(Потому что наши русские читатели очень важны, мы сейчас в поисках профессионального переводчика. Мы приносим свои извинения, что на данный момент, мы можем лишь предоставить текст на английском языке.)

Why are people? The title of chapter one properly defines the reason for this book’s existence. Why their worries, why their struggles, fears, lovings, hatings? What is our purpose on this planet and ultimately in the universe? Why all the bad things in order to feed our visceral hunger for pleasure? Why does the phrase “nature red in teeth and claw” make such a perfect opening epigram for any biology book?

Naive lily-livered eschewers run all their lives on the treadmill of ignorance diverting their thinking from the answers to the above questions, beguiling themselves to some hopped destination where all things must be about peace, pleasure, and the good of man. Call it heaven, nirvana, ultimately the reason for all this life of struggle. These are the theists not famished at conception with the love for the real truth, be it white, gray, or black. They will never have the guts to face reality, they will always be driven and controlled by emotions. And what do you expect to happen when you have individuals with this kind of agenda up their sleeves? The Bible, brain-washed children, a general milieu of malevolent ineluctable set of memes from which society can have no hope of freeing its fettered limbs from the leashes of nature. And in the middle you have the people who didn’t have the time to make up their minds, and this book is for them in particular.

Yes, life can be fun. But there are myriad of antithetical examples both in the animal kingdom and in the human society in which life is anything but innocuous. This book is about the truth of these facts and the reasons for it being this way. Its purpose is not to feed the emotional thirst for positiveness, safety, and well being. Its embodied astute goal is to climb the ladder of truth, blithely analyzing the causes and effects, the ontology and systemic organization of nature and its products: Us and all living things that roam planet Earth.

What is this book’s mission? To explain biology’s gears, levers and pulleys, individual selfishness, altruism, behavioral strategies in animals and consequently in us humans, presenting all of these using the gene, that is, the slightly small set of bits from the chromosome that is capable of surviving meiotic division a significant amount of time for it to be considered a long living sequence of DNA, as the single unit of natural selection.

So, although counter-intuitive, the consequences of adopting this point of view apparently transforms us human beings into mere puppets, zombie vehicle robots designed, programmed and polished for eons by our genes in order to preserve their prodigiously long chain of nucleotides. That is, blindly designed, blindly programmed, for genes are only mechanistic stable arrangements of molecules that sprouted in the non-steered, full of ingredients but lacking design, primordial soup; genes are the software that bootstrapped themselves in the Multiverse from shabby tooled beginnings. Atom by atom, molecule by molecule, this software began to be assembled by the environmental machinery that is planet Earth some 4 billion years ago.

Therefore, Natural Selection does not select between ecosystems, or species, or groups, or even individuals, but between genes. This so counter-intuitive approach is tantamount, Richard argues, to the cyclic change in perception when one looks at a Necker Cube; from time to time, as you look at the cube, it seems that the point of view from which you look at it changes its position. The same thing happens when we analyze what does the “Necker Cube of Natural Selection” act upon when it selects between structures that need to survive. But unlike in the Necker Cube analogy where any point of view might be the right one to look at, in the case of analyzing natural selection’s inner workings some points of view might be more needless than others. Ecosystems, groups, species, and individuals do not fight for dominance, instead, the structures they emerge from do it: their Genes. There is no act done for the good of species. Instead they’re acts done for the good of the genes, more exactly, for the good of complexes of genes. The genes’ blind, blithe, and most importantly, unconscious acts are iconoclastic image destroyers for the mis-construed whelps of group selection. Let’s analyze this book chapter by chapter.

        Chapter 1: Individual evanescence, gene immortality and the steering of the gene pool. As we’ve made the point in the above text, the single unit that natural selection acts upon is the gene. Genes can live hundreds of millions of years unscathed. As opposed to them, groups, species, and ecosystems die out and constantly morph themselves into new organizational structures with no hope but to be whisked aside by newer and more adapted systems as soon as these get the chance to get command of the operations.

