to a System that Works (Without Shooting People)
David Warsh   /  October 21, 2007

So “mechanism design” has entered the language of everyday economics,
as described by newspapers. It is a truism that most Nobel Prizes are
won by researchers who tumble onto their topics in their twenties and
often have all but nailed them down by their late thirties. Thus, even
before they left Harvard University, where they had been
undergraduates and graduate students in the 1970s, Eric Maskin, of the
Institute for Advanced Study, in Princeton, and Roger Myerson, of the
University of Chicago, were firmly on the trail of the ideas that led
to their recognition last week, “implementation theory” and “the
revelation principle.” Both men are 56.

How is it that Leonid Hurwicz, of the University of Minnesota, shares
the spotlight with two economists more than thirty years younger?  At
90, Hurwicz is the oldest person ever to be recognized by the Swedes,
in any discipline. There has to be a story in that.

The modern theory of mechanism design, as presented today in
microeconomics texts, is a hard-edged and high-tech topic, especially
auction theory — a body of knowledge that informs the sale of radio-
spectrum licenses and timber-harvest rights; structures cap-and-trade
emissions schemes and incentive systems designed to lead expert
panelists to tell the truth; and which determines the price of
advertising on Google and the mechanics of transactions on eBay.  The
theory is not complete, of course; far from it. Even the best-
understood mechanisms, auctions, are no more than a metaphor for more
general forms of competition.

But in fact the roots of our understanding of economic mechanisms
trace back to a topic intensely debated by European intellectuals in
the years immediately after World War I — could a planned economy,
such as that of Germany during the war, succeed?  Could patriotic
bureaucrats, operating without the benefit of markets, prices and
money, be depended on to make better decisions than self-interested

With the socialist nature of the Russian economy under the new Soviet
Union in the 1920s, the topic became more interesting still. And then
the Great Depression brought the possibility of planning to the fore
in the West, especially in Great Britain. Friedrich von Hayek, in
1935, edited a collection of essays by Continental writers, including
the one by Austrian economist Ludwig von Mises that had most
forcefully broached the issue, all designed to introduce English
readers to the controversy: Collectivist Economic Planning: Critical
Studies in the Possibility of Socialism.

By then, the argument had acquired a name (“the socialist calculation
debate”); various champions (Oscar Lange, Abba Lerner); a good deal of
interest in mathematical and quantitative planning techniques under
development elsewhere; and, finally, in 1945, a concise statement of
the argument against planning (and against formal methods) by Hayek,
in “The Use of Knowledge in Society:”

The economic problem of society is not merely a problem of how to
allocate “given” resources…. It is rather a problem of how to secure
the best use of resources known to any of the members of society, for
ends whose relative importance only those individuals know. [I]t is a
problem of the utilization of knowledge not given to anyone in its
totality. This character of the fundamental problem has, I am afraid,
been rather obscured than illuminated by many of the recent
refinements in economic theory, particularly by many of the uses made
of mathematics.

Leonid Hurwicz’s entry onto the scene came that same year, when he was
28.  He had been born in Moscow in 1917, two months before the
Bolshevik Revolution. His parents returned to their native Poland, by
horse cart, in 1919. “It was something you could make a Doctor Zhivago
movie about,” he told the economics writer Douglas Clement last year
for his article, “Intelligent Designer.” He studied law, graduating
from Warsaw University in 1938, then studied for a year with Nicholas
Kaldor at the London School of Economics.  He was in Geneva when
Hitler invaded Poland. Paul Samuelson, who had just left Harvard for
the Massachusetts Institute of Technology, hired him for a year.  The
next year Hurwicz moved to the University of Chicago to teach
meteorology (mathematically gifted, he was a quick study). There he
quickly fell in with the Cowles Commission, which was then engaged in
seeking to build the first calculable models of the US economy. And in
1945 the editor of The American Economic Review asked him to review a
book by a pair of central European expatriates, John von Neumann and
Oskar Morgenstern.

Hurwicz gave Theory of Games and Economic Behavior a rave.

Had it merely called to our attention the existence and exact nature
of certain fundamental gaps in economic theory, the [work] by von
Neumann and Morgenstern would have been a book of outstanding
importance. But it does more than that.  It is essentially
constructive:  where existing theory is considered to be inadequate,
the authors put in its place a highly novel analytical apparatus
designed to cope with the problem. It would be doing the authors an
injustice to say that theirs is a contribution to economics only. The
scope of the book is much broader. The techniques applied by the
authors in tackling economic problems are of sufficient generality to
be valid in political science, sociology, or even military strategy.

For the problem the von Neumann and Morgenstern addressed was
absolutely fundamental, wrote Hurwicz. It wouldn’t be easy to define
“rational economic behavior” on the part of any one person “when that
very rationality depended on the probable behavior of others.”

