A New York Times article reports on avatars in World of Warcraft finding love, which they then consummate through their players, who are real people. As one of my French friends says, it is a turvy topsy world. It reminds me of a Star Trek episode where two ethereal and compatico aliens made up of pure intelligence decide to inhabit the bodies of the Star Trek crew in order to experience the physical world. It doesn't work out well. The humans start to die, so, being of moral character, the aliens retreat into their disembodied state, but first have one last fling in order to consummate their love (with a kiss – it was 1960's television).

We, like WoW's Avatars and Star Trek's Sargon and Thalassa, are straddling the virtual and the physical. The trend is moving toward the former, but most of us still remain in the camp of preferring the latter. But if we do take the leap to living more in a set of virtual worlds, what is the problem with that? One reason, that I will discuss in this post, is that the virtual world is one of limited depth and created with compete intentionality and rationality, and thus strips away much of what makes us 'real'. This might be so obvious that it is not worth writing about. Obvious now, but I do not think it is only in science fictions and thought experiments that we will find games and virtual reality that blur the line beyond our ability to perceive the physical from the virtual.

We are Living in a Materialist World
What is a person?” If I knew the answer to that, I might be able to program an artificial person in a computer. But I can’t. Being a person is not a pat formula, but a quest, a mystery, a leap of faith. – Jaron Lanier

Materialism is a thread of philosophy that views man as inhabiting a deterministic world driven only by the laws of nature. Given that our virtual worlds are driven by a set of (virtual rather than physical) laws laid down by their decidedly finite creators, are completely understandable and solvable, devoid of the spiritual and mystical which the materialist denies, the virtual worlds pose a materialism of a new sort. Consider the Turing Test, which I discussed in a previous post. If we end up being successful in developing a machine that can fool people into thinking it is a person, that can use algorithms to successfully feign personal experience and emotion, then we have gone far towards proving this materialist case.

Indeed, success with the Turing Test is a prerequisite for replacing the physical with the virtual, because people still want human interaction, or the appearance of such interaction, when they occupy their virtual worlds. So creating your own made-to-order world also will mean populating it with made-to-order people, friends created based on the sort of information used now in social networks and dating sites; great friends based on your background, the books you read, music you listen to, sites you visit, perhaps personality tests and the types of e-mail you write. Friends that are then updated and refined based on who you are clicking with. You end up in a virtual world that you prefer to any real world you could find, you end up with apparent humans that are more interesting and tuned into you than any real humans would be.

The virtual worlds we create and occasionally inhabit are materialist because in the virtual world everything comes with a purpose, everything – even randomness – has to be created by rational, conscious action. Everything is constructed with a defined cause and effect. As Lanier writes in You are Not a Gadget:


The virtual at once seems to be covering everything but at the same time seems to leave everything of substance out.

The Virtual, Worlds Gone Mad
You cannot call up any wilder vision than a city in which men ask themselves if they have any selves...
You cannot fancy a more skeptical world than that in which men doubt if there is a world. – G.K. Chesterson

Materialism was the rage in early 20^th century England, and the Catholic apologist G. K. Chesterson wrote Orthodoxy as a charge against its dogma. In Orthodoxy, Chesterson likens the world of the materialist to that of a madman. The real world, the world of the sane, is filled with mystery, with infinite depth that cannot be plumbed. In contrast, the world of the madman is limited in scale, rational in its construction, and self-contained. We can say of the virtual what Chesterson says of the materialist:


The complete intentionality of the virtual world, like that of the real world in the eyes of the materialist, can give the impression of humanity, but it is the humanity inhabited by the madman who can not see anything without it having set about with a cause. Chesterson wrote that, “The madman is not the man who has lost his reason. The madman is the man who has lost everything except his reason”.

The virtual world has nothing but reason; it is rational and consistent, because it is developed through the rules of logic and mathematics. Virtual materialism takes materialism to an extreme: In the virtual world there is not even a place for the material. It is a world where one has no self, a world in which there is no world.

Jeremy Grantham put out a great quarterly letter about the scarcity of commodities and the marked rise of commodity prices, calling this “the mother of all paradigm shifts”.

Two interesting points in his letter are:

1. China consumes between 25% and 50% of many important commodities.
2. Prices for nearly all commodities are two or more standard deviations above their long-term mean; four standard deviations for iron ore, coal, copper and silver.

The recent drop in commodity prices notwithstanding, this and other analysis lay down the groundwork for his concern about the end of falling commodity prices. No one can deny that, absent one hundred per cent recycling, non-renewable resources extracted from a finite world will finally run out. And, furthermore, that we are using these resources more now than we have in the past, and given the growth of China and other countries, there are major sources of consumption that were a rounding error even a few years ago.

But insofar as the large dislocations in prices are due to the rapid increase in demand from China (and the lag in production gearing up to increase supply in response), the increase in commodity prices does not forebode a paradigm shift. Just an increase in demand. And much of the increase in demand is short term. China's explosive demand will finally drop from its stratospheric level, either because China's economic development falters or because China is finally totally covered over in cement.

Paradigm Shifts -- The Usual Suspects
The rise in demand from China does not constitute a paradigm shift – nor does a continuing rise in demand as other countries move up the development trajectory and follow suit.

Nor does the recent rise in speculative demand. This has been a focus early on of Michael Masters. The relatively small supply of commodities compared to the demand that can arise from pension funds and other institutions investors, which lately has trickled down through the use of EFTs to include retail investors, all can create sizable distortions; big money chasing after a limited supply of commodities, coupled with underlying inelastic demand -- because, for example, people still need to eat.

Nor is there a paradigm shift due to technology, though obviously technological change alters resource demand, sometimes for the better and sometimes for the worse. Two examples in the positive column are the reduction of copper demand due to fiber optics and wireless, and the drop in demand for silver due to digital photography. One in the negative column is the increased demand for rare earths for electronics. But technological improvements and increased efficiency are a given in our current paradigm and cannot be considered paradigm shifts; neoclassical models of growth theory have included adjustments for technological change since the 1960s.

The mother of all paradigm shifts
But there is a paradigm shift underway, maybe even the mother of all paradigm shifts, and it is coming from a direction where Grantham and other bears are not looking.

The real paradigm shift, or more like a paradigm drift, because it is slo wly enveloping us, is that we are moving toward preferences and lifestyle where we will simply consume less. A lot less. Like improvements in efficiency, changes in tastes and preferences are nothing new, but this time is different.

I have already discussed this in previous posts on life in the experience machine and the world of smaller scale. In The Accidental EgalitarianI make the point that with the increased focus on technology – where we spend more and more of our time on our cell phone, doing emails, watching DVDs and surfing the web – there is less of a difference between how the super rich and the reasonably well off spend their time hour by hour during their typical days. The point of that post is that in practical terms the income gap is not as large as it might seem; that several orders of magnitude differences in income don’t make all that much difference in what these people do with their time. The point here is a corollary: those activities do not require much in the way of material consumption, and therefore not much in terms of commodities.

In The Technology-Driven Consumption Trap I argue that in the not-so-distant future the main items we will demand, beyond food, clothing and shelter, are “game systems” that approach the level of Nozick’s experience machine, allowing us to have the experience of being anyone we want, wherever we want (even in a world we have designed), accompanied by whomever we want, all in Realicta Immersion 3-D® with full sensory feedback.

Our demand for housing and transportation, two of the biggest commodity hogs, will be lower. McMansions will be totally passe. It should already be dawning on people that most all of our non-sleeping hours at home are spent in the kitchen and its adjacent family room. Living rooms and dining rooms are relics. When people internalize the fact that they spend most of their non-sleeping, non-bathroom, non-eating time in a ten by twelve foot space with their various experience machine prototypes, large homes will, by and large, go the way of cars with fins and chrome.

