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It is probably true that learning from others either by teaching or imitation is usually cheaper than learning on your own. It is like cheating on a test: you do as well as the person you copy from but avoid all that tedious studying. However, evolutionary models show that if this is the only benefit of social learning, there will be no increase in the ability of the population to adapt. This surprising result emerges from the coevolutionary processes that affect the kinds of behaviors that are available to imitate and the psychology that controls learning and imitation. These evolutionary models of social learning rest on two assumptions. First, the propensities to learn and to imitate are part of an evolved psychology shaped by natural selection. This means that the balance between learning and imitating will be governed by the relative fitness of the two modes of behavior-the average fitness of the population is irrelevant. When few individuals imitate, imitators will acquire the locally adaptive behavior with the same probability as individual learners. Because they do not pay the cost of learning, imitators have higher fitness, and the propensity to imitate spreads. As the number of imitators increases, some imitate individuals who imitated other individuals, who imitated other individuals, and so on until the chain is rooted in someone who extracted the information from the environment. As the fraction of imitators in the population increases, these chains extend further.

The second assumption is that the environment varies in time or space. This means that as chains of imitation get longer, there is a greater chance that the learner who roots the chain learned in a different environment than the current environment, either because the environment has changed since then or because someone along the chain migrated from a different environment. The upshot is that on average imitators will be less likely to acquire the locally adaptive behavior than learners. The propensity to imitate will continue to increase until this reduction in fitness exactly balances the benefit of avoiding the costs of learning. At evolutionary equilibrium, the population has the same average fitness as a population without any imitation. There will be no increase in the ability to adapt to varying environments, and cumulative cultural adaptation will not occur.

Then, if the environment is not too variable, an adaptive psychology will evolve in which most people ignore environmental cues and adopt behaviors that are common in the sample of the population they observe. They modify these behaviors rarely, or only at the margin, and as a result local adaptations evolve gradually often over many generations.

Many examples indicate that people often do not understand how adaptive practices work or why they are effective. For example, in the New World, the traditional use of chili peppers in meat recipes likely protected people from food-borne pathogens. This use of chili peppers is particularly interesting because they are inherently unpalatable. Peppers contain capsaicin, a chemical defense evolved in the genus Capsicum to prevent mammals (especially rodents) from eating their fruits. Nonhuman primates and human infants find peppers aversive because capsaicin stimulates pain receptors in the mouth. Efforts to inculcate a taste for chilies in rats using reinforcement procedures have failed. However, human food preferences are heavily infuenced by the preferences of those around us, so we overcome our innate aversion and actually learn to enjoy chilies. Psychological research indicates that people do not get accustomed to the chemical burning sensation. Instead, observational learning leads people to reinterpret their pain as pleasure or excitement. So, New World peoples learned to appropriately use and enjoy chili peppers without understanding their antimicrobial properties, and to do this they had to overcome an instinctive aversion that we share with other mammals.

Fijian food taboos provide another example of this process. Many marine species in the Fijian diet contain toxins, which are particularly dangerous for pregnant women and perhaps nursing infants. Food taboos targeting these species during pregnancy and lactation prohibit women from eating these species and reduce the incidence of fish poisoning during this period. Although women in these communities all share the same food taboos, they offer quite different causal explanations for them, and little information is exchanged among women save for the taboos themselves. The taboos are learned and are not related to pregnancy sickness aversions. Analyses of the transmission pathways for these taboos indicate the adaptive pattern is sustained by selective learning from prestigious women.

Culture and Maladaptation
…this same propensity will cause individuals to acquire any common behavior as long as it is not clearly contradicted by their own inferences. This means that if there are cognitive or social processes that make maladaptive ideas common, and these ideas are not patently false or harmful, people will adopt these ideas as well. Moreover, it is clear that several such processes exist. Here are a couple of examples…

Weak Cognitive Biases Can Favor the Spread of Maladaptive Beliefs or Practices over Generations. Laboratory diffusion chain studies clearly document that biases that have undetectable effects on individual decisions can have very strong effects when iterated over “generations” in the laboratory. The same effect may lead to the spread of false beliefs in natural populations. For example, Boyer argues that a number of cognitive biases explain the spread of supernatural beliefs and account for the widespread occurrence of folktales about ghosts and zombies.