A century after the essence of problem had been identified (by
Augustin Cournot, writing in French), the necessity of strategic
behavior at last had become an inescapable part of economics (in

For the next five years, Hurwicz experimented with game theory, linear
programming, the concept of strategic equilibrium that had just been
introduced by John Nash, and all the other exciting ideas that were in
the air. He spent a summer in Santa Monica, California, at the free-
wheeling Air Force think-tank known as Rand Corp., and met Kenneth
Arrow. They began one of the most remarkable research collaborations
in all of economics. And then, in 1950, he found his problem. Since no
one over the years has drawn out Hurwicz more successfully than George
Feiwell, Retired Alumni Distinguished Service Professor of the
University of Tennessee, I will rely here on Feiwel’s work in Arrow
and the Ascent of Modern Economic Theory to let Hurwicz do the

My work in thus area started around 1950 when I was still with the
Cowles Commission. I was writing a more or less expository paper
dealing with activity analysis…and happened to use the term
“decentralization,” which was then often applied to the market
mechanism as a sort of a selling point. But when I used the word
“decentralization” I thought I should explain what I meant. So I made
a footnote mark, went to the bottom of the page, and began writing,
“By decentralization we mean…” But then it struck me that I did not
know what we meant by decentralization. That was the beginning of many
years of work trying to clarify the concept, because I thought that if
we think this property is so important, we should be able to define
what it is.

Already the diaspora of math-econ types from Chicago had begun.
Hurwicz was hired by Walter Heller at the University of Minnesota,
and, with his wife, settled down to a quiet life of research in
Minneapolis. The move was, in effect, one-for-one trade: Milton
Friedman had left Minnesota for Chicago four years before. Chicago
became a center of one sort of economics; Minnesota of quite another.

Hurwicz’s first notable effort came about the time he turned 40, in
the form of a game in which participants send messages to each other
and/or to a “message center,” and where a pre-specified rule assigned
an allocation outcome to each set of messages received. “Optimality
and Resource Efficiency in Resource Allocation Processes” was finally
published, in 1960.

My interest had been in a broad class of situations,  broader than the
advanced industrial market economies, including situations in third
world countries, and in countries attempting to have some kind of
socialist approach to their problems.  I have been interested in how
one can construct efficient mechanisms that have the decentralization
features similar to a market but that do not necessarily resemble a
market. For this purpose, I formulated the notion of an
informationally-decentralized economy in which perfect competition was
just a very special case….

To carry out such an analysis, you have to have a very general notion
of what you mean by decentralization, because you cannot just point to
the market system and say, well, that is decentralized. (That is as if
someone were to ask you what is a mammal?, and you would point to a
dog and say, a dog is a mammal. This, of course, does not help answer
the question of whether an elephant is a mammal or not.) You must
provide a general description of what would qualify as decentralized.
If you don’t have a rigorous answer to that question, how can you know
whether it is possible to decentralize in a given situation?

Having defined mechanisms in terms of information flow and decision-
making authority, Hurwicz had achieved a generality more satisfying to
him and others than vague talk of “central planning” or “competition.”
He was able to move on to thinking systematically about the rules
under which individual strategies would be pursued. One of these he
called “the greed process.”

The basic idea of the greed process is that whatever the other side
offers you take as a minimum and then you ask for more. Its origin was
an old Polish Jewish anecdote about a young man who went to buy a
suit. But he had never bought anything before. So his father told him,
“Whatever they ask, always offer half.”  So when he was asked, let us
say, 100 zloty, he said 50 zloty. When the tailor went down to 80
zloty, he retorted 40 zloty. At the end, the tailor is really
disgusted, wants to get rid of him, and tells him he can have the suit
for free. The young man then retorts, “Can I have two pair of pants?”
The “greed process” is somewhat similar in spirit.

The emphasis on models of information-processing lasted until the late

But then I noticed that whenever I was asked to present some of my
work, I would start by saying, “Of course the incentive problem is
very important, but I will assume that people are angels and whatever
you tell them to do, they will do.” Thus I was ignoring the incentive
aspect and instead asking the following question, “Could we give the
decision makers (say managers) the kind of instructions that, if
followed, would make the economy run well?” But at some point I
decided that since I know people are not angels, perhaps I should not
completely ignore the incentive aspect.

At that stage I tried to see how one could formalize the incentive
issue. Initially I was thinking of it in rather informal terms,
somewhat along these lines:  Let us say a country has some economic
problem, for instance its balance of payments is in bad shape, as in
pre-war Poland. What would it do?  It might, say, introduce exchange
controls (you must not export money, and so on). But what happens
then? People figure out ways of exporting money: one has an uncle in
London, others over-invoice or under-invoice… all the usual tricks.
You could of course put them in jail or shoot them. But that is a
distinct failure of economics, isn’t it? Because what economists
should be able to do is to figure out a system that works without
shooting people.