We obviously will not need to drive around as much, given that so much of what we want is delivered to us electromagnetically. And, getting back to real goods and technological advances, if we take the web-based distribution a few steps further, rather than having thousands of cars running from one store to the next, a couple of delivery trucks will ply the streets. So per-capita consumption of energy and resource-intensive infrastructure will decrease.

Given our evolved interests a few decades hence, most of us will be spending a fraction of our income on consumption. There just won't be a lot that we will demand that requires nonrenewable resources. What we will demand will be in the way of electronic products, which will only consume a few ounces of such commodities. We will basically eat, sleep, work and then veg out. Give us food, plumbing, heat and our two-hundred dollar experience machine games, and we will be happy as a clam.
People who are staring at a tsunami of demand for commodities from the developing world and predicting a doomsday of $400 oil and $4000 gold are missing the longer-term retreating tide of demand as citizens of the developed world actually demand decreasing amounts of energy, large goods, and heavy infrastructure. We won't be packing up and moving to Mars, as the science fiction solutions to resource depletion propose. We will pack up and move into the virtual world.

The following reflects my personal views.

The two best treatments of the financial crisis are both free for the reading, courtesy of the U.S. government.

The first to hit the press, the 600-page Financial Crisis Inquiry Report, is the product of a year and a half of work, seven hundred interviews, over a dozen hearings, and millions of pages of documents. The report is not as tome-like as it appears. It is a 400 page book (albeit one with small print) followed by 200 pages of references, appendices and dissents. Don't let the dissents bother you -- they are dealing with second-order issues.

What is most remarkable about this report is that it is written like a best-seller. For example, each chapter subsection begins with a clincher quote taken from the interviews. This not only keeps the story line going, it also allows the Commission to put forward some strong views through the eyes of the crisis participants. It will keep you on the edge of your seat, or at least as far toward the edge of your seat as any of the scores of crisis books written over the past few years.

The second work is the Anatomy of a Financial Collapse, a.k.a. the Levin-Coburn Report of the Senate Permanent Subcommittee on Investigations. This report, which came out in mid-April, weighs in at 640 pages of text, which includes almost three thousand footnotes. It is a brilliant work, constructed through four case studies that show the mortgage mess wending its way from the banks (WaMu), ducking past the regulators (OTS), then turbocharged by the rating agencies (S&P and Moody's) before landing into the waiting arms of the investment banks (Goldman with Deutsche Bank in a supporting role).

While the FCIC report covers the entire landscape, the Levin-Coburn Report, by putting the crisis into a set of interconnected and detailed case studies, distills the essence of the crisis with an historian's perspective and a novelist's flair.

M&A activity is showing signs of life, activity reaching its highest levels since 2007. What more appropriate symbol of the renewal of the economy, of the emerging spring-time of our business cycle, than the merger of two firms, their culture, management style and business as the genes, and the result of the union a manifestation of the process of economic evolution.

This metaphor might be passed off as nothing more than bad writing except that it is the way many people actually view things; capitalist evolution likened to natural evolution, perhaps with the implication that capitalism, like biology, is a fundamental life force.

It really is taken seriously in some quarters, and I am not simply talking about alpha males evoking the survival of the fittest during moments of self-reflecting on their business conquests. For example, in the last chapter of The Ascent of Money, Ferguson cites this as the view among thought leaders now and voices from the past such as Thorstein Veblen. He goes on to compare the recent frenzy of financial products to the ushering in of a financial Cambrian age and writes that, “a long-run historical analysis of the development of financial services suggests that evolutionary forces are present in the financial world as much as they are in the natural world”.

If by evolution we mean that things improve over time, and that in the course of this improvement some of the old ways fall by the wayside, then the economy and markets do indeed evolve. As does nearly everything to which we put our hands. We can just as easily say that horsemanship, metallurgy or warfare evolve. This is nothing more than saying that we are imbued with intelligence and creativity, which may indeed be the consequence of evolution of our species. But that does not mean that everything we create is innately part of an evolutionary process. We make things better over time and create new things. It isn't just laundry detergent that is constantly “new and improved”. There is nothing particularly remarkable about tagging economic progress as evolution when all that is happening is an upward trajectory because of our application of intelligence, creativity and a desire to improve things.
If we follow this line of thought and try to apply the theory of biological evolution to the markets, we will not end up where we would hope. A species would not survive in the natural world if it pulled its evolutionary strategies from the capitalist playbook. And the converse is also true. The capitalist paradigm most resembles an evolutionary strategy that has failed in nature. That is, taken as a biological evolutionary process, capitalism leaves something to be desired.

Capitalist Evolution
“I have three words: Destroy, Destruction and Destroy” Marvin Hagler

In Capitalism, Socialism and Democracy, Joseph Schumpeter repeatedly speaks of “capitalist evolution” resulting from “the opening up of new markets, foreign or domestic, and the organizational development from the craft shop and factory to such concerns as U.S. Steel illustrate the same process of industrial mutation—if I may use that biological term—that incessantly revolutionizes the economic structure from within, incessantly destroying the old one, incessantly creating a new one. This process of Creative Destruction is the essential fact about capitalism”.

The phrase "creative destruction" romanticizes the common; creative destruction basically means out with the old and in with the new. Creativity without Schumpeterian “destruction” is difficult to fathom given fixed resources and a preference for better over worse.

But by whatever name, creative destruction is not the norm. Capitalist evolution has more to do with consolidation, with successful firms growing to dominate the market on the one hand, and breeding more of their kind on the other. This is the the dynamic of competition, firms following the scent of what is making money, leading economic rents to collapse.

The sort of evolution that we see in the markets, that is embodied in M&A as it is elsewhere, must take the world as it is. And do so even if it thinks it knows better. Otherwise it will become an also-ran against other firms willing to ignore the possibility for surprises. This is the way to read Citigroup CEO Chuck Prince’s famous statement, “as long as the music is playing, you’ve got to get up and dance”. That statement could say something about obliviousness or imprudence, but unfortunately it is also stating the way things work in the free market system.

To see the pressures to consolidate and stamp out diversity, consider the following:

• Everyone is integrated into the most efficient production process. This requires specialization based on comparative advantage.
• Efficiency leads everyone to 'go with the winners'. That is the way economic rents are reduced. So even if an economy starts with many different enterprises and approaches, there is a tendency to swarm toward the few, based on the existing economic world, preferences, resources, and technology.
• Everyone becomes tied to the same networks, be they power, transport, communication.
• Everyone buys the same sort of products. The convergence even greater now than in the past because of the economies that come from people “locking in” to use common platforms and software.

Go back to M&A as an example. It reduces diversity and creates a larger entity that by design is structured or selected to do better in the current environment. Maybe it looks like natural selection, but it is not all that similar, at least not that similar to the route of natural selection that has come to dominate the biological world.

It turns out that an entity optimized to compete and survive in the present is not one that is resilient in the face of unexpected shocks. Resilience requires taking resources away from profit maximization in the present, and if the current world lasts too long, then pursuing that strategy means being eaten up by more single-minded competitors. So we all have to go with what works best now, go with the winners.

The greater the opportunities for capitalist adventures, the larger the crowd in the race to the fertile fields, and the lower the diversity in the economic landscape. If we were interested in having our species, however defined, last, we would pursue a different strategy than what is possible in the competitive world. As I will discuss below, one such strategy is to do what biology does, which in any state appears non-optimal.

Evolutionary diversity goes hand in hand with not being optimal in the present environment. Nature is rife with what would pass as bad management practices. It is not likely that there will be a lot of diversity while at the same time requiring that each of the diverse agents will give one another a run for the money in the present. There may be a few types of firms that can compete, but look around in any sphere of business or markets, and you will see that the norm is for all to converge on what works now. Diversity cannot last, only optimality to the present can.