Adaptive Social Learning Biases Can Lead to Maladaptive Outcomes. A model’s attributes provide indirect evidence about whether it is useful to imitate her. If she is successful, then by imitating her you can increase your chances of acquiring traits that gave rise to her success. If she is more similar to you than alternative models, her behavior may work better in your situation. If her behavior is more common than alternatives, then it is likely to be adaptive because learning increases the frequency of adaptive behaviors. An evolved cultural learning psychology that incorporates such biases increases the chance of acquiring beneficial beliefs and behaviors. However, these same biases can sometimes lead to the spread of maladaptive beliefs and practices. For example, the tendency to imitate the prestigious, or those making credibilityenhancing displays of commitment, can lead to a “runaway” process analogous to sexual selection, and this may explain the cultural evolution of maladaptive cultural systems in which people risk life and limb to summit icy peaks or achieve spiritual perfection in celibate seclusion.


from this paper.

This may explain why globalization is still dominated by American culture currently, although US is declining and clearly unsustainable. And many cultures just imitate the superficial culture traits of US (e.g. cars, technology), not really learn the institutions design that are keys to US success (and failure).

Another important point of this paper:


…loss of beneficial technologies in small, isolated populations. For instance, the Tasmanian tool kit gradually lost complexity after isolation from mainland Australia at the end of the Holocene. Other Pacific island groups have apparently lost useful technologies, such as canoes, pottery, and the bow and arrow. The best documented example comes from the isolated Polar Inuit of northwest Greenland. Explorers Elisha Kane and Isaac Hayes wintered with the Polar Inuit in 1853 and 1861, respectively, and reported that the Polar Inuit lacked kayaks, leisters, and bows and arrows and that their snow houses did not have the long heat-saving entryways that were seen among other Inuit populations. They could not hunt caribou, could only hunt seals during part of the year, and were unable to harvest arctic char efficiently, although char were plentiful in local streams. Apparently the population was struck by an epidemic in the 1820s that carried away the older, knowledgeable members of the group, and according to custom, their possessions had to be buried with them. The Polar Inuit lived without these tools until about 1862, when they were visited by a group of Inuit who migrated to Greenland from Baffin Island. There is every reason to believe that these tools would have been useful between 1820 and 1862. The Polar Inuit population declined during this period, and the tools were immediately adopted once they were reintroduced. After their introduction, population size increased. It is also telling that the kayaks used by the Polar Inuit around the turn of the century closely resemble the large, beamy kayaks used by Baffin Island Inuit and not the small sleek kayaks of the West Greenland Inuit. Over the next half century the Polar Inuit kayak design converged back to the West Greenland design. If this inference is correct it means that for 40 years (nearly two generations) the Polar Inuit could have benefitted from the lost knowledge. Moreover, they collectively remembered kayaks, leisters, and bows and arrows, but did not know how to make them and could not recreate that knowledge.

Lost knowledge can be hard to re-created again, especially when the knowledge is imitated superficially but not really learned its essence.

hypothesis that individuals who vary genetically in their capacity to learn (or to adapt developmentally; Ref. [9]) will leave most descendants because they will have the greater capacity to adapt.

In a short and insightful paper that appeared in 1987, Hinton and Nowlan [11] developed a simple computational model based on an extended version of genetic algorithm to demonstrate the magnitude of what was now being called the ‘Baldwin effect’. Their simulation, suggesting ‘how learning can guide evolution’, shows straightforwardly that creatures that are genetically predisposed to learn (in their oversimplified mode) by guessing the solution to a given environmental obstacle, by virtue of having correct settings on all the hardwired alleles, are on average more fit than those who cannot guess the solution. Moreover, their model demonstrated that, without ‘learnable alleles’, pure evolutionary search is completely blind and exceedingly slow.

