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It takes you 500,000 microseconds just to click a mouse. But if you’re a Wall Street algorithm and you’re five microseconds behind, you’re a loser.” ~ Kevin Slavin.

TED video lecture – Kevin Slavin (link) argues that we’re living in a world designed for – and increasingly controlled by – algorithms. In this riveting talk from TEDGlobal, he shows how these complex computer programs determine: espionage tactics, stock prices, movie scripts, and architecture. And he warns that we are writing code we can’t understand, with implications we can’t control. Kevin Slavin navigates in the “algoworld“, the expanding space in our lives that’s determined and run by algorithms (link at TED).

Video Documentary – Code Rush (, produced in 2000 and broadcast on PBS, is an inside look at living and working in Silicon Valley at the height of the dot-com era. The film follows a group of Netscape engineers as they pursue at that time a revolutionary venture to save their company – giving away the software recipe for Netscape’s browser in exchange for integrating improvements created by outside software developers.

” (…) code (…) Why is it important for the world? Because it’s the blood of the organism that is our culture, now. It’s what makes everything go.“, Jamie Zawinski, Code Rush, 2000.

The year is early 1998, at the height of dot-com era, and a small team of Netscape code writers frantically works to reconstruct the company’s Internet browser. In doing so they will rewrite the rules of software development by giving away the recipe for its browser in exchange for integrating improvements created by outside unpaid developers.  The fate of the entire company may well rest on their shoulders. Broadcast on PBS, the film capture the human and technological dramas that unfold in the collision between science, engineering, code, and commerce.

Fig. – A Symbolical Head (phrenological chart) illustrating the natural language of the faculties. At the Society pages / Economic Sociology web page.

You have much probably noticed by now how is emerging as a powerful platform for those collecting interesting research papers. There are several good examples, but let me stress one entitled “Bounded Rationality and Beyond” ( web page) curated by Alessandro Cerboni (blog). On a difficult research theme, Alessandro is doing a great job collecting nice essays and wonderful articles, whenever he founds them. One of those articles I really appreciated was John Conlisk‘s “Why Bounded Rationality?“, delivering into the field several important clues, for those who (like me) work in the area. What follows, is an excerpt from the article as well as part of his introductory section. The full (PDF) paper could be retrieved here:

In this survey, four reasons are given for incorporating bounded rationality in economic models. First, there is abundant empirical evidence that it is important. Second, models of bounded rationality have proved themselves in a wide range of impressive work. Third, the standard justifications for assuming unbounded rationality are unconvincing; their logic cuts both ways. Fourth, deliberation about an economic decision is a costly activity, and good economics requires that we entertain all costs. These four reasons, or categories of reasons, are developed in the following four sections. Deliberation cost will be a recurring theme.

Why bounded rationality? In four words (one for each section above): evidence, success, methodology, and scarcity. In more words: Psychology and economics provide wide-ranging evidence that bounded rationality is important (Section I). Economists who include bounds on rationality in their models have excellent success in describing economic behavior beyond the coverage of standard theory (Section II). The traditional appeals to economic methodology cut both ways; the conditions of a particular context may favor either bounded or unbounded rationality (Section III). Models of bounded rationality adhere to a fundamental tenet of economics, respect for scarcity. Human cognition, as a scarce resource, should be treated as such (Section IV). The survey stresses throughout that an appropriate rationality assumption is not something to decide once for all contexts. In principle, we might suppose there is an encompassing single theory which takes various forms of bounded and unbounded rationality as special. cases. As with other model ingredients, however, we in practice want to work directly with the most convenient special case which does justice to the context. The evidence and models surveyed suggest that a sensible rationality assumption will vary by context, depending on such conditions as deliberation cost, complexity, incentives, experience, and market discipline. Beyond the four reasons given, there is one more reason for studying bounded rationality. It is simply a fascinating thing to do. We can mix some Puck with our Hamlet.

Photo – The Aftermath Network research group: Manuel Castells, Terhi Rantanen, Michel Wieviorka, Sarah Banet-Weiser, Rosalind Williams, John Thompson, Gustavo Cardoso, Pekka Himanen, You-Tien Hsing, Ernesto Ottone, João Caraça and Craig Calhoun.

Oh!… nostalgia. But can you read between the lines? Could you perceive the cynical TV ads. The underlying media mantra that you are not being productive enough. That is you, ultimately the reason for the global crisis. That ‘something‘ went broken. Are you having a feeling that all this mess could give rise to National Socialism, again? That, reversed nostalgia plays a role too?! Well, … shortly after the beginning of the financial crisis of 2008 sociologist Manuel Castells gathered a small group of international top intellectuals to ponder the crisis. While the crisis expanded, Castells named his group ‘The Aftermath Network‘, a direct reference to the new world which according to him will emerge from the ashes of the crisis.

Under the venue and patronage of Calouste Gulbenkian Foundation, Lisbon-Portugal, Castell‘s multidisciplinary research group meet every year with the aim of discussing in real time and from different angles the societal and cultural consequences of the worldwide economic collapse. Now, thanks to the Dutch VPRO Backlight, a new documentary has been produced (uploaded last week over YouTube), reflecting part of those meetings. Entitled ‘Aftermath of a Crisis‘ (above) is a 48 minute documentary reporting the world incertitude, facing a global fallacy, as well as the emergence of new social movements and protests in Spain, Greece, Portugal and London. Unfortunately, as I said the other day (link), there are increasing signs that: Keynesianism is now Bankism. Know what? Next time someone or some institution comes to you covered by a veil of nostalgia, even a thin one, do yourself a favor: put your brain in maximum alert.

Book cover from Economics Nobel prize (2008), Paul Krugman (link): Paul R. Krugman, “The Self-Organizing Economy“, Cambridge, Massachusetts, and Oxford: Blackwell Publishers, 1996. What follows is the entire excerpt review on his book, by Cosma Shalizi, a friend and colleague, done in March 1996 with minor corrections in 1997 and 2006:

[…] Paul Krugman cannot be accused of lacking good opening lines:

    Is an economic slump like a hurricane, or is it more like an earthquake? Is a growing city like an embryo, or is it more like a meteorite?