The Asexual Capitalist
When we speak of evolution we also are speaking about reproduction, which leads to the question of why we have sex. Asexual species can reproduce more quickly and efficiently than ones that require the mating of a male with a female. So why don't the asexual species overrun the sexual ones? Why doesn't natural selection get rid of the males?

Sexual reproduction is not only less efficient than asexual reproduction rate, it also tends to preserve “suboptimal” characteristics – biological traits that are irrelevant in particular ecological settings. Sexual organisms carry an unnecessary second copy of almost every gene, and the interaction of the duplicated genes creates unnecessary diversity, and in fact is the source of many diseases that reduce an individual’s odds of evolutionary success. Species are not as streamlined and efficiently built, as honed to meet the world as they might be. Darwin remarked that:

Organs or parts in this strange condition, bearing the stamp of inutility, are extremely common throughout nature. Some of the cases of rudimentary organs are extremely curious; for instance, the presence of teeth in foetal whales, which when grown up have not a tooth in their heads; and the presence of teeth, which never cut through the gums, in the upper jaws of our unborn calves. Nothing can be plainer than that wings are formed for flight, yet in how many insects do we see wings so reduced in size as to be utterly incapable of flight, and not rarely lying under wing-cases, firmly soldered together!

What appear in the obvious physical traits also appear, and are of more importance, on a less visible level: the “pseudo genes” that seem to have no particular purpose, that are turned off and therefore certainly aren't doing anybody any good – at least not in the current environment.

DNA for many species is riddled with these pseudo-genes, unused sequences that are potentially transformable into new, functional gene. The classical formulation of evolution – or at least one thread of it that was prevalent in the eighteen hundreds – believed in the same sort of trend toward efficiency that forms the bedrock of economics, namely that the forces of nature would eliminate such inefficiencies, and thus over time the species would lose diversity, becoming increasingly streamlined. But as Darwin remarked, we see nonfunctional parts remain at the macroscopic level, and we see the same at the microbiological level as well The reason is simple: the resulting diversity, though less than optimal in any one environment, enhances the odds of survival when the environment changes in unanticipated ways, in ways for which the species has no genotypical prior. The dominance of sexual reproduction over the asexual alternative rests on the apparent inefficiency of carrying around this excess baggage of pseudo-genes.

So although at first it seems to be almost self-evident that if a species can reproduce asexually with more efficiency and reproductive fidelity, then it would be the dominant approach to evolution, there is a reason that nature has not worked that way. Despite this inefficiency, the number of sexual species far outweighs the asexual ones. Although there is general agreement that in the short term asexual reproduction (a.k.a. cloning) is better, that it can maintain a given ecological niche, asexual reproduction tends to be a dead end in the long run because no ecological niche is stable.
Second, and more important from the perspective of pushing an analogy to economics, is that no ecology is stable. Surprises and shocks occur that are not in the organism's genotypical prior – that is, shocks where the organism has no way of being pre-adapted. Its genome may no longer be up to the job, and if it is reproducing asexually there is not much it can do about it. Absent a few random mutations, it is stuck with what it has. So in the long run asexual lineages usually degenerate and go extinct.

In contrast, if organisms reproduce sexually, the shuffling and recombination of genes increases the odds that some offspring may be lucky and get dealt a set of genes that produce offspring that happen to be well-adapted for the shock. By bringing together the variations arising in different individuals that can turn out to be beneficial ex post, sex increases the odds of survival.

Asexual species are like weeds, optimized for quick growth. But over time they give up their territory to species that may be poorer colonizers but are more effective long term survivors. Thus asexual reproduction is not the way to go if a species plans to stick around for more than a few ticks of the evolutionary clock.

Capitalists are also like weeds. In a capitalist system, speed of development and colonization – grabbing market share – is of the essence to capture and generate market share. The hope is to then turn from the asexual mode to garner the flexibility to maintain that market in the face of changing preferences and market conditions.

If something like pseudo-genes appeared in the Schumpeter's capitalist evolution, where individuals are optimizing for a given environment, such baggage would be stripped away in the quest for economic efficiency. The competitive economy casts off excess baggage, as it does useless appendages. The competitive system is less forgiving of the inefficiencies of carrying around excess baggage than is nature. Modes of production and the workforce are not left free to roam away from what generates the most profit. If they do, it is chalked up to poor management, and the business will be on the acquiree end of an M&A transaction.

When the going gets tough, the hidden genes get going
To understand the origins of diversity in species, we need to go beyond the genetics into what is termed the epigenetic system. Epigenetics is easy to see in our own bodies. Our liver cells and kidney cells both have the same DNA the same genes, but something tells kidney cells to beget kidney cells and liver cells to beget liver cells. That something is the epigenetic inheritance system. It tells genes when to turn on and turn off.

The reason we humans can share so many genes with other species is that, although the genes might be the same, the sequences making up switches, and thus the nature of of the genes' interaction, have evolved to be different. Small changes in switches can produce very different patterns of genes turning on and off during development. The diversity of organisms is largely due to evolutionary modifications of switches, rather than genes. This is also the reason that large changes can happen so quickly (at least relative to evolutionary time): the genes stay the same, but switches change. These changes can occur in the parts of DNA long thought of as “junk”, and are the major force in evolution, rather than the rapid appearance of entirely new genes.

The combination of a high rate of generation and a good chance of being appropriate means that adaptation through the epigenetic system will both be much faster and more likely to have a positive result than adaptation through genetic change. When faced with an environmental challenge, these hidden genes come to the fore to be captured by natural selection and generate evolutionary change.
There are a number of characteristics between sexual versus asexual reproduction that relate to the tendency for economies to be unstable in the face of shocks. The diversity emerging from the genetic and epigenetic mixing, especially under stress, creates less-than-optimal variations in species that kick in to allow the species to survive these shocks. The capitalist system at its most efficient does not have a similar mechanism. Indeed, the tendency is decidedly in the opposite direction. We go with the winners, and those who decide to take a non-optimal path will disappear from the scene well before a shock comes about which derives a benefit from that diversity.

Destruction not by murder, but by suicide.
In my book, A Demon of Our Own Design, I draw two examples from biology to illustrate the ways to cope with the risk arising from unanticipated events. On one side I have the cockroach, an insect that has survived for eons with the simple escape mechanism of moving away from gusts of air. In any one environment, the cockroach will be less than optimal, because it does not even consider visual or olfactory cues. On the other side, I have the furu, a fish that once inhabited Lake Victoria, a large lake in the center of Africa. The furu developed into many species to take advantage of every nook and cranny of the lake’s ecology. Finely tuned but not robust, the furu disappeared once the unanticipated happened, the Nile Perch was introduced into the lake.

The point of this comparison is to illustrate that being optimal in any given environment might not be optimal in the long run. The robust but coarse response might always be an also-ran, but be more survivable as shocks occur. The non-optimal but robust species survive because over eons species are beset by one surprise after another, surprises for which they do not have a genotypical prior.
Sexual and asexual reproduction operate much like the cockroach and the furu, respectively. Sexual reproduction is less efficient in any given setting but is more survivable and robust across varying environments. Asexual reproduction is best if you are a fit organism in the current ecology, and if that ecology doesn't change. (Or if it doesn’t, but long-term survival is not the objective).

Given the constraining effect of competition on diversity, given the rapid push for all hands to move in the direction of the current best thing, if someone were to put a gun to my head and ask me to fit economics into the biological world of evolution, then I would answer that capitalism evolves asexually. It wants weeds, the short-term winners.

And it is because of this that stability begets instability in the capitalist system. If we want to speak of capitalist evolution, the process of stability breeding instability is ingrained into the genes, the process of evolution, because the more dominant the opportunities are for success, the less diversity there will be, and the more the capitalists will follow the asexual path. We go with the winners, and those who decide to take a non-optimal path will be taken from the scene well before a shock comes about which derives a benefit from that diversity.