The Berkeley biochemist, Wilson [12], who in the 1960s introduced the concept of a ‘molecular clock’ (based on genetic mutations that accumulate since they parted from a common ancestor) in evolutionary biology, predicted in 1985 that the presence of cultural factors may create a selective pressure for the ability to learn itself. Based on his early results on quantitative molecular evolution, he developed the concept of a ‘cultural drive’, through which the time required for a population to fix a mutation that complements a new behavior is shorter if the new behavior spreads quickly not only to offspring (vertically) but also to other members of the population (horizontally). His example of this cultural drive was the rise of agriculture that imposed new selection pressures, leading to swift genetic changes in human populations. He then considered the well-known example [13] of the introduction of milk sugar (lactose) into the diet of adults as the result of the invention and social propagation of dairy farming (pastoralism). In the relatively short period of 5000 years, genes conferring the ability to absorb lactose reached a level of 90% in populations dependent heavily on dairy farming, while, in contrast, the level of these genes is virtually zero in human populations that do not drink milk and in all other mammalian species tested. Analyzing the same phenomenon, the correlation of a genetic variation and a cultural trait, Feldman, Cavalli-Sforza, and Zhivotovsky [13] described it as ‘gene-culture coevolution’.

The edge-of-chaos regime is the optimal condition to be in a constantly changing environment, because from there one can always explore the patterns of order that are available and try them out for their appropriateness to the current condition. What is not necessary at all is to get stuck in a state of order, which is bound sooner or later to become obsolete. In that way, complex social systems that can evolve will always be near the transition region, poised for that creative leap into novelty and innovation, which is the essence of the evolutionary process.

‘life is evolution at the edge of disorder’.

In 1987, Modelski (Ref.[19], Chap. 5) proposed that the rise and decline of world powers (known also as the long cycle, the constitutive process of world politics) are best understood as a learning process, and in 1991 [20] described it as “evolutionary learning”. In 1996, he presented the evolution of global politics as a complex system situated at the border between order and chaos (Ref. [21], pp. 331-332)… Modelski and Perry [23] argued that, in the perspective of centuries, democratization is the process by which the human species is learning how to cooperate, and demonstrated that the rise in the proportion of the world’s population living in democracies (now exceeding 50%) is best described as a logistic process of the diffusion of a strategic social innovation.

The pace of the process, and hence the duration of the K-wave, is determined by the two biological control parameters already discussed: the cognitive (the collective learning rate), driving the rate of exchanging and processing information at the microlevel, and the generational, constraining the rate of transfer of knowledge (information integrated into a context) between successive generations at the macrolevel.

typical values for the diffusion learning rate of basic innovations are 16-17%, corresponding to typical time spans of about 25-30 years [generational turnover] for the spread of these radical innovations.

We note, first, the multilevel (or hierarchical) character of this evolutionary analysis. It posits that social evolution is not a singular process with one simple trajectory but an entire cascade across a number of levels—agent, institutional, species-wide—and those evolutionary processes occur or proceed at each of these levels [recall panarchy]. That accords broadly with the position of Gould, described by him as the “hierarchical theory of selection” (Ref. [34], Chap. 8). Contrary to the conventional Darwinian argument, that selection operates solely at the organismic level, and which has recently been expanded to the level of the genes (in Richard Dawkins’ ‘gene selection’), Gould argues that “Darwinian individuals” (those with a reproductive potentiality, hence evolution-capable) may be found across an entire biological hierarchy, beginning with genes and cells, to organism, deme, and species, and it is the last level that is of interest for the present analysis. [how about ecosystem?]