Thus did Hurwicz arrive at the idea for which he won the Nobel Prize
last week, the concept of  “incentive compatability,” in a paper
circulated widely for several years and finally published in 1972,
when Hurwicz was 55.  He framed the argument in terms of a famous 1954
paper by Paul Samuelson on the nature of public goods, in which
Samuelson stated that no decentralized system will work for their
production (“Of course as soon as I see the word ‘decentralized,’ I am
aroused, especially when such a strong negative assertion is made”);
but clearly he was thinking of his native Poland as well:

What I meant by this was a system of rules designed in such a way that
people would have an incentive to obey these rules. If the system is
incentive-compatible, you do not have to threaten criminal punishment
to get compliance. But this does not necessarily mean just maximizing
profits.  So the question is, “Could one design (a combination of
taxes, subsidies, trading rules and whatnot) that would work as one
would want it to work (that is, to achieve its goals) even without
coercion or compulsion?”

The old debate about “socialist calculation” had yielded a new way of
thinking, at once highly general and extremely detailed, about how
incentives might be aligned in systems of all sorts, capitalist,
socialist, military, religious, whatever. The effect on young
researchers just entering the field in the late ’60s and early ’70s.
was electric. “Hurwicz gave us the definitions, and we went to work,”
says Jerry Green, of the Harvard Business School, co-author of a
leading microeconomics text.  As Hurwicz’ co-laureate Roger Myerson
wrote last year, it had become clear within a decade that incentive
constraints in the “social coordination problem” could be sorted into
two basic varieties:  there were information constraints, that made
formal the various “adverse selection” processes that cropped up when
people sought decentralized information; and there were strategic
constraints, the formal version of various problems of “moral hazard”
of controlling behavior that had been noticed and dealt with on a case-
by-case basis over the years.

So much, then, for how it is that Leo Hurwicz became the oldest person
ever to be awarded the Nobel Prize, and shared the honor with two men
who, when he started working on what would become their problem, had
not yet been born. He, too, started when he was a young man; he kept
working until he got the set-up that he wanted. Indeed, he is still
working.  “But Who Will Guard the Guardians?,” a meditation on the
ancient problem of trust and verification, was on the agenda when
economists gathered in Minneapolis last April to celebrate his 90th
birthday. He is one of those thinkers, like Arrow and Samuelson, who
worked at a consistently high level over many decades.

We will come back to mechanism design in December, when the prizes are
actually awarded to Hurwicz, Maskin and  Myerson in Stockholm. The
Royal Swedish Academy of Sciences, which only in 1969 began awarding a
prize in economics (technically the “Bank of Sweden Prize in Economic
Sciences in Memory of Alfred Nobel”), is still studying a dwindling
backlog of significant work done in the ’50s by economists who are
alive, leading their friends to joke that the Swedes engage in an
annual game of “Beat the Reaper.” A painful case in point came in
1996, when 82-year-old William Vickrey shared the prize with 60-year-
old James Mirrlees (for work in the engineering of mechanisms that
anticipated the deepening interest in the principles of their design).
Vickey was so pleased that, a few days after the announcement, he
jumped in his car to drive overnight to a meeting — and died of a
heart attack on the way. Potential laureates also sometimes die
young:  Jean-Jacques Laffont, who was a sure-fire eventual winner (and
the man chosen in 1996 to lecture in Vickrey’s place), succumbed to
cancer at 57 in 2004.

The outcome this year is highly satisfactory: Swedes 1, Reaper 0.


The roots of mechanism design in the socialist calculation debate were
nicely laid out last week by Peter Boettke, of George Mason
University, in an op-ed page feature in The Wall Street Journal, and
in much more detail by Roger Meyerson in a lecture last year at the
North American meetings of the Econometric Society. Still the best
source on the formalization of economics is Philip Mirowksi’s Machine
Dreams: Economics Becomes a Cyborg Science — a saucy, scholarly,
brilliant, and ultimately thoroughly wigged-out narrative of events.
E. Roy Weintraub’s How Economics Became a Mathematical Science offers
a calmer, less salacious version of the story.  Bruce Caldwell’s
intellectual biography of Hayek is indispensable for understanding the
Austrian’s contributions to the debate. You may have to go to a
library to find George Feiwel’s remarkable 1987 contribution, Arrow
and the Ascent of Modern Economic Theory, but it might be worth it.
Useful, too, are these two magazines devoted to Minnesota economics.