Obviously some explaining needs to be done here.

The term “self-organization” seems to have entered the language in a 1947 paper in the Journal of General Psychology on cybernetic mechanisms of adaptation, though related ideas are considerably older. It has, of course, become a buzzword, indeed an indispensable element in modern techno-cant – I was once on a mailing list where some people proposed to write a “self-organizing” novel – but a lot of real science carries on under the label, in some remarkably different fields:

    [W]hat links the study of embryos and hurricanes, of magnetic materials and collections of neurons, is that they are all self-organizing systems: systems that, even when they start from an almost homogeneous or almost random state, spontaneously form large-scale patterns. One day the air over a particular patch of tropical ocean is no different in behavior from the air over any other patch; maybe the pressure is a bit lower, but the difference is nothing dramatic. Over the course of the next few days, however, that slight dip in pressure becomes magnified through a process of self-reinforcement: rising air pulls water up to an altitude at which it condenses, releasing heat that reduces the pressure further and makes more air rise, until that particular piece of the atmosphere has become a huge, spinning vortex. Early in the process of growth an embryo is a collection of nearly identical cells, but (or at least so many biologists believe) these cells communicate with each other through subtle chemical signals that reinforce and inhibit each other, leading to the “decision” of some cells to become parts of a wing, others parts of a leg. [pp. 3–4]

This is vague, for which I am grateful, since sharpening the notion of self-organization into something quantifiable is the subject of my thesis. But let us draw a veil over this and press on.

There’s a sense in which economists have been studying little but the “spontaneous formation of large-scale patterns” ever since Adam Smith and the creation of self-regulating markets, but Krugman is not interested in convincing his profession that it has been speaking prose all its life; it would, in his words, “be entitled to change the channel.” Rather he wants to look at the way economies organize themselves in space and over time, which they do in a most conspicuous way. (There is, however, a brief discussion of technological lock-in in chapter six.) Krugman picks out three examples in particular: the way cities differentiate themselves into specialized districts; the power-law distribution of city sizes; and business cycles.

That cities – even Los Angeles – are not homogenous lumps, with everything mixed together, seems to have been true from earliest times. Some of this is simply because different locations have different advantages – dockyards go by the water, fortresses on heights, and brothels and bars near fortresses. Some of it is due to zoning boards, planning commissions, real-estate magnates and red-lining, to say nothing of the police and cross-burning – whether such forces contribute to urban self-organization is a delicate question, and in any case Krugman is silent about them. Still, this leaves a lot of differentiation which seems to be due to nothing but self-reinforcement, which (unlike zoning boards and red-lining) has actually been studied in economic theory, especially by economic geographers, for some time. (Krugman is at pains to point out that self-organization was not unknown to economists before the arrival of missionaries from Santa Fe.) He begins his discussion of this with so-called “edge cities,” and then passes on to a marvelously elegant illustration from Thomas Schelling’s marvelously elegant book, Micromotives and Macrobehavior, which suggests how the former (requiring that at least 37% of your neighbors be like yourself) can lead to the latter (massive segregation). He then dives into a discussion of “urban morphogenesis” directly inspired by Turing’s classic work on embryological morphogenesis. He assumes his city is one-dimensional and either infinite or circular, but claims no more value for it than that of qualitative illustration; I can think of physicists who should be so modest. Self-organization happens here because the initial random noise contains components which correspond to many different patterns in nucleo, and the dynamics are such that some of these get magnified faster than others. The pattern which grows fastest ultimately dominates the system, which is called “pattern selection” in traditional reaction-diffusion systems. [Note containing the words “Fourier decomposition.”]

A power law distribution means that the number of objects whose size is at least S is proportional to S^a, for some (hopefully negative) constant a. It happens that the size of cities obeys a power law known as Zipf’s law, which is usually stated thus: the size of a city is inversely proportional to its rank order so that, for example, the 100th largest city is a tenth the size of the 10th largest city. This rule is almost exactly true of the sizes of American cities (it corresponds to a value of a of -2), and has been for at least a century. Physicists have liked power laws ever since Galileo, and recently we’ve developed a taste for power law distributions; Prof. Per Bak and his disciples sometimes seem to want to claim everything obeying a power law distribution for “self-organized criticality.” Krugman explains the power law distribution as an outcome of growth processes where the expected rate of growth is independent of the size already attained. Such processes do, in fact, generate power laws, and have been known to for some time – Herbert Simon proposed one, “in a completely impenetrable exposition,” in 1955. Alas, none of them are as regular as the empirical data!

At this point Krugman tells us that what we have just seen are order from instability (“When a system is so constituted that a flat or disordered structure is unstable, order spontaneously emerges.” – p. 99) and order from random growth (“[O]bjects are formed by a growth process in which the expected rate of growth is approximately independent of scale, but the actual rate of growth is random.” – p. 100). He declines, thankfully, to call these universal laws of self-organization, but he does suggest they are “principles,” or rather common ways of self-organizing.

Temporal self-organization in the economy is more familiarly known as business cycles, or yet more familiarly as booms and crashes (err, depressions; err, recessions; err, slumps; err, slow-downs). Since Keynes (at least) the idea that these are in some way self-reinforcing has been common, and Krugman resurrects a body of Keynesian theory from the ’50s, “non-linear business cycle theory.” This is of the order-from-instability type, and so predicts a characteristic size to business cycles, which, on a comparison of 1933 with the recent unpleasantness, or even the early 1980s, is less than plausible. Krugman also presents an order-from-random-growth theory – really percolation theory in wolf’s clothing – which avoids that problem at the cost of “[making] less contact with what seems to happen during a boom or slump,” and predicting a power law distribution for business fluctuations, which is not observed. Charitably, Krugman chooses to “regard them both more as illustrations as how one might approach self-organization in time than as finished statements of how one actually ought to do it.” Some such theory will be necessary if we are not to continue treating shifts in aggregate demand as external shocks administered, perhaps, by the vengeful specter of Karl Marx.