The phenomenon at hand (the cascade of world evolutionary processes) is then a cascade of scale-invariant, interdependent, and structure-transforming processes at several levels of organization of the self-organizing complex world system. In other words, such structure-transforming processes come to existence through the innovation process occurring at the several levels of the cybernetic hierarchy [systems higher in the order are relatively high in information while those lower down are relatively high in energy. That is, in effect, information controls energy (via communication).] and at the several scales of world organization (local, national, regional, and global). But innovations must diffuse in and be learned by society, and the adaptive mechanism of learning is paramount in giving the pace of change at each level.

In as much as “information controls energy”, the cybernetic hierarchy might be seen as the expression of the requirements of learning. This is why, thirdly, each of the four world system processes can be described as an algorithmic (Dennett [37], Chap. 2) learning process, because each might be seen as four-phased, and the phases are ways in which information is transformed into energetic solutions. The phases of a social learning process are generally seen to be (1) developing a variety of information; (2) mobilizing support; (3) choosing and/or deciding; and (4) implementing. Most notably, this concept of learning also comprises the essential elements of Darwinian evolution, namely (1) variation, (2) cooperation, (3) selection, and (4) amplification (differential survival) [9]. This evolutionary concept can also be rephrased as specifying a set of simple rules whose application brings about complex systems. These rules are (1) generate variation; (2) mobilize (and generalize); (3) select; and (4) amplify/reinforce. [recall four phases of adaptive cycle]

our postulated cascade of world system processes: social systems may self-tune their structure to a poised regime between order and chaos (as if by an invisible hand, in Adam Smith’s felicitous phrase, and as Kauffman has pointed out), with a power law distribution of breakthrough events, or in other words, of innovations.

what is seen as self-organization might more precisely also be systemic learning. In more general terms, ours might be recognized as a “learning civilization”. It is good to know, too, that world history might be the unfolding of a millennial learning process. If, as Gould (Ref. [34], p. 1055) maintained, “most evolutionists. . . are historians at heart”, then maybe the reverse could also come to be true.


from this paper.


The concept can be understood by looking at its Table 2: Cascade of modern evolutionary processes.

One of the reason people are not motivated to cooperate is lack of global vision. Avoidance of something worse is not enough. People would rather grip what they have right now even though they know it becomes worse tomorrow. To motivate, there have to be something more attractive than present if they act. And actually it is exactly what will happen if we change – we would be better off, happier, our civilization will be far more advanced, and we will be able to go out of the Earth.

Yes, out of the Earth, you hear it correctly. We (The Earth’s Biosphere) need not be constrained by the limits of Earth forever. We will be better diversifying ourselves to multiple planets/outer space’s living spaces if anything happens to the Earth, Sun, or even Galaxy. We will be better prepared to meet extraterrestrial beings. This is the dream of humanity, popular in 1960s but fading afterwards. We waste precious time by dealing with symptoms of our own problems so that they keep dragging us from progress.

Thus to realise this vision we have to really resolve our problems, unite, to release our full potentials so that we can get full ingenuity apply to this challenge. It is so much waste for so many population but under-develop; genetic or cultural diversity becomes source of conflicts instead of source of ingenuity; precious slow-renewable resources and time wasted on conflicts rather than for going out of the Earth. If we collapse now, then the Biosphere have to wait for a long time for slow-renewable resources to recover and then the next emergent (and hopefully wiser) life can utilize them to make the breakthrough.

One important point: even if we have succeeded to go out of the Earth, never damage the Earth. The Earth is still the best place for us. It is where we come into being and evolve, therefore the environment is the most suitable living condition to us. It is our base for diversify, so we should sustain it as long as possible. Not to mention we are not ready to go out of the Earth yet. I don’t see any reason why we should not act to sustain our base, exploit our full potentials to maximize our (life’s) chance of existence. It is how the world works (dynamics, evolution).