Sun Pin was in battle against the Wei general, P`ang Chuan. Sun Pin said: 'We have a reputation for cowardice, and our adversary despises us. Let us turn this to our advantage.' Accordingly, when the army had crossed the border into Wei territory, Sun Pin gave orders to show 100,000 fires on the first night, 50,000 on the next, and the night after only 20,000.

P`ang Chuan pursued them, saying to himself: 'I knew these men were cowards; their numbers have already fallen by more than half.' In his retreat, Sun Pin came to a narrow pass, which he calculated that his pursuers would reach after dark. Here he had inscribed on a tree: 'Under this tree shall P`ang Chuan die.'
When night fell, he placed archers in ambush, with orders to shoot where they saw a light. P`ang Chuan arrived and struck a light to read what was written on the tree. His body was immediately riddled by a volley of arrows, and his army thrown into confusion.”

In a recent post I discuss the limitations of neoclassical economics and the strain of behavioral economics that remains tethered to it. I argue that they fail because the market is inhabited by people, heterogeneous and context-sensitive, who do not live up to the lofty assumptions of mathematical optimization and Aristotelian logic that underlie these approaches – and do not do so for good reasons.
The nature of complexity also is different in the economic realm from that in physical systems because it can stem from people gaming, from changing the rules and assumptions of the system. Ironically, "game theory" is not suited to addressing this source of complexity. But military theory is.

What is Complexity?
Complexity can be either an annoyance or a boon, depending on one's enthusiasm for tricky problems. We all know intuitively that complexity makes accidents both more likely and more severe. After all, any machine with many parts has more risk of having something go wrong, and with more interconnected mechanisms there is more risk that a single failure will propagate to cause the entire machine to fail. For markets, the accidents are market crises. I pointed to complexity and tight coupling as key components in the origin of market crises in my book, A Demon of Our Own Design.
But there remains the task of defining the type of complexity that matters for financial markets. There are a number of different concepts that harbor under the umbrella of complexity, which is not surprising, given that complexity is an issue in many different fields, ranging from physics and engineering to biology to sociology and economics. I want to lay out my view of what sort of complexity matters in economics and finance, and contrast it with some of the notions of complexity used in these other fields.

The measurement of complexity in physics, engineering, and computer science falls into one of three camps: The amount of information content, the effect of non-linearity, and the connectedness of components.

Information theory takes the concept of “entropy” as a starting point: essentially, the minimal amount of information required to describe a system. Related to this is a measure called thermodynamic depth, which looks at the energy or informational resources required to construct the systemic. The idea is that a more complex system will be harder to describe or to reconstruct, though this is problematic because it will look at random processes as complex; for example, by these sorts of measures a shattered crystal is complex.

The use of information content has been extended to define the complexity of a system as the amount of energy needed to maintain it. For example, it has been employed to explain the collapse of societies, arguing that as societies become more complex, they require more of their energy (loosely defined) to maintain the status quo, and can no longer defend themselves against the many inroads toward decline. In biology, one measure of complexity related to information content is the gene count, though that alone might understate complexity because what matters is not just the number of genes, but how they are used in an organism -- the epigenetics of how they are turned on and off, and even how all of these interact in different environments and during periods of stress.

Non-linear systems are complex because a change in one component can propagate through the system to lead to surprising and apparently disproportionate effect elsewhere, e.g. the famous “butterfly effect”. Indeed, as we first learned from Poincare's analysis of the three body problem, which later developed into the field of chaos theory, even simple non-linear systems can lead to intractably complex results.
Connectedness measures how one action can affect other elements of a system. A simple example of connectedness is the effect of a failure of one critical node on the hub-and-spoke network of airlines. Dynamic systems also emerge from the actions and feedback of interacting components. Herbert Simon posed a fractal-like measure of system complexity by looking at the layering of hierarchy. That is, the depth to which a system is composed of subsystems, which in turn are composed of yet deeper subsystems.

A common approach to complexity in biology is to use some variant of size, such as the number of part types in an organism or the number of nodes in a food web. The use of size might seem intuitive at first, because things that are bigger -- that have more parts -- generally are more complex. But building a road that is twice as long, piling leaves twice as high, pushing twice as many letters through a postal system all increase some dimension of size without making things more complex.
The definition you use depends on the purpose to which you want to apply complexity. For finance, several of these measures of complexity come into play. There are non-linearities due to derivatives. Connectedness comes from at least two sources: the web of counterparties and common exposures. Exacerbating all of these is the speed with which decisions must be made.

Also, because economics and finance deal with human-based rather than machine-based systems, our tendency to operate based on context will invariably lead the conventional tools used to solve complex physical systems to miss the mark. But another important point for finance which makes complexity differ from its physical counterparts is that in finance complexity is often created for its own sake rather than as a side-effect of engineering or societal progress. It is created because it can give a competitive advantage. I will discuss this more below.

An Epistemological Definition of Complexity
A complex system is one that is difficult to understand and model; as complexity increases, so do the odds of something unanticipated going wrong. This is the driving characteristic of complexity that is most important for finance and economics: complexity generates surprises, unanticipated risk. “Unanticipated” is the key word: it is not simply that more complexity means more risk -- we can create risk by walking on a high wire or playing roulette. Rather, it is that complexity increases risk of the “unknown unknowns” variety. And the risks that really hurt us are these risks, the ones that catch us unaware, the ones we cannot anticipate, monitor or arm ourselves against. Simply put, a system is complex if you cannot delinate all of its states. You may think you have the system figured out, and you might have it figured out most of the time, but every now and then something happens that leaves you scratching your head. This is an epistemological interpretation of complexity. It defines complexity as creating limits to our knowledge. Neoclassical economics does not admit such complexity.

If the states in a system can be determined in a sufficiently short time frame, it is not complex, even though doing this may require more analytics and computer power. So complexity is measured by the increased risk of surprising modes of failure and propagation. This means a complex system can be defined as one that cannot be solved, whose effects under stress cannot be anticipated.
The limits of knowledge arising from this definition of complexity are not randomness or prediction error. Uncertainty where the states are know but it is uncertain which state will be realized is not a complex system. This distinction has been made by Keynes and Knight between risk and uncertainty, embodied in the concept of Knightian uncertainty.

If we take this route of defining complexity as creating limits to our knowledge, then these limits are constrained further because although we can know the characteristics of a process or system that tends to be complex, we often will not know definitively if something is complex ex ante, because to do so we must know that there are states that we do not know.

Complexity Depends on Timeframe
We cannot think about complexity without reference to time frame. A problem might be complex if we only have a few seconds to respond, but not complex if our time frame is one or two months. If we have enough time to solve a problem and understand and anticipate all of its possible outcomes, then it is no longer complex even though, to restate the point, it might be costly to solve and monitor, it might have random results (random but where we can know all of the possible states and assign probabilities to each one), but it no longer can lead to surprises.

This importance of time frame is the reason we have to look at complexity and tight coupling jointly. Tight coupling means that a process moves forward more quickly than we can analyze and react. For example, the college matriculation process is complex in one sense – there are many requirements, and those have prerequisites layered on them; there are courses that are dropped because a key professor is taking leave – but there also are appeals that can allow for adjustments within the time frame to deal with these complications so that students wend their way through the maze.

A second characteristic for complexity in economics, and finance in particular, is that it is not exogenous, simply sitting out there as part of the world. We create it ourselves, indeed often create it deliberately, and create it expressly to harvest the attendant unanticipated risks.

What does it mean to create risk, and why would we want to make our life more complicated by doing so? Let me address this by first taking a detour into the well-trod ground of game theory, and then into an area that is more applicable: military strategy.