If this were a formal and comprehensive treatise, I would be disappointed by the passing over of evolutionary and institutional economics; the cavalier starting of models from tabulæ rasæ rather than already-differentiated settings; the fact that most of the models are what in physics would be called “phenomenological,” i.e. they don’t try to connect to the underlying mechanisms, such as markets; the absence of even qualitative comparisons with empirical data; and the indifference to exogenous forces, natural , social or political, which in practice are very important in all of the topics Krugman discusses. But this is not a formal and comprehensive work; that will have to wait for a good many years. It is a self-described “discourse” of exactly a hundred pages, a very brief introduction and an appeal for further development, for the work which will make the treatise possible. As befits such a book, Krugman’s writing is clear, informal and concise (but then, it usually is). His attitude towards the mathematics is that it should be used and not seen; accordingly we get the hypotheses once as stories (“I do not want to dignify them by calling them models”); a second time with a bit of calculus; and a third time in an appendix for those who want the nitty-gritty. (Even there he draws the line at Fourier decomposition and linear stability analysis; phase space and attractors are explained verbally, and well, in the body of the text.) The economics should be accessible to anyone who’s taken Econ. 1, and probably many (such as your humble narrator) who haven’t. The book will be of particular interest to those crossing the bridge from economics to self-organization and dynamics in either direction, but most educated readers should find it informative and engaging. […] Cosma S. Shalizi, 1996.

Video – A 1964 film based on the novel Zorba the Greek by Nikos Kazantzakis. The film was directed by Michael Cacoyannis and the title character was played by Anthony Quinn. The supporting cast included Alan Bates as a visiting Englishman as well as Irene Papas. The theme, “Sirtaki” by Mikis Theodorakis, has become famous and popular as a song and as a dance. The movie was shot on location on the Greek island of Crete. Specific places featured include the town of Chania, the Apokoronas region and the Akrotiri peninsula. The famous scene, in which Quinn’s character dances the Sirtaki, was shot on the beach of the village of Stavros. (from YouTube)

Basil (Alan Bates), a young English writer, meets a free-spirited Greek peasant named Zorba (Anthony Quinn) while waiting to travel to the island of Crete. While Zorba pursues a relationship with aging French courtesan Madame Hortense, Basil attempts to court a young widow. Along the way, he learns valuable life lessons from the earthy Zorba, who has an unquenchable joie de vivre (link):

[…] Basil: I don’t want any trouble. Alexis Zorba: Life is trouble. Only death is not. To be alive is to undo your belt and look for trouble. […] Zorba: Damn it boss, I like you too much not to say it. You’ve got everthing except one thing: madness! A man needs a little madness, or else… Basil: Or else? Zorba: …he never dares cut the rope and be free. […] Basil: Teach me to dance, will you? Zorba: Dance? Did you say… dance?! … Come on my boy… together… Let’s go… hop … Again… hop … […] Zorba: Boss, I have so much to tell you, … I never had loved a man like you … […] Zorba: Hey boss, did you ever see a more splendiferous crash?! … Oh, … You can laugh too!… hmmm… Hey!… You laugh! […]

Figure – Poker final hand rankings. Poker is a typical example of bounded rationality in our daily lives. Without having all the information available, you still have to make a decision. In one of his works, Herbert Simon states: “boundedly rational agents experience limits in formulating and solving complex problems and in processing (receiving, storing, retrieving, transmitting) information“.

[…] Bounded rationality is the idea that in decision making, rationality of individuals is limited by the information they have, the cognitive limitations of their minds, and the finite amount of time they have to make decisions. It was proposed by Herbert Simon as an alternative basis for the mathematical modelling of decision making, as used in economics and related disciplines; it complements rationality as optimization, which views decision making as a fully rational process of finding an optimal choice given the information available. Another way to look at bounded rationality is that, because decision-makers lack the ability and resources to arrive at the optimal solution, they instead apply their rationality only after having greatly simplified the choices available. Thus the decision-maker is a satisfier, one seeking a satisfactory solution rather than the optimal one. Simon used the analogy of a pair of scissors, where one blade is the “cognitive limitations” of actual humans and the other the “structures of the environment”; minds with limited cognitive resources can thus be successful by exploiting pre-existing structure and regularity in the environment. Some models of human behaviour in the social sciences assume that humans can be reasonably approximated or described as “rational” entities (see for example rational choice theory). Many economics models assume that people are on average rational, and can in large enough quantities be approximated to act according to their preferences. The concept of bounded rationality revises this assumption to account for the fact that perfectly rational decisions are often not feasible in practice due to the finite computational resources available for making them. […] In Wikipedia, (link).

Book cover – Herbert A. Simon. Models of Bounded Rationality, Volume 1, Economic Analysis and Public Policy, MIT Press 1984. The Nobel Prize in Economics was awarded to Herbert Simon in 1978. At Carnegie-Mellon University he holds the title of Professor of Computer Science and Psychology. These two facts together delineate the range and uniqueness of his contributions in creating meaningful interactions among fields that developed in isolation but that are all concerned with human decision-making and problem-solving processes. In particular, Simon has brought the insights of decision theory, organization theory (especially as it applies to the business firm), behavior modeling, cognitive psychology, and the study of artificial intelligence to bear on economic questions. This has led not only to new conceptual dimensions for theoretical constructions, but also to a new humanizing realism in economics, a way of taking into account and dealing with human behavior and interactions that lie at the root of all economic activity. The sixty papers and essays contained in these two volumes are grouped under eight sections, each with a brief introductory essay. These are: Some Questions of Public Policy, Dynamic Programming Under Uncertainty; Technological Change; The Structure of Economic Systems; The Business Firm as an Organization; The Economics of Information Processing; Economics and Psychology; and Substantive and Procedural Reality. Most of Simon’s papers on classical and neoclassical economic theory are contained in volume one. The second volume collects his papers on behavioral theory, with some overlap between the two volumes. (from MIT).