The main point of chapter one is to emphasize the importance of the above statements. Compared to the life of their genes, individuals have a very short lifetime because meiotic division and sex re-steer these complexes of genes in the new primordial soup, the gene pool, that is, the myriad of vehicles that carry the genetic material for the sole purpose of preserving it; these vehicles, meaning me, you, humans, all the animals, plants, and insects are then cast aside in order to be replaced by newer, and hopefully, more advanced carrier robots.

Selfish is a very adequate adjective to emphasize our evanescent existence, but what about our apparently altruistic acts? How can we explain this behavior when it escapes even the most non-shallow attempts at using individual selfishness as the major reason for it. It seems altruism at the individual level emerges only because of the selfishness of the sets of genes yoked together by millions of years of evolution. Saving your ten brothers from a certain death at the expense of your own life might mean a lot to your genes, because the probability that 50% of your genes are to be found in every brother of yours means that your death will save five more times copies of some of your genes than they would be saved if you would have left your brothers blithely perish. Individuals die, only genes survive.

        Chapter 2: The bootstrapping of survival machines and their first attempts at staying safe. “From so simple a beginning endless forms most beautiful and most wonderful have been, and are being, evolved.“. This part of one of the most known phrases written by Charles Darwin properly exposes Chapter two’s plot. Although a science territory that lapses a lot from the empirical point of view, Abiogenesis, the story of how simple organisms bootstrapped themselves almost spontaneously from inanimate matter, and afterwards evolved into complex entities like the one reading this material, gives us a enthralling explanation about the possible ways in which this might have happened.

The primordial soup, consisting of water, carbon dioxide, methane and ammonia among other elements, constituted the primary ingredients from which certain stable molecular structures begun to emerge as early as 4 billion years ago. The rarest event, which had to happen only once, bootstrapped into existence the first molecular arrangement capable of making copies of itself, the first Replicator. The mechanisms of how this might have happened are well explained in chapter two, but the most important idea worth exposing is that compared to events that hitherto managed to produce molecular arrangements as complex or even more complex than our replicator, that weren’t endowed with the capacity to replicate themselves, our lucky molecule, the Replicator, had this constitutive cunning ability, that is, to make copies of itself. So little by little, beginning with an initial biologically empty and dull primordial soup, more and more replicators began populating the hitherto bare environment without the “fear” of being devoured by bacteria and other microorganisms because of course there weren’t any at that particular time.

So, from so simple a beginning where resources were plentiful, these replicators diversified into more complex ones that took advantage of the now starting to get sparse number of resources. They started designing survival machines, which at first constituted just a protein wall, and then evolved proto-carnivore capabilities in order to feed themselves with the survival machines of the other not so equipped replicators. Nature’s bloody movie begun tailoring itself.

        Chapter 3: The specializations of survival machines, and the tool of sex. How did the replicators manage to live throughout 4 billion years of constant blood bath? By building exquisite survival machines properly designed to fit a certain niche in the ecosystems that covered this planet. Fish are survival machines designed for life in the water, whereas monkeys for example, in general, are designed to survive in closed forest environments. Chapter three shows us how genes are manifestly responsible for their own survival. Selfishness is a requisite quality of every gene, quality that often translates itself to individual martyrdom. Acts of altruism that previously were wrongly explained as self sacrifices done by the individual for the good of the species (see group selection), and that often sparked feelings of deference towards us and the animal kingdom, are now given a proper reality tuning by using the ersatz of the gene point of view.

The tool of sex and meiotic division has the same purpose of shuffling the replicators as did the primordial soup eons ago. The benefit that the genes get out of this? Eternal Life. As for their survival machines, the lumbering zombie robots that we are, we’re doomed to perforce mortality. Blessed with uniqueness for an inconsiderable amount of time compared to the everlasting life of the genes that supervised our growth and development, we will blindly be cast aside by the replicators for in this mechanistic natural environment this is what can happen, has happened, happens, and will happen at least in the near future. Why can it happen and why does it happen remains a mystery for philosophers and physicists to explore? But then again, purpose has no meaning, logic and place at analyzing these facts. It happens because it can. It happens because it happens and that suffices as an explanation.