This is Not a Game
When arguments related to strategy, to cognition and social interaction enter into the discussion, the first arrow pulled out of the quiver is game theory. And, at least in the view of some game theorists, it will carry the day. Aumann and Hart state that, “Game Theory may be viewed as a sort of umbrella of ‘unified field’ theory for the rational side of social science”. It is certainly true that game theory takes a stab at the human component, the “I know that you know that I know that...” sort of interaction, and in doing so, adds a level of model complexity that reflects social interaction. It turns out that game theory is not as hard as it may initially sound. For example, the interaction among low species of birds and insects employ the same sort of recursive games and do so with ultimately predictable and stable results.
Game theory began with the insights of John von Neumann and Oskar Morgenstern in their book, The Theory of Games and Economic Behavior. They defined a game as an interaction between agents governed by a set of rules that specified possible moves for each participant and the set of outcomes for each possible set of moves. The theory of games rests on defined rules and outcomes. It also assumes rationality. “Rational” means “logical”, and I have already argued in the posts linked above why that might not be the best assumption to use. But the fact that games are predefined with bounds and states that correspond to the actions of the players also limits their realism and skirts a key source of the complexity in human interaction, be it in markets, the economy, or society generally.

Finance is often regarded as a game, but by the conventional von Neumann definition it is not. Granted it is ostensibly circumscribed by the rules of law, but so is war circumscribed by the rules of the Geneva Convention (at least conventional war). Adversaries at war do not have to play by the same rules or even play the same game. Indeed, what more is the strategy of war than playing the game that works to your advantage, and doing so while keeping your adversary unaware of that game? What more is the charge of “asymmetric warfare” than having an adversary that is not playing by your rules or your game – and is winning the war in the process?

“The Strategic Game of ? and ?”
The military theorist John Boyd used this phrase to convey the essential point that warfare is not a game. Or if you want to think of it as a game, it is a game that is ill-defined, with rules that are, put gently, subject to interpretation. Thus, he said, for any strategy, “if it works, it is obsolete. Yesterday’s rules won’t work today”. This point was also made by the great German Field Marshall Helmuth von Moltke: “In war as in art there exist no general rules; in neither can talent be replaced by precept.” That is, plans – and models – don't work because the enemy does not cooperate with the assumptions on which they are based. In fact the enemy tries to discover and actively undermine any assumptions of his opponent.

Boyd viewed the key to tactical dominance as creating confusion for your adversary; “The warrior’s object is to create pandemonium, chaos, disorder – and you sweep out the debris”. This philosophy found its first success in air-to-air combat, where Boyd's theory allowed even those with technically inferior aircraft to dominate the skies. Rather than simply operate efficiently in the given environment, he taught pilots to “generate a rapidly changing environment” to suppress or distort his opponent’s observations so that he could not adjust to these environmental changes, reducing him to “confusion and disorder,” so that he would act with accumulating errors “because of activity that appears uncertain, ambiguous or chaotic.”

If the time frame is long enough to allow reaction within the “rules” of the existing system, we have gaming. If it allows for the rules to be changed, we have something more akin to warfare. In war itself, changes of this sort can occur very quickly, because the key to victory is creating both change and the tight coupling that prevents adjustment to that change. In finance, changes also can occur quickly, because finance has no physical plant to alter, is designed for innovations, and largely works in the close to instantaneous realm of information flows and trading. When we move to the macro sphere, the changes of this type take longer, because they require time for institutional and political shifts. But the objective remains the same: move to unanticipated new environments, thereby creating endogenous uncertainty.

The Informational Battlefield
After its acquisition by the hedge fund manager Steve Cohen, Hurst’s “shark in the tank” sculpture, The Physical Impossibility of Death in the Mind of Someone Living, became a metaphor for the sophisticated traders preying in the waters of the financial markets. Like most metaphors, it only goes so far, mainly because sharks take their environment as given, whereas those operating in the market – particularly those at the top of the food chain – can alter the market to their advantage.

If we are going to use the analogy with war in economics and finance, the battlefield where Boyd's dictum will be applied will be in the realm of information. One tactic in this battlefield is to create informational asymmetries. If the market is becoming efficient, if information is accessible to everyone at the same time, then either create new private information or else speed up your access to the public information. Derivatives play a role in the first approach, with banks creating information asymmetries by constructing financial instruments that they understand better than the buyers. For the second approach, consider the news feeds that are fed to high frequency traders with millisecond response times.

Another tactic is to destroy information. One way this is done is through what Steve Wunch has called algorithmic shredding; algorithmic trading breaks down trades into confetti-like pieces that obscure the information that might otherwise be broadcast to the market. Yet at the same time those doing the shredding employ more sophisticated methods which track the pattern of trading as it moves from one venue to the next in order to reconstruct vital information about the pre-shredded trade.

Conclusion
The interaction between the market participants, and for that matter between the market participants and the regulators, is not a game, but a war. Complexity in the information battlefield, the willful creation of complexity – complexity that is peculiarly human in origin – and the resulting endogenous uncertainty, is particularly confounding for the neoclassicists. The battle spells trouble for the foolhardy armed only with the neoclassical methods.

In a recent post I laid the blame for the inadequacies of neoclassical economics and behavioral economics on the failure to take into account human context. By context I mean that humans make decisions that are colored by their assumptions, experience, agenda, and even their sense of foreboding.
One way for economics to overcome its deficiencies is to take into account these inherently human characteristics. A different route is for people to cast aside these traits and start behaving more like computers. It looks like we might be going down the latter path.

In an article in this month's Atlantic, Brian Christian recounts his role as a confederate in the annual Loebner competition, which runs the Turing Test to see if computers can fool judges over the course of a five minute conversation conducted via computer console. The humans won this time around, as they have in each of the twenty years the contest has been run. And Christian's bet is that the computers will not be winners anytime soon because even as computers get faster and more adeptly programmed humans will counterattack with the weapons in their arsenal. One of those, which Christian used to win the event's prize as the “most human human” (the human who was most often identified correctly as a human), was to interrupt frequently and backtrack to previous points in the conversation the way we do in real conversation. By comparison, the computers far preferred a you-ask-I-answer interrogative approach.

The tendency for the Turing Test to become a competitive game for the humans as well as the computer programmers -- that is, where the humans are trying to win rather than 'be themselves' within the structure of the game -- defeats the test's intention, which is more or less to have a computer be indistinguishable from a person in a “normal” human interaction: say, a pleasant dinner conversation with a stranger, in which neither party is trying to prove that he is not a computer.
A better Turing Test to overcome the problems introduced in the competitions is to interject a computer into a round of dinner conversations where the human subjects are not made aware that this is occurring. After the fact, subjects are told that some of their companions might have been computers, and only then are they asked to rank the guests by “humanness.”

Apply the same method to other common modes of conversation, moving down the line toward the increasingly vacuous and context-less: e-mail exchanges, then online chat, and finally “texting.” As we go down the line we lose more and more context and depth. Each back and forth depends, if anything, on fewer and shorter prior communications. Tweets, which seem like the lower-limit of texting, are virtually “stateless,” meaning that they often spew forth apropos of nothing. As we descend into these more modern forms of communication it becomes easier and easier for a computer to “win” the Turing Test.

To illustrate this point, Christian relates an exchange between a computer and an unwitting human, where the human engaged in a conversation for an hour and a half, and then broke away without ever realizing there wan no human on the other end. (The dialogue, presented in part in this link, is one of the funniest things I have ever read). And this occurred in 1989:


We are indeed sinking to that level, not by becoming more verbally abusive, but by becoming less verbal, period. We are moving as a society toward the vacuous and non-contextual as we embrace new modes of conversation. Many have written on the vacuousness of IM and SMS-based conversation. But it is not depth of content that differentiates humans from machines. A computer can already beat us in terms of content. One human in a previous Loebner competition was pegged as a computer because she knew more Shakespeare than the judges thought was humanly possible, but not more than what they thought was possible for a computer. Recently a computer went head-to-head with past Jeopardy champions and won handily.