(pic. – click to enlarge) Summer time in here, you know?! So, this will be my next T-shirt: “First, the Economy took over Politics. Now, Finance took over Economy. Bit by bit, planet Earth bounds to be a giant speculation machine“. @ViRAms April 28 2011 (link).

Video lecture by Ken Long (at the Statistics Problem Solvers blog) on Nassim Taleb‘s 4th Quadrant problems [1,2], i.e. a region where statistics not only don’t work but in which statistics are downright dangerous, because they lead you to make predictions as well as control systems that are unprepared for the kinds of systems shocks awaiting you.

Statistical and applied probabilistic knowledge is the core of knowledge; statistics is what tells you if something is true, false, or merely anecdotal; it is the “logic of science”; it is the instrument of risk-taking; it is the applied tools of epistemology; you can’t be a modern intellectual and not think probabilistically—but… let’s not be suckers. The problem is much more complicated than it seems to the casual, mechanistic user who picked it up in graduate school. Statistics can fool you. In fact it is fooling your government right now. It can even bankrupt the system (let’s face it: use of probabilistic methods for the estimation of risks did just blow up the banking system).”, Nassim Taleb, in [1].

[1] Nassim Nicholas Taleb, “The Fourth Quadrant: A Map of the Limits of Statistics“, An Edge Original Essay, Set., 2008. (link)

[2] Nassim Nicholas Taleb,”Convexity, Robustness, and Model Error inside the Fourth Quadrant“, Oxford Lecture (Draft version), Oxford, July 2010. [PDF paper]

Animated Video – Lively RSA Animate [April 2010], adapted from Dan Pink‘s talk at the RSA (below), illustrates the hidden truths behind what really motivates us at home and in the workplace. [Inspired from the work of Economics professor Dan Ariely at MIT along with his colleagues].

What drives us? Some quotes: […] Once the task called for even rudimentary COGNITIVE skills a larger reward led to poorer performance […] Once you get above rudimentary cognitive skills, rewards do not work that way [linear], this defies the laws of behavioural physics ! […] But when a task gets more complicated, it requires some conceptual, creative thinking, these kind of motivators do not work any more […] Higher incentives led to worse performance. […] Fact: Money is a motivator. In a strange way. If you don’t pay enough, people won’t be motivated. But now there is another paradox. The best use of money, and that is: pay people enough to take the issue of money off the table. […] …Socialism…??

[…] Most upper-management and sales force personnel, as well as workers in many other jobs, are paid based on performance, which is widely perceived as motivating effort and enhancing productivity relative to non-contingent pay schemes. However, psychological research suggests that excessive rewards can in some cases produce supra-optimal motivation, resulting in a decline in performance. To test whether very high monetary rewards can decrease performance, we conducted a set of experiments at MIT, the University of Chicago, and rural India. Subjects in our experiment worked on different tasks and received performance-contingent payments that varied in amount from small to large relative to their typical levels of pay. With some important exceptions, we observed that high reward levels can have detrimental effects on performance. […] abstract, Dan Ariely, Uri Gneezy, George Loewenstein, and Nina Mazar, “Large Stakes and Big Mistakes“, Federal Reserve Bank of Boston Working paper no. 05-11, Research Center for Behavioral Economics and Decision-Making, US, July 2005. [PDF available here] (improved 2009 version below)

Video lecture – On the surprising science of motivation: analyst Daniel Pink examines the puzzle of motivation [Jul. 2009], starting with a fact that social scientists know but most managers don’t: Traditional rewards aren’t always as effective as we think. So maybe, there is a different way forward. [Inspired from the work of Economics professor Dan Ariely at MIT along with his colleagues].

[…] Payment-based performance is commonplace across many jobs in the marketplace. Many, if not most upper-management, sales force personnel, and workers in a wide variety of other jobs are rewarded for their effort based on observed measures of performance. The intuitive logic for performance-based compensation is to motivate individuals to increase their effort, and hence their output, and indeed there is some evidence that payment for performance can increase performance (Lazear, 2000). The expectation that increasing performance-contingent incentives will improve performance rests on two subsidiary assumptions: (1) that increasing performance-contingent incentives will lead to greater motivation and effort and (2) that this increase in motivation and effort will result in improved performance. The first assumption that transitory performance-based increases in pay will produce increased motivation and effort is generally accepted, although there are some notable exceptions. Gneezy and Rustichini (2000a), for example, have documented situations, both in laboratory and field experiments, in which people who were not paid at all exerted greater effort than those who were paid a small amount (see also Gneezy and Rustichini, 2000b; Frey and Jegen, 2001; Heyman and Ariely, 2004). These results show that in some situations paying a small amount in comparison to paying nothing seems to change the perceived nature of the task, which, if the amount of pay is not substantial, may result in a decline of motivation and effort.

Another situation in which effort may not respond in the expected fashion to a change in transitory wages is when workers have an earnings target that they apply narrowly. For example, Camerer, Babcock, Loewenstein and Thaler (1997) found that New York City cab drivers quit early on days when their hourly earnings were high and worked longer hours when their earnings were low. The authors speculated that the cab drivers may have had a daily earnings target beyond which their motivation to continue working dropped off. Although there appear to be exceptions to the generality of the positive relationship between pay and effort, our focus in this paper is on the second assumption – that an increase in motivation and effort will result in improved performance. The experiments we report address the question of whether increased effort necessarily leads to improved performance. Providing subjects with different levels of incentives, including incentives that were very high relative to their normal income, we examine whether, across a variety of different tasks, an increase in contingent pay leads to an improvement or decline in performance. We find that in some cases, and in fact most of the cases we examined, very high incentives result in a decrease in performance. These results provide a counterexample to the assumption that an increase in motivation and effort will always result in improved performance. […] in Dan Ariely, Uri Gneezy, George Loewenstein, and Nina Mazar, “Large Stakes and Big Mistakes“, Review of Economic Studies (2009) 75, 1-19 0034-6527/09. [PDF available here]

Now, these are not stories, these are facts. These are one of the most robust findings in social science,… yet, one of the most ignored [sic]. And they keep coming in. Such as the fallacy of the supply and demand model (March 2008). Anyway, enough good material (a simple paper with profound implications)… for one day. But hey, …Oh, if you are still wondering what other paper inspired the specific drawings at minute 7′:40” and on, in the first video over this post, well, here it is: Kristina Shampan’er and Dan Ariely (2007), “How Small is Zero Price? The True Value of Free Products“, in Marketing Science. Vol. 26, No. 6, 742 – 757. [PDF available here]… Got it ?!