        Chapter 4: In building and programming the brain of their survival machines, genes don’t posses total control over their behavior but only a chance at an optimum parsimonious training. Chapter four dredges on the details of how the replicators play the chess game of building their ‘must be exquisite in order to survive‘ carrier zombie robots. One fact worth noting is that the wielding of the replicator’s prowess has, of course, some limitations. The growth and development of the survival machine occurring under total gene control takes months if not years to yield fully bred organisms. Not only that, after the genes manage to do their finesse job of building their organism they transfer total control to the highly advanced software that runs in its brain. From now on survival machines are on their own. The software that modulates their behavior and modifies it by using built-in learning techniques (dreaming is such a tool), and that generally anticipates future happenings by building a virtual model of the world and making simulations on it, will be the source of insight and foresight in the survival machines’ search for the moments so yearned by the built-in pleasure seeking cognitive tools of its brain.

Pain, lust, love, anger, thirst, and hunger will trigger the functions of this software. What is their desired effect? To trigger the behavior which will tend to maximize the chances that the genes, which created the survival machine, will increase their number in the gene pool. In general, this selfishness at the gene level translates itself into individual selfishness but not always. As chapter four reveals, individual altruism may sometimes be the serendipitous effect of the replicator’s self-interest.

        Chapter 5: Evolutionary stable strategies and how these translate into the genetic warfare fought by the survival machines, a.k.a. Individual Aggression. A very important mental tool will be introduced in Chapter five. The Evolutionary Stable Strategy (ESS), first presented by the British theoretical evolutionary biologist and geneticist John Maynard Smith, will be the party popper used by Dawkins to lampoon the attempts made by group selectionists at explaining some apparently weird animal behavior involving aggression.

Dawkins helps us imagine a mental exercise in which, on a given territory, animals of a certain kind can be programmed by their genes to use any of the following two behavioral strategies all the time, or a combination the two with a ratio randomly chosen. These are the so called Hawk and Dove strategies, with no relation with the real animals. These creatures are programmed by their genes so that if the animal uses the Hawk strategy, when confronted with either another Hawk user or a Dove user, it fights back vigorously until exhaustion. On the other hand, when the Dove user encounters another Dove user they don’t fight, but have the opportunity to play an attrition game until one of them backs down; also, when a Dove user meats a Hawk user, the one using the Dove strategy promptly leaves the fighting ring without getting hurt. Points are assigned to each result of the above behaviors such that a winner gets 50 points, a loser that gets seriously injured gets -100, a loser that runs away gets 0, and any contestant that wastes considerable time in any contest gets -10 points. These points are to be considered equivalent to copies of genes that are spread in the gene pool. The more points a certain individual earns the more genes it spreads in this novel primordial soup.

So what should we expect when we build a computerized model as the one above and simulate it on the computer? Say, for example, we have a population that contains only Hawk strategy users. If we calculate (check chapter five for details) the average pay-off of each individual considering it has 50% chance of winning any contest we will obtain the value of -25 points. So, on average, in a population consisting only of Hawk strategists each individual loses on average 25 points. Let’s now consider a population made entirely by Dove strategists. The average pay-off will be +15. So the smart thing to do, group selectionists argue, is for all the animals to adopt the Dove Strategy. But that is not what happens because the system is vulnerable of treachery from within. A promisingly thrifty spoilsport might start to adopt the Hawk strategy and win all the battles averaging +50 points of gene spread accrual. So genes for Hawk strategy users will start to increase. It seems that this average point will oscillate until it will reach a stable point of +6.25 (the so called Evolutionary Stable Strategy-ESS).