For humans, context matters more than content. A computer does not have existential angst. It does not hold grudges or have its reactions shaped by its childhood experience. It does not respond to a remark based on the previous conversations and how that colors the sense of the other person's interests and emotions. These dimensions of human interaction are flattened as we sink into the texting, twittering world.

Imperial Exam Halls

In the Ming Dynasty, (1368 – 1644), China established an examination system as a merit-based approach for appointments to government office. There were three levels to the exams, with the final cut then coming through an examination administered by the Emperor himself. The subject matter of the exams was standardized beyond anything we see today. It was based on a limited set of ancient works, stripped of any contemporary additions. The examinations depended exclusively on the memorization of these classics. The exams were administered in a way that assured anonymity. Those reaching the third level wrote in separate cells, the equivalent of modern-day cubicles. After days of writing, they literally threw their papers over a wall, where the writing was copied by a scribe to assure there would be no tell-tale indications of the examinees.

Those seeking elite government office spent years preparing for the exams. Those who failed could reapply as often as they wished. This gave hope that even those of humble birth could rise to the upper class by dint of their will and assiduous efforts. This in turn increased the stability of the Dynasty, because those who might vent their frustration of being outside the system and who had the talent for fomenting a revolution could be channeled into the elite rungs of society instead. And the fact that this path existed made it more difficult to corral others of a similar mindset.

This system was adopted by other Asian countries, notably Japan and Korea, and has continued to the modern era with little change. The path to the top colleges came through similarly standardized tests based on that ability to memorize and learn by rote. These tests were of such critical importance that students followed up their class work with hours of after school studies, and often took an additional year to prepare. Tests governed admission into the elite middle schools, which in turn prepared the student for the next set of tests to get into the elite high schools, which then led to the elite colleges. Unlike the U.S., the pecking order of those colleges is clearly determined, with one school indisputably at the top – Seoul University in Korea, Tokyo University in Japan.

I studied Asian languages in college and spent a few years in Asia, seeing this first hand. Just before I spent time in Korea, the country had eliminated the grueling examination program for entrance into the middle schools, and the result was an almost immediate increase of an inch in the average height of twelve and thirteen year-olds. I knew students who took a year after college, living in squalid conditions while studying non-stop for the kodung koshi, the equivalent of the third-level exam that extended from the Ming. And those who failed could retake the exams, in the same spirit as occurred during the Ming.

I believe this tradition of examination, based on memorization and rote learning, with a fanatical focus to the exclusion of all else, is at the root of the Asian “Tiger Mother” approach to raising children today.

The examination system is less prevalent now in Asia because government service has lost some of its earlier luster as opportunities expanded in the private sector, and it is certainly irrelevant for Asians who now live in U.S., (the preparation for the SAT, substantial as that can be, pales in comparison). But the tradition remains. Perhaps it survives as more than a tradition, because the families of those who harbored the characteristics that allowed them to succeed in these exams would have flourished, so those traits would have survived disproportionately.

The rigor of this examination process, which in the U.S. simply does not require the level of focus and does not fully determine one's future, is being channeled into other areas. One area, prominent in the Tiger Mother book, is music. Several of my children who participated in piano competitions were often the only non-Asians. The results of the Tiger Mother progeny's two plus hours a day of practice, focused a year at a time on the two or three pieces required for most competitions, is spectacular in one respect, and flat in another. Such musical training is more like training for athletics; indeed piano performance in particular can be readily transformed into an athletic event that focuses on small-muscle groups. The performances of the piano athletes are technically spectacular, but as would be expected from something that is developed by rote, they can be lean on musicality. Think gymnastics versus ballet. (I sponsor a piano competition in the memory of one of my children who had an insatiable love of music where a broad repertoire is required, with the hope that this will map to students who have a love of music as an end in itself).

What is the end result of this vestige of the Ming approach to education? Well, we can look back to the end result in the Ming itself. Those who passed the examinations and entered into the elite offices had the classics down cold. But they didn't know much else. How could they, given the efforts and focus required of these examinations? And while I don't have much to go on, my guess would be that they were not exactly off the charts in terms of what we now popularly call emotional IQ. But the history of the period suggests that for all the laudable screening, those who succeeded to office often did not succeed in the office.

My experience is that this process as it has been retained in the modern era leads to similar failings. That should not be surprising, because as with the Ming, there is little time for anything beyond the task. There is an incredible uniformity in the approach to problem solving, and the sorts of problems that can be solved. When I was a professor, I had two Korean students who handed in identical exam papers. They went so far as to work out the problems in the same steps, put a box around each problem, put identical work in the same place in the box. They both even underlined each of the answers twice. It was clear to me that one of them must have copied in distinctively uncreative fashion from the other. When I called them into my office and confronted them with their identical work, they really had no idea why I thought there was a problem. They had not cheated, they had been trained with painstaking precision to do things in the same way. Thus the form of their work was identical, the process of their solutions was identical, and their mistakes were as well.

A few months ago I discussed the failing of econophysics, and more generally, the economic paradigm that treats people like computers and views economic dynamics like physics. The natural follow up question is, “What can you say that is constructive?” The answer is an emerging approach to behavioral economics.
Over the past few decades it has dawned on some researchers that we don't make decisions the way most economists think we should. And as a result behavioral economics has become a burgeoning field of study. Initially, the bulk of this field consisted of cataloging behavior deemed aberrant and anomalous. That is, the underlying assumption was that the economic view of decision making is the correct one, and the economists need to see where people get it wrong. Thus, we had descriptions of behavioral economics such as “exploring limited rationality” and developing models for the “systematic imperfections in human rationality.” When inconsistencies between behavior and theory were demonstrated, the most charitable response from the neoclassical school was that maybe there was a missing factor; the theory was correct but not well parametrized. Unlike similar fields in psychology and biology, little time was spent on understanding how people think, why they think the way they do, and the ways the bedrock assumptions of economics based on mathematical methods and axioms of behavior might be off the mark.
And they probably are off the mark because, after all, neoclassical economics is missing half the story. It has left out any consideration of the context in which people make decisions, how that relates to people's varied experience, environment, and the uncertainty they harbor about how the world might change in unanticipated ways -- ways that cannot be captured through an enumeration of the probabilities of the possible states of nature. One field that does take this important (for humans) context into account is called behavioral ecology. It is not as well known in economics as it is in biological and psychological studies of behavior. Now, behavioral economics is incorporating this psychological realm.
This new approach is a quiet revolution that may transform the way we look at economic behavior. The era of mathematical, axiomatic views of human behavior will give way to approaches that start with how people look at decision making, understanding why they do that, and then understanding why that approach might have arisen evolutionarily and how it, rather than the utility maximization approach that has dominated the field for two generations, moves us closer to reality.
Following is a critique of the neoclassical approach, and the initial and perhaps still dominant approach of what might be called Behavioral Economics 1.0, within the context of behavioral ecology. A key proponent of behavioral ecology is Gerd Gigerenzer. I rely on his writings, including his book Rationality for Mortals, in much of the discussion below.