Book – Karl Sigmund, The Calculus of Selfishness, Princeton Series on Theoretical and Computational Biology, Princeton University Press,  ISBN: 978-1-4008-3225-5, 192 pp., 2009.

[…] Cooperation means that a donor pays a cost, c, for a recipient to get a benefit, b. In evolutionary biology, cost and benefit are measured in terms of fitness. While mutation and selection represent the main forces of evolutionary dynamics, cooperation is a fundamental principle that is required for every level of biological organization. Individual cells rely on cooperation among their components. Multicellular organisms exist because of cooperation among their cells. Social insects are masters of cooperation. Most aspects of human society are based on mechanisms that promote cooperation. Whenever evolution constructs something entirely new (such as multicellularity or human language), cooperation is needed. Evolutionary construction is based on cooperation. The five rules for cooperation which we examine in this chapter are: kin selection, direct reciprocity, indirect reciprocity, graph selection, and group selection. Each of these can promote cooperation if specific conditions are fulfilled. […], Martin A. Nowak, Karl Sigmund, How populations cohere: five rules for cooperation, in R. M. May and A. McLean (eds.) Theoretical Ecology: Principles and Applications, Oxford UP, Oxford (2007), 7-16. [PDF]

How does cooperation emerge among selfish individuals? When do people share resources, punish those they consider unfair, and engage in joint enterprises? These questions fascinate philosophers, biologists, and economists alike, for the “invisible hand” that should turn selfish efforts into public benefit is not always at work. The Calculus of Selfishness looks at social dilemmas where cooperative motivations are subverted and self-interest becomes self-defeating. Karl Sigmund, a pioneer in evolutionary game theory, uses simple and well-known game theory models to examine the foundations of collective action and the effects of reciprocity and reputation. Focusing on some of the best-known social and economic experiments, including games such as the Prisoner’s Dilemma, Trust, Ultimatum, Snowdrift, and Public Good, Sigmund explores the conditions leading to cooperative strategies. His approach is based on evolutionary game dynamics, applied to deterministic and probabilistic models of economic interactions. Exploring basic strategic interactions among individuals guided by self-interest and caught in social traps, The Calculus of Selfishness analyses to what extent one key facet of human nature–selfishness–can lead to cooperation. (from Princeton Press). [Karl Sigmund, The Calculus of Selfishness, Princeton Series on Theoretical and Computational Biology, Princeton University Press,  ISBN: 978-1-4008-3225-5, 192 pp., 2009.]

What follows comes partly from chapter 1, available here:

THE SOCIAL ANIMAL: Aristotle classified humans as social animals, along with other species, such as ants and bees. Since then, countless authors have compared cities or states with bee hives and ant hills: for instance, Bernard de Mandeville, who published his The Fable of the Bees more than three hundred years ago. Today, we know that the parallels between human communities and insect states do not reach very far. The amazing degree of cooperation found among social insects is essentially due to the strong family ties within ant hills or bee hives. Humans, by contrast, often collaborate with non-related partners. Cooperation among close relatives is explained by kin selection. Genes for helping offspring are obviously favouring their own transmission. Genes for helping brothers and sisters can also favour their own transmission, not through direct descendants, but indirectly, through the siblings’ descendants: indeed, close relatives are highly likely to also carry these genes. In a bee hive, all workers are sisters and the queen is their mother. It may happen that the queen had several mates, and then the average relatedness is reduced; the theory of kin selection has its share of complex and controversial issues. But family ties go a long way to explain collaboration. The bee-hive can be viewed as a watered-down version of a multicellular organism. All the body cells of such an organism carry the same genes, but the body cells do not reproduce directly, any more than the sterile worker-bees do. The body cells collaborate to transmit copies of their genes through the germ cells – the eggs and sperm of their organism. Viewing human societies as multi-cellular organisms working to one purpose is misleading. Most humans tend to reproduce themselves. Plenty of collaboration takes place between non-relatives. And while we certainly have been selected for living in groups (our ancestors may have done so for thirty million years), our actions are not as coordinated as those of liver cells, nor as hard-wired as those of social insects. Human cooperation is frequently based on individual decisions guided by personal interests. Our communities are no super-organisms. Former Prime Minister Margaret Thatcher pithily claimed that “there is no such thing as society“. This can serve as the rallying cry of methodological individualism – a research program aiming to explain collective phenomena bottom-up, by the interactions of the individuals involved. The mathematical tool for this program is game theory. All “players” have their own aims. The resulting outcome can be vastly different from any of these aims, of course.