So, if group selection were true all creatures would adopt the Dove strategy and would average +15 points in pay-off, or, if we calculate even further, in a population consisting of 1/6s Hawk strategists and 5/6s Dove strategists the average pay-off for each individual would be +16.66 points so this might offer the highest average pay-off to each individual making it the ideal strategy for all individuals to adopt. The fact that we don’t see this happening consists serious evidence for the frailness of the generous ‘for the good of species milieu‘ explanation that group selection theory advocates for. This, and much more in Chapter five.

        Chapter 6: Genetic teammanship and the exclusion of rogues. Why the same copies of genes should and do like each other? One fact worth putting emphasis on when talking about individual altruism engraved in the survival machines by gene’s selfishness is how does this altruism emerge. How could this happen, for genes are blind? How could the non-discriminatory tools of sex and meiotic division assemble the exact set of genes that are capable of programming their survival machines to recognize them and act appropriately in order to increase their copies in the gene pool? What are the chances that a gene say, for example, that makes you grow green mustaches be cobbled together with a gene that makes an individual organism recognize the green mustache, and more to that behave altruistically towards such an individual? Very slim.

The reality is that there need not be such a contingency for altruism to develop. We don’t really need a gene for green mustaches, a gene for recognizing mustaches, and a gene for programming their survival machines to behave altruistically towards individuals with long green mustaches to be piggy-backed one upon another in order for altruistic behavior to occur. And as a matter of fact, Chapter six, doesn’t even provide evidence to support the existence in the animal kingdom of any such discriminatory acts of altruism or equivalents of them. A gene needs not to program its carrier organism to recognize a certain other gene and behave altruistically towards it. It only needs to just so happen to program the survival machine to behave altruistically towards individuals that by happenstance, because they live in the same small group, probably share a lot of their genetic material and by consequence the gene for behaving altruistically.

So here we have it. Genes for altruism spread by programming their organisms to behave altruistically towards all the individuals in their group. But this seems a bit simplistic. If supposedly in the tribe i live in i have to choose between saving the life of my three brothers or the life of my three cousins doesn’t the altruism gene have a problem between choosing between them? That is to say, i share a lot more genetic material with my brothers than with my cousins so i should leave the later perish in order to save my much more closer kin. But how does one know which individual is more related to him than to someone else. How do you separate brothers from cousins, from uncles from fathers, etc in order to know how to act when some random incident happens? One method, Richard argues, might be to measure your physical resemblance to each and every one of them, but even this method, albeit in the absence of mirrors, might not give sufficient information. Solution to this problem?

Well, because it seems that any individual will find it hard to guess the correct index of relatedness, that is, the percent of genes he/she shares with the individual we are comparing him/her with, we should also use an index of certainty. That is, the certainty to which we really know a specific index of relatedness is right, the certainty to which we really know a certain percent of genes are also to be found in the individual we might be willing to save the life of. So, for example, whilst a mother might really know that she shares 50% of her genes with her son, the son, even though he also knows he shares half of his genes with his mother, he sure as hell wouldn’t want to bet the same think for the father that provided food, time and energy for his upbringing. The father might be subjected to cuckolding, therefore, if that happens, none of his genes would be present in the son.

So rather than spuriously behave as if everyone is acting candidly for the good of the group, every gene that has survived surely must have been endowed with a little more adroitness than some dodgers might have hopped. We should expect genes to program their survival machines to act altruistically towards individuals in their group based on a so called estimate index of relatedness that need not always be the correct one. Better to be safe than to be fooled. This and much more about the topic of Genemanship in chapter six.

        Chapter 7: Family planning, birth rate regulation, and why almost certainly group selection is must be false. Another animal behavior conundrum is given ample space in Chapter seven and that is birth-rate regulation observed in several species of animals. These species apparently reduce their birth rates during periods of excessive population size. The selfish gene theory, some group selectionists have thought, couldn’t predict that because it wouldn’t be in the best interest of each and every one individual to reduce its child-bearing. Selfish genes would tend, so they say, to program their survival machines to bear and care for as much offspring as they can taking advantage of the resources left unused by their more altruistic co-inhabitants. Instead, what we