P.S. When writing this post I discover the debates of terraforming and its ethical concerns. It led me to think that what should we act if we encounter extraterrestrial beings. Life is reconcilable if we can find something in common, for example, we are actually from the same origin because both of us are the product of terraforming by other extraterrestrial beings in different planets a long time ago. Then it immediately appears to me that by enlarging our scope, shared prosperity is always possible.

This blog post tells a good example of my concept of learning. It is the most effective, as people look at the results using their eyes, comparing the results and reflect on the differences. Same input, different interventions, different outcomes. It must be due to the interventions! No cognitive conflict can be stronger than this. By explicitly pointing out this, again and again, people cannot escape but reflect.

If we have two earths (at least two human-hospitable planets), then we can run an experiment – one earth is like now, business as usual; and another earth changes to sustainable course. Wait and see them after Year 2050, we will learn that which one is better choice.

Unfortunately we don’t have another earth to learn. The best we can do is creating virtual earths, or modelling and simulation to test policy interventions. People who don’t like simulation outcome of a model can always complain about its assumptions, since model is never as perfect as the real world. But this is what the best human can do. Study the model as unbiased as possible, learn its usefulness and limitations, examine its assumptions and trace back to understand why the simulation outcome is like that (how the model results that simulation outcome). We can learn a lot even the model is not perfect.

Another way is to learn from history. Of course no history is identical. But similar to modelling and simulation, we can learn its usefulness (insights) and limitations (what may not apply). Understand why the history becomes like that is the most important gain of study history. Generally most of the insights are just repeating. If our civilization is collapsing again, it means we didn’t learn enough history.

How to make a civilization fail? Borrow until broke, from future generation.

Inspired by this column.

Some people (optimists like some economists) are confident (overconfident?) about human . They think that human can solve any problem as long as there is a need. This perception formed may be due to the industrial advancement (standard of living, science and technology, better institution) since the last few centuries. But can we attribute it solely to the human ingenuity? Why human did not achieve the great leap earlier (note that human has already been evolved to this current form since at least 50,000 BP, before the last fews centuries human history keeps showing rise and fall of the civilizations)? Some other people argue that rising of current civilization is mainly due to high EROI of fossil fuel. I cannot judge because I think it is hard to identify the root causes in an unrepeatable process like this.

While I have no plan to talk about reasons of rising of current industrial civilization in this post, it is a good example to show that how poor our knowledge be. While we can send people to the moon, we cannot eradicate war, hunger, AIDS, traffic jam; we still struggle in developing technology that can recognize people’s face un-intrusively and flexibly under natural environment like human does; or we cannot even predict how the water level of a bathtub change. There are lots of examples you can think of about what human still cannot do presently, even there is a will (e.g. forecast direction of winds that bring the volcano ash).

The most critical evolutionary constraint on human is to understand complexity (complex means difficult to understand, so a thing will not be called complex if we can understand it). For example, no one know for sure what will happen in the current Euro financial crisis. What if we let Greece bankrupt? What is the consequences (especially unintended consequences) of current decision to bail it out? We grow our civilization to this state of complexity but we don’t know how to manage it. In a world of changing faster and faster and becoming more and more interconnected (interdependence), we just realize how poor our ability to control it to achieve the vision we want.

This is my thought after reading this post:


The ultimate challenge for humanity, then, is to figure out how to make insight about complex systems evolutionarily successful.

At least, we need to recognize that we still ignorant of many things. We should be more humble. We should be more careful. We should be watchful about where our current direction leads us to be, and rethink the actual relationship between economic growth and human development. So I think the first step should be raising awareness about our poor ability to learn complexity (especially dynamic complexity).

If you think this is not an issue, then ask yourself: Are you happy? Do you feel your life is full of happiness? If not, why? Do you think you are happier than people before the industrial civilization? Or more simple question, happier than people who died before the internet has invented? You enjoy so many modern innovations, you should be much happier than them. If not, this is a sign of unhealthy development. Development should increase people’s happiness, not less. Let’s think about it.

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