THE INVISIBLE HAND: If the end result depends on the decisions of several, possibly many individuals having distinct, possibly opposite interests, then all seems set to produce a cacophony of conflicts. In his Leviathan from 1651, Hobbes claimed that selfish urgings lead to “such a war as is every man against every man“. In the absence of a central authority suppressing these conflicts, human life is “solitary, poor, nasty, brutish, and short“. His French contemporary Pascal held an equally pessimistic view: : “We are born unfair; for everyone inclines towards himself…. The tendency towards oneself is the origin of every disorder in war, polity, economy etc“. Selfishness was depicted as the root of all evil. But one century later, Adam Smith offered another view.An invisible hand harmonizes the selfish efforts of individuals: by striving to maximize their own revenue, they maximize the total good. The selfish person works inadvertently for the public benefit. “By pursuing his own interest he frequently promotes that of the society more effectually than when he really intends to promote it“. Greed promotes behaviour beneficial to others. “It is not from the benevolence of the butcher, the brewer, or the baker, that we expect our dinner, but from their regard to their own self-interest. We address ourselves, not to their humanity but to their self-love, and never talk to them of our own necessities but of their advantages“. A similar view had been expressed, well before Adam Smith, by Voltaire in his Lettres philosophiques: “Assuredly, God could have created beings uniquely interested in the welfare of others. In that case, traders would have been to India by charity, and the mason would saw stones to please his neighbour. But God designed things otherwise….It is through our mutual needs that we are useful to the human species; this is the grounding of every trade; it is the eternal link between men“. Adam Smith (who knew Voltaire well) was not blind to the fact that the invisible hand is not always at work. He merely claimed that it frequently promotes the interest of the society, not that it always does. Today, we know that there are many situations – so-called social dilemmas – where the invisible hand fails to turn self-interest to everyone’s advantage.

Bluffing poster

On Bilateral Monopolies: […] Mary has the world’s only apple, worth fifty cents to her. John is the world’s only customer for the apple, worth a dollar to him. Mary has a monopoly on selling apples, John has a monopoly (technically, a monopsony, a buying monopoly) on buying apples. Economists describe such a situation as bilateral monopoly. What happens? Mary announces that her price is ninety cents, and if John will not pay it, she will eat the apple herself. If John believes her, he pays. Ninety cents for an apple he values at a dollar is not much of a deal but better than no apple. If, however, John announces that his maximum price is sixty cents and Mary believes him, the same logic holds. Mary accepts his price, and he gets most of the benefit from the trade. This is not a fixed-sum game. If John buys the apple from Mary, the sum of their gains is fifty cents, with the division determined by the price. If they fail to reach an agreement, the summed gain is zero. Each is using the threat of the zero outcome to try to force a fifty cent outcome as favorable to himself as possible. How successful each is depends in part on how convincingly he can commit himself, how well he can persuade the other that if he doesn’t get his way the deal will fall through. Every parent is familiar with a different example of the same game. A small child wants to get her way and will throw a tantrum if she doesn’t. The tantrum itself does her no good, since if she throws it you will refuse to do what she wants and send her to bed without dessert. But since the tantrum imposes substantial costs on you as well as on her, especially if it happens in the middle of your dinner party, it may be a sufficiently effective threat to get her at least part of what she wants. Prospective parents resolve never to give in to such threats and think they will succeed. They are wrong. You may have thought out the logic of bilateral monopoly better than your child, but she has hundreds of millions of years of evolution on her side, during which offspring who succeeded in making parents do what they want, and thus getting a larger share of parental resources devoted to them, were more likely to survive to pass on their genes to the next generation of offspring. Her commitment strategy is hardwired into her; if you call her bluff, you will frequently find that it is not a bluff. If you win more than half the games and only rarely end up with a bargaining breakdown and a tantrum, consider yourself lucky.

Herman Kahn, a writer who specialized in thinking and writing about unfashionable topics such as thermonuclear war, came up with yet another variant of the game: the Doomsday Machine. The idea was for the United States to bury lots of very dirty thermonuclear weapons under the Rocky Mountains, enough so that if they went off, their fallout would kill everyone on earth. The bombs would be attached to a fancy Geiger counter rigged to set them off if it sensed the fallout from a Russian nuclear attack. Once the Russians know we have a Doomsday Machine we are safe from attack and can safely scrap the rest of our nuclear arsenal. The idea provided the central plot device for the movie Doctor Strangelove. The Russians build a Doomsday Machine but imprudently postpone the announcement they are waiting for the premier’s birthday until just after an American Air Force officer has launched a unilateral nuclear attack on his own initiative. The mad scientist villain was presumably intended as a parody of Kahn. Kahn described a Doomsday Machine not because he thought we should build one but because he thought we already had. So had the Russians. Our nuclear arsenal and theirs were Doomsday Machines with human triggers. Once the Russians have attacked, retaliating does us no good just as, once you have finally told your daughter that she is going to bed, throwing a tantrum does her no good. But our military, knowing that the enemy has just killed most of their friends and relations, will retaliate anyway, and the knowledge that they will retaliate is a good reason for the Russians not to attack, just as the knowledge that your daughter will throw a tantrum is a good reason to let her stay up until the party is over. Fortunately, the real-world Doomsday Machines worked, with the result that neither was ever used.

Friedman's Law's Order book

For a final example, consider someone who is big, strong, and likes to get his own way. He adopts a policy of beating up anyone who does things he doesn’t like, such as paying attention to a girl he is dating or expressing insufficient deference to his views on baseball. He commits himself to that policy by persuading himself that only sissies let themselves get pushed around and that not doing what he wants counts as pushing him around. Beating someone up is costly; he might get hurt and he might end up in jail. But as long as everyone knows he is committed to that strategy, other people don’t cross him and he doesn’t have to beat them up. Think of the bully as a Doomsday Machine on an individual level. His strategy works as long as only one person is playing it. One day he sits down at a bar and starts discussing baseball with a stranger also big, strong, and committed to the same strategy. The stranger fails to show adequate deference to his opinions. When it is over, one of the two is lying dead on the floor, and the other is standing there with a broken beer bottle in his hand and a dazed expression on his face, wondering what happens next. The Doomsday Machine just went off. With only one bully the strategy is profitable: Other people do what you want and you never have to carry through on your commitment. With lots of bullies it is unprofitable: You frequently get into fights and soon end up either dead or in jail. As long as the number of bullies is low enough so that the gain of usually getting what you want is larger than the cost of occasionally having to pay for it, the strategy is profitable and the number of people adopting it increases. Equilibrium is reached when gain and loss just balance, making each of the alternative strategies, bully or pushover, equally attractive. The analysis becomes more complicated if we add additional strategies, but the logic of the situation remains the same.