Assumption: We are Logicians
The seminal work on which behavioral economics 1.0 rests is that of Kahneman and Tversky. Using carefully posed questions, they plumb the ways people fail as rational beings, where rational means making decisions in a way consistent with the rules of logic. They find that the same question posed in different but logically equivalent ways leads to different results. They catalog these aberrations as demonstrating human tendencies toward heuristics, biases, frames, and other devices.
The notion here, which was then embraced by the first wave of behavioral economists, is that if nothing else, a rational human should act logically. The problem with this is that for humans logic cannot be considered apart for context, such as the usage and norms of language. For example, does anyone really think that when Mick Jagger sings “I can't get no satisfaction” he actually means he can get satisfaction? If you are parsing like a logician, that is what you think, because you are operating in the absence of context, namely how people use language. Language usage and the mode of conversation are among the clearest examples of how context and norms matter. If someone says “I'm not going to invite anyone but my friends and relatives,” does anyone really think that means he will only invite that subset of people who are both his friends and also his relatives? Again, that will be the takeaway for someone parsing like a logician. These two examples are simplistic, but if you look at the work used to establish the failure of logic and inconsistencies based on framing and the like, they are fairly illustrative.
The bedrock of much of behavioral economics assumes that we should follow the rules of logic, and when we don't, that it is suggestive of a behavioral bias or anomaly; the axioms are right, and we are flawed. The objective is to uncover those flaws. A classic example of the problems that come from this assumption is shown by this question posed by Kahneman and Tversky, and critiqued by Gigerenzer:
Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student she was deeply concerned with issues of discrimination and social justice and also participated in anti-nuclear demonstrations.
Which of two alternatives is more probable:
A. Linda is a bank teller.
B. Linda is a bank teller and is active in the feminist movement.
The vast majority of U.S. college students who were given this question picked B, thus scoring an F for logical thinking. But consider the context. People are told in detail about Linda, and everything points to her being a feminist. In the real world, this provides the context for any follow up. We don't suddenly shift gears, going from normal discourse based on our day-to-day experience into the parsing of logic problems. Unless you are a logician or have Asperger's, the term “probable” is going to be taken as “given what I just described, what is your best guess of the sort of person Linda is”. Given the course of the question, the bank teller is extraneous information, and in the real world where we have a context to know what is extraneous, we filter that information out.
Demonstrating our failures to operate within the framework of formal logic is more a manifestation of logic not being reconciled to context than it is of people not being logical. Much of Kahneman and Tversky's work could just as well have been directed toward the failures of formal logic as a practical device than the failures of people to think with logical rationally.

Assumption: We are Mathematicians
In going up against the neoclassical paradigm, behavioral economics sets itself against mathematical structure. A mathematician entering the world of economics begins with a set of axioms. That is just the way mathematics works. And one of those axioms is that people think like mathematicians. In starting this way, they fail to consider how people actually think, much less how that thinking is intertwined with their environment and the context of their decisions.
The mathematical approach is to assume that, absent constraints on cognitive ability, people will solve the same sort of problem a mathematician will solve in decision making: one of optimization. Then, recognizing that people cannot always do so, they step back to concede that people will solve the optimization problem subject to constraints, such as limited time, information and computational power. Of course, if computational power is an issue, then moving into a constrained optimization is moving in the wrong direction, because the new problem may be even more difficult that the unconstrained one. But given the axioms, what else can you do?
It doesn't take much familiarity with humans – even human mathematicians – to realize we don't actually solve these complex, and often unsolvable, problems. So the optimization school moves into “as if” mode. “We don't know how people really think (and we don't care to know) but we will adjust our axioms to assume they act 'as if' they are optimizing. So if we solve the problem, we will understand the way people behave, even if we don't know how people's mental processes operate in generating their behavior.”
Behavioral economics 1.0 does not fully get away from the gravitational pull of this mathematical paradigm. Decision making is compared to the constrained optimization, but then the deviations are deemed to be anomalies. Perhaps this was a necessity at the time, given the dominance of the neoclassical paradigm. But academic politics aside, it might be better to ask if the axioms that would fit for a mathematician are wrong for reality. After all, I could start a new field of economics where I assert as an axiom that people make decisions based on astrology, and then enumerate the ways they deviate from the astrological solution. Of course, people will throw stones at such an axiom, but I do have evidence that there are people who operate this way, which is more, as far as I can tell, than the optimization school has.
Behavioral economics of the 2.0 variety, patterned after the context-laden methods of behavioral ecology, does not take mathematical optimization as its frame, so to speak. And the more it delves into how people actually think – work that naturally originated in psychology rather than economics – we find that people employ heuristics: rules of thumb that do not look at all like optimization.

Assumption: We are Probability Theorists
Behavioral economics recognizes that we operate in an uncertain world, and so assumes people not only act “as if” they optimize, but do so under uncertainty. Things then get really complicated, because we have not only added constraints but also made the problem stochastic.
Heuristics take a different approach to this problem; they overcome the uncertainty by applying coarse and robust rules. They do not try to capture all of the nuances of the possible states and their probabilities. They operate in a different way, unrelated to optimization. They use simple approaches that are robust to changes in states that might randomly occur.
This turns out to be better because it recognizes an important aspect of our environment that cannot be captured even in a model of constrained optimization under uncertainty: There are things that can happen which we cannot anticipate, much less assign a probability to. In such an environment, the best solution is one that is coarse. And, being coarse and robust leads to another anomaly for those who are looking through the optimization lens. In a robust and coarse rule, we will ignore some information, even if it is costless to employ. (This is a point of a paper I co-authored years ago in the Journal of Theoretical Biology, one that, like much of the argument in this post, has been embraced in behavioral ecology while passed over in behavioral economics).
Let's consider environmental context again to see why the apparently rational appeals based on the application of probability theory might be off the mark. At Caltech, Antonio Rangel is looking at how the brain lights up when various problems are posed to subjects. It turns out the problems related to large losses affect different parts of the brain than problems that seem, from a probability standpoint, to be nothing more than a reflection of problems that look at the potential for large gains. This might provide physiological evidence to support the irrationality observed by many in behavioral economists. Or it might be that it demonstrates these apparent biases were wired deep in our evolutionary past, and that they might be what is rational given that past.
Today it is not hard to envision a windfall gain that is similar in magnitude to a large loss. We can hit the lottery; we can build up wealth to last our lifetime. We can do that because of relatively new social and economic structures that allow us to save our wealth, and a legal structure backed up by a police force that gives us confidence that we and our possessions will be around long enough for us to enjoy them.
If we go back far enough, and not so far in terms of evolutionary time, the only good thing that could happen is capturing a large animal, or rebuffing the most recent tribal raids. Anything good was short-term and could easily be reversed. On the other hand, the negative tail was long and ominous. Even short of the not insubstantial risk of losing one's life or that of one's family (and with it one's future support), there was the risk of crippling injury, floods, and any number of other calamities. Include in these a gnawing realization that there were calamities that could not even be envisioned. In that world, it is not surprising that the brain circuitry would be wired differently for gains and losses. In that world, mapping gains and losses with any notion of symmetry is what would be irrational.
This use of robust and information-sparse heuristics again stems from context. We make our decisions in the context of our environment at the time, and our experience with how the world works. In that world, we have to ignore information because much of it is likely to be irrelevant.

Summary
Mathematical optimization can be correct in its purified world and we can be rational in our world, without optimization as the benchmark. It is a truism that if we inhabit a world that fully meets the assumptions of the mathematical problem, it is irrational to deviate from the solution of the mathematical optimization. So either we catalog our irrationality and biases, or we ask why the model is wrong. The invocations of information cost, limited computational ability, missing risk factors are all continually shaving off the edges of the square peg to jam it into the round hole. Maybe the issue is not that we are almost there, and with a little tweaking we can get the optimization approach to work. Rather, logical models may not be the right approach for studying and predicting human behavior.
It deserves repeating that the use of heuristics and the deliberate limits on the use of information as employed in the Gigerenzer worldview are not part of an attempt at optimization, real or “as if”. It is not a matter of starting with optimization and, in some way, determining how to achieve something close to the mathematically optimal solution. It is a different route toward decision making, one that, unfortunately for economists and mathematicians, is most likely the way people actually operate.
Logic, math and probability are all context independent. That is where their power lies; they will work as well on Mars as on Earth. But heuristics can take into account context and norms, an awareness of the environment, and our innate understanding that the world may shift in unanticipated way. As with many new paradigms, the new route to behavioral economics adds a critical part of the world that the old one ignored. Perhaps it was ignored for the same reason physics assumes a perfect vacuum. Or perhaps because the field became overrun with mathematicians, and as Kuhn has said, a new paradigm such as this will only successfully assert itself once the older generation dies off.