Subscribe to Economic Principals and receive the weekly e-mail version
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To reach the editor, e-mail warsh [at] economicprincipals [dot] com [dot]


Impressive and fun, June 21, 2006
By A. J. Sutter (Tokyo, Japan)

As you can see from the previous reviews, this is a book that provokes
strong feelings. As usual that’s often more a reflection on the reader
than on the book. You’d never guess that this book is (by intention)
very funny. But it is.

Mirowski has written elsewhere that John von Neumann is the “hero” of
this book. Von Neumann thought neoclassical economics was nonsense,
and made no secret of that opinion. As a result, many post-war
American economists have tried to write him out of history. One fruit
of their effort was the beatification of John Nash as the patron saint
of game theory, a process that began in the 1980s.

According to this book, the irony is that those same economists have
“followed the trajectory” of von Neumann’s thinking for the last five
decades, even if they wouldn’t acknowledge it. Through the 1970s or so
they relied on fixed-point theorems and other nonconstructive proof
techniques (von Neumann in the 1930s). From the 1980s to now, they
have relied on game theory (von Neumann for a few years in the 1940s).
Recently, they have begun to rely more on computers, particularly to
study “agent”-type automata (von Neumann from the mid-1940s to the end
of his life). And, as for von Neumann, military funding has been an
important factor throughout this development.

Actually, this isn’t “the” irony, but just one of many. If you’ve ever
had any suspicions that neoclassical economics was kind of a crock,
you’ll find them well-supported in this impressively well-researched
book. (Some highlights include the misplaced aspiration to axiomatize
economic theory, the impossibility of computing Nash equilibria, ditto
for Walrasian general equilibria, the socialist antecedents of “free
market” jingoism, the bounded usefulness of V. Smith’s market
experiments, and much else.) It may be a bit of a stretch to say that
the book reads like a thriller, but the fun of uncovering some
additional bit of intellectual dishonesty with each turn of the page
did keep my attention.

For over 500 pages, this story is told with a sustained, righteous and
gleeful sarcasm. Such a tone may sound tiresome, but based on the
evidence Mirowski brings forward – much of it the neoclassicals’ own
words – it struck me as quite justifiable. And I laughed a lot.

However, be aware that this book is less self-contained than
Mirowski’s earlier book, “More Heat Than Light”. Even if you’ve read
that book first (which I recommend, especially if you’re not an
economist), you should have at least a Scientific American-level of
acquaintance with theory of computation, a bit more math-intensive
experience with game theory (like a few chapters of Myerson — not
that “Machine Dreams” has any equations, but the math is often alluded
to), and smidgens of Arrow, Debreu, Herb Simon, Vern Smith and
Kahneman & Tversky. You should also know “who” Bourbaki is and have
some experience of the Bourbakist style, because it’s taken for
granted that you already do.

There are a few quirks, but nothing so dire as what other reviewers
have mentioned. For example, the “Newtonian” issue appears maybe in
one offhand comment. More frequent, no less irritating, and just as
utterly inconsequential is the use of the word “thermodynamics” when
“statistical mechanics” would have been more appropriate. (None of
those physics gaffes is important to the main theme.) An august group
of manuscript readers allowed the author repeatedly to use “phenomena”
and “automata” as singular nouns in the first two-thirds of the book.
And throughout, there are ironic allusions and silly puns based on pop
culture references, which is fine; but those of you born after 1965
may miss a lot of them.

Maybe one day, some econ undergrad as yet unborn will write a senior
honors thesis glossing those many dozens of goofy remarks. For its
multitude of remarks both insightful and trenchant, this book deserves
to continue to be read at least until that time.

A weak case, April 18, 2004
By Lee Carlson (Saint Louis, Missouri USA)

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
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.

Note added later, December 30, 2002
By Professor Joseph L. McCauley “Joseph L. McCauley” (Austria+Texas)

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.

Undecidable econ vs. Perfect Rationality, June 18, 2002
By Professor Joseph L. McCauley “Joseph L. McCauley” (Austria+Texas)

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.


Machine dreaming: an environmental perspective
by James Juniper

International Journal of Environment, Workplace and Employment
(IJEWE), Vol. 1, No. 2, 2005

Abstract: Mirowski’s Machine Dreaming provides an invaluable critical
history of the post-war development of economic theory under the
influence of military-funded Cold War research into the cybernetic
sciences. However, this reviewer argues that in restricting the scope
of his historical analysis to the influence of the natural sciences
over the development of economic thought, Mirowski has neglected a
variety of traditions within cybernetics and systems theory that draw
on the philosophy of language. Moreover, the paper traces the
influence these neglected traditions have exerted over various strands
of economic analysis. Finally, these strands of economic theory are
interrogated to identify various ways they have influenced the
development of richer and more comprehensive notions of environmental

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