This particular example of bilateral monopoly is relevant to one of the central disputes over criminal law in general and the death penalty in particular: Do penalties deter? One reason to think they might not is that the sort of crime I have just described, a barroom brawl ending in a killing more generally, a crime of passion seems to be an irrational act, one the perpetrator regrets as soon as it happens. How then can it be deterred by punishment? The economist’s answer is that the brawl was not chosen rationally but the strategy that led to it was. The higher the penalty for such acts, the less profitable the bully strategy. The result will be fewer bullies, fewer barroom brawls, and fewer “irrational” killings. How much deterrence that implies is an empirical question, but thinking through the logic of bilateral monopoly shows us why crimes of passion are not necessarily undeterrable. […]

in Chapter 8, David D. Friedman, “Law’s Order: What Economics Has to Do With Law and Why it Matters“, Princeton University Press, Princeton, New Jersey, 2000.

Note – Further reading should include David D. Friedman’s “Price Theory and Hidden Order“. Also, a more extensive treatment could be found on “Game Theory and the Law“, by Douglas G. Baird, Robert H. Gertner and Randal C. Picker, Cambridge, Mass: Harvard University Press, 1994.

Last year, at the beginning of October I decided to dedicate my second post on financial markets (I, II) to Black Swans. Swans are beautiful animals, but while white swans are vulgar and omnipresent at every pond, black swans are rare! Meanwhile, 2 days ago (June 1) the Wall Street Journal comes with this very awkward – and by all means for that precise reason – interesting article written by journalist Scott Patterson, where Mr. Taleb’s name pops-up again (image below).

Well, … let’s face it: you could put your money in the bank and have – let’s say – a 3% revenue at the end of your fiscal year. Or you could apply it to raise a new fancy gourmet restaurant at your local vicinity. Restaurants and local food stores are known to have 5-7% revenues in one year, not to speak on the immense burden they represent as well as for some associated risks – specially these days. But then you may think – better than banks, right? Right! Or, just to give you another example on this increasing scale – raising a little bit the risk -, on the other hand you could apply your money in stock markets. Main financial indexes (Dow Jones, NASDAQ, etc) are known to have an annual average revenue of 10-12% (since 1918). Not these days of course, where high volatility and entropy in the markets are installed. Well,  emergent countries like China are raising themselves at 12%/year also. We could go on and on with so many other examples. Some say that Eolic parks could achieve 40%. Normally the cost of one eolic tower is around 1 million euros, which could be paid back after one year producing energy trough wind at normal operating conditions. The rest are maintenance costs, as well as initial investment in terrains, etc. So, what’s new? Consider this. For moments imagine yourself having 100% in revenues, just last year, at this precise dramatic context. That’s 10 times what the market does in regular years, 20 times what your favorite restaurant does. Moreover, there is a substantial difference between all these examples. If you keep dropping money at the restaurant (for instance the revenue you have earned in the last year), still liquid revenues will be the same in the next year (unless you open a new dinner room next to the first one, while the awful burden keeps increasing). Some business are static and linear in time while others are exponential. As Alice in the wonderland, you will need to keep running twice as faster in order to be at the same place. Amazing those differences, no? Well, not for those “lovely” animal creatures known as Black Swans. According to Patterson, … Funds run by Universa, which is managed and owned by Mr. Taleb’s long-time collaborator Mark Spitznagel, last year gained more than 100% thanks to its bearish bets. Universa now runs about $6 billion, up from the $300 million it began with in January 2007. Excerpts from the Wall Street Journal article (Black Swan Fund Makes a Big Bet on Inflation) follow below. So, why the hell I do not feel at all surprised by this?! Really, I am not. Let me just say, I do have my own reasons:

Nassim Nicholas Taleb - Black Swan author  […] A hedge fund firm that reaped huge rewards betting against the market last year is about to open a fund premised on another wager: that the massive stimulus efforts of global governments will lead to hyperinflation. The firm, Universa Investments L.P., is known for its ties to gloomy investor Nassim Nicholas Taleb, author of the 2007 bestseller “The Black Swan,” which describes the impact of extreme events on the world and financial markets.

Funds run by Universa, which is managed and owned by Mr. Taleb’s long-time collaborator Mark Spitznagel, last year gained more than 100% thanks to its bearish bets. Universa now runs about $6 billion, up from the $300 million it began with in January 2007. Earlier this year, Mr. Spitznagel closed several funds to new investors….

Mr. Taleb doesn’t have an ownership interest in the Santa Monica, Calif., firm, but he has significant investments in it and helps shape its strategies. The term “black swan,” which has become a market catchphrase in the last few years, alludes to the once-widespread belief in the West that all swans are white. The notion was proven false when European explorers discovered black swans in Australia. A black-swan event, according to Mr. Taleb, is something that is extreme and highly unexpected. … […]

Singapore Port in May 2009
[via Foreign Policy / Contrafactos Twitter] (…) Want to get a sense of just how bad things are? Take a spin on Google Earth. The above image, pulled yesterday  from’s Google Earth file, shows container ships languishing off the Singapore coast. Welcome to the largest parking lot on Earth. International Economy explains (…):

“The world’s busiest port for container traffic, Singapore saw its year-over-year volume drop by 19.6 percent in January 2009, followed by a 19.8 percent drop in February. As of mid-March 2009, 11.3 percent of the world’s shipping capacity, sat idle, a record.”

Extremely bad news. Meanwhile, someone have made a huge mistake

Two “The Economist” covers. The first one was manually created and posted by Richard Dawkins himself, … – yes – the evolutionary Biologist. The second one is real as well recent (as of April 4th) – UNDER ATTACK, a 14-page special report on the rise and fall of the wealthy. Do note the Blackberry on top of the dead guy in the front and the skyline of London’s Canary Warf financial district in the background (via HS Dent blog). The Laissez-faire Economy lead to all this (more).

The Economist cover OH FUCK Sept 2008

The Economist April 4 2009 UNDER ATTACK


It’s not everyday we see a 40 year ideology collapsing through a dramatic act of contrition. It has happened just a few hours ago (check video above), yesterday in the “financial crisis” congressional hearing in Washington (23. Oct. 2008). Moreover, what seems remarkable, is that the recognition comes from one of his most universally respected founding fathers and defenders.