Where will Facebook be in ten or fifteen years? In our immediate euphoria, such a long term view may be like taking a good joke too far. But where Facebook is in that long term will say a lot about the nature of society. And, or course, it also will say a lot about how much anyone with a very long view should be willing to pay for Facebook.

The success of Facebook depends on people being willing to eschew privacy, to share their lives, or their lives such as they are in the limited dimensions of the virtual world, with a wide set of people; to have many Facebook friends, to have an interest in the day-to-day world of those friends, to believe in the value of interaction afforded by virtual modes of contact. If people decide to cull back their circle to something that resembles real life and share their lives in more personal and direct ways, Facebook may still exist, but it will not be a potent force.

I am not going to enter the discussion of how secure Facebook's position is, or how much advertising it can generate. Instead, I am going to discuss the implications of Facebook for our individuality as we increasingly embrace Facebook and similar systems that replace real interaction with the virtual, and the implications of this world for the success of Facebook.

The basic point is that either the world changes and Facebook become marginalized, or Facebook continues the thrive and we live in a world of existential alienation. Most of my discussion will be along the lines of those in Jaron Lanier's brilliant book, You Are Not a Gadget. I will use excerpts from the book below.

Crowd Identity and Alienation
It naturally happens that the designs that celebrate the noosphere and other ideals of cybernetic totalism tend to undervalue humans. Examples are the ubiquitous invocations of anonymity and crowd identity – Lanier

The themes of Existentialism are freedom of choice, authenticity, and alienation. These are themes cast aside by the Internet age in general – the cloud, the hive, the redefining of humans as parameters of a database, the programs that confine our imagination – and Facebook as a particular. Existentialism starts at the level of personal meaning rather than general philosophical theory, the person is the active subject rather than a passive spectator. It deals with choice, while the Internet constricts, even dictates, our choices.

Kierkegaard writes extensively about people's desire to meld into the common crowd in the quest to overcome existential anxiety, to be, as Kierkegaard put it, tricked out of one's self by “the others.” He calls the result of this desire leveling. Leveling makes people feel closer and more connected because there is less need to grapple with the uncertainty in interpreting subjective experiences. After all, one way we remain alone is that we cannot know what another person is really seeing or experiencing.

“Melding into the common crowd” has the two operative characteristics of melding and commonality. The melding is a natural force within the social network community, because its whole objective is to allow us to interject ourselves into this huge and ever-present crowd. The commonality of the crowd is another aspect of leveling. If everyone is the same, the uncertainty in knowing what others are experiencing disappears. Heidegger refers to this aspect, the leveling of all differences: “by averageness and leveling down, everything gets obscured, and what has thus been covered up gets passed off as something familiar and accessible to everyone. ...by virtue of an insensitivity to all distinctions in level and genuineness, and in providing average intelligibility, opens up a standard world in which all distinctions between the unique and the general, the superior and the average, the important and the trivial have been leveled”.

The elimination of distinctions comes about inevitably in the digital world because people need to be transformed into standardized dimensions in order to insert themselves into this crowd. Lanier discusses the path to this standardization of identities: “Individual web pages as they first appeared in the early 1990s had the flavor of personhood. MySpace preserved some of that flavor, though a process of regularized formatting had begun. Facebook went further, organizing people into multiple-choice identities. If a church or government were doing these things, it would feel authoritarian, but when technologists are the culprits, we seem hip, fresh, and inventive”.

Marx also had a notion of alienation that provided a background to the most prominent existentialists and that links alienation to subjugation of individuality. The 'materialism' of Marx's philosophy of historical materialism came from Feuerbach, and the 'historical' came from Hegel; the latter overcame the limitations of the former by seizing on historical development to place humans in an active role. But while the Hegelian focus was on the realm of thought, Marx's was on the physical world, the practical sphere. It is in this that Marx was a precursor of Existentialism; one of the first to consider the individual directly rather than as a part of the universal. Not surprisingly, Marx's application of this practical orientation was to labor, which historically was how man interacted with and conceptualized the world.

Marx's focus on alienation in labor led naturally to the the plight of the worker, which then led to the indictment of capitalism, and from there to the solution of communism. We can abstract from the economic system that gave rise to alienation in society, and put the philosophical point more abstractly and with less polarity: in modern society labor became increasingly specialized and this specialization dissociated a person from his essential nature. Marx argued that for the most part, the worker does not engage their human essence, their creativity and ingenuity, their ability to respond to many varying challenges and situations.

A similar alienation occurs due to the computer cloud. We become detached from our essence by the transformation from a person with infinite depth and variation into one that is finite, specified by a multidimensional digital array. The Marxist view is alienation through specialization. In a sense people are turned into a datum, into one dimensional commodities. The Facebook world is not much better than that. In the ironic guise of a social tool, it creates a force for alienation and leveling beyond the dreams of Existentialists of a century ago.

The End of Privacy
The only hope for social networking sites from a business point of view is for a magic formula to appear in which some method of violating privacy and dignity becomes acceptable.– Lanier

Facebook and related sites owe their existence to a willingness for people to give up privacy. In order to meld into the crowd, people send pictures of where they are and give frequent updates of what they are doing. Most people are not exhibitionists, or even if they are now, every social trend, including a trend towards exhibitionism, has a rebound. I think there will be a time when protection of privacy once again becomes the norm, when it will be considered avant garde not to strip away the subjective and complex of the individual and dive into the cloud. At the least, to limit it to a small set of people.

One pressure that will act against the current fashion of casting aside privacy and dignity is that it will dawn on people that the world of Facebook has features of an all seeing Orwellian state, only worse, because rather than a single anonymous entity tracking our actions, we happily and voluntarily contribute, updated intraday, with the singular eye of the state replaced by the many eyes of the anonymous cloud. And rather than only tracking what we are doing and where we are, we throw in our preferences and our thoughts for free. I am surprised that repressive regimes do not seize on this tool rather than suppress it.

Replacing the Real with the Fictional
The most effective young Facebook users, the ones who will probably be winners if Facebook turns out to be a model of the future they will inhabit as adults, are the ones who create successful online fictions about themselves.– Lanier

The solution to the loss of privacy is to hold back the real and push forward a fictionalized version of the self into the cloud. This is the only way to meld into the crowd and still preserve individual identity. Fortunately, even as Facebook reduces individualism by holding the subjective from display, it also allows us to create such self-designed fictions. Toward the terminus of his life, Kierkegaard stopped going to church, saying that he no longer wanted to participate in “making a fool of God.” Here we make a fool of people.

Prognosis
So my bet – a long term bet because it will take the force of cultural change to accomplish – is that Facebook will become marginalized. It will not disappear, it will remain a repository for factoids about one's collection of friends, but the reality of what Facebook friends really are will become evident, as will the effects of standardization of the individual, the cost to individuality of giving up privacy, and the frustration with having Facebook friends that are increasingly fictionalized and flattened versions of their real selves.

Postscript: I joined Facebook a few years ago because some people sent me e-mails from their Facebook accounts asking to be my friend. So I signed up and befriended them all. I haven't received any new friend requests for the past year. I thought no one wanted to be my friend anymore, until I recently checked my privacy settings and discovered no one could search for my account.