Alan Greenspan was the longest serving chairman in the Federal Reserve board history (1987-2006), and during this 18-year period of time he were perhaps the leading proponent of de-regulation along with libertarian capitalism, vividly expressed on his “The Age of Turbulence – Adventures in a New World” 2007 book, advocating above all issues, Adam Smith’s “Invisible Hand” that markets can regulate themselves. As it’s known, for his whole adult life, the former Fed chairman has been a devotee of the philosophy of Ayn Rand, who celebrated free-market capitalism as the world’s most moral economic order and advocated a strict laissez-faire approach to government regulation of the marketplace. Ironically, he was a regulator that did not believed in any regulation at all.

It is now quite a remarkable historic moment seeing former Federal Reserve chairman, a lifelong champion of free markets, publicly questioning the philosophy that guided him throughout his years as the world’s most powerful economic policymaker. A philosophy followed and strongly defended by him (along with many others like Margaret Thatcher and Ronald Reagan), at least in the last 40 years, as he himself acknowledged yesterday. Asked by the congressional committee chairman, whether his free-market convictions pushed him to make wrong decisions, especially his failure to rein in unsafe mortgage lending practices, Greenspan replied that indeed he had found a flaw in his ideology, one that left him very distressed. “In other words, you found that your view of the world, your ideology was not right?” he was asked:

Absolutely, precisely“, replied Greenspan. “That’s precisely the reason I was shocked, because I have been going for 40 years or more with very considerable evidence it was working exceptionally well“. Albeit he was surely one of the most influential voices for de-regulation: “There is nothing in Federal regulation that makes it superior to Market regulation”, said Greenspan back in 1994, in one among many of his past radical free-market statements.

I presume we now all wonder, where was Greenspan, when back in 2003 one of the most prestigiously recognized and legendary financial investors such as Warren Buffet, called credit default obligations and derivatives “weapons of financial mass destruction“? Or where was he when Princeton Professor of Economics, Paul Krugman – the recent Nobel laureate – said back in 2006 that “If anyone is to blame on the current situation (sub prime) is Mr Greenspan who poopooed warnings about an emerging bubble and did nothing to crack down on irresponsible lending“. Or what did he, Greenspan itself, said just a few days after ENRON collapsed?

People working in complex systems – and surely financial markets are one of them (yes, for the past 4-5 years including these present turbulent times I am working hard in this area as well) – for long know that any systemic structure could collapse if only positive-feedbacks are injected into them, creating an auto-catalytic snow-ball effect, leading among other things to a power-law like Black Swan. Indeed power-laws are a striking powerful signature. This is specially true when we address self-organization (read it in the present context as self-regulation). In order to be a truly self-regulated system, financial markets should also be embedded with negative-feedbacks as well, as I have addressed in a post about finance and complex systems one month ago. In fact, in order to emerge as a truly self-organized system, self-interest, should constitute just one among many of the ingredients over the entire financial system, and not the isolated unique ingredient. Self-interest promotes amplification and positive feedback, which is – as I recognize – necessary. However, left alone, promotes instead dramatic snowballing drifts over chaotic regimes, due to it’s intrinsic amplification. What’s amazing (at least for me), is that Alan Greenspan just recognized that in a tiny few seconds along his current discourse (check video above), pointing it to the precise key-word:

[…] I made a mistake in presuming that the self-interest of organizations, specifically banks and others, was such that they were best capable of protecting their own shareholders. […] So the problem, here is something which looked to be as a very solid edifice, and indeed a critical pillar to market competition and free-markets, did breakdown and I think that, as I said, shock me. I still do not fully understand why it happened, and obviously to the extend, that I figure out where it happened and why, … aaaaaa, … I will change my views. If the facts change I will change. […]

As a result, “the whole intellectual edifice” of risk management collapsed, Greenspan said. In what regards his unexpected words yesterday at the congressional hearing, at least, I frankly praise him for his huge intellectual courage and present honesty. In the end, it seems that during the past 18 years, former FED chair was nothing else then a simple-man driven by his own blind faith on markets, from which he apparently comes out now. Unfortunately, only now at a very high price. Meanwhile as we know, severe consequences are here to stay, as was already evident when Greenspan addressed the House Financial Services Committee on 2003 (video below). Let’s hope that all these will not be forgotten in 3 decades from now (though, I doubt it – after all, nothing really serious came out from the entitled 3-man dream-team Bush-Sarkozy-Barroso “new global finance order” summit at Camp David last weekend, as expected):

“You have told the American people that you support a trade policy which is selling them out.” – Rep. Bernard Sanders to Federal Reserve Chairman Alan Greenspan on 7/16/03. Rep. Bernard Sanders (Independent-Vermont), now a US Senator, dresses down Federal Reserve Chairman Alan Greenspan in front of the House Financial Services Committee on 7/16/03.

Subprime Banking Mess (via YouTube) – John Bird and John Fortune (the Long Johns) brilliantly, and accurately, describing the mindset of the investment banking community in this satirical interview.

Now, above in the video, do you remember the words: Structured Investment Vehicle (S.I.V. or Conduits)? No? Okay, let’s now pass to a very brief and relatively more technical approach to it (as you will see it, reality transcends fiction) – CNBC via Youtube:

Care for more?

[…] From the ice-age to the dole-age
There is but one concern
I have just discovered: Some girls are bigger than others
Some girls are bigger than others
Some girls mothers are bigger than
Other girls mothers

The Smiths – “Some Girls Are Bigger Than Others“, (Queen is dead) 1986. Song written by Morrissey and Johnny Marr.

 ________________  §  ________________


Key: “S:” = Show Synset (semantic) relations, “W:” = Show Word (lexical) relations / S: (n) dole (a share of money or food or clothing that has been charitably given) / S: (n) dole, pogy, pogey (money received from the state

 ________________  §  ________________

(via William Gibson‘s blog)

posted 12:29 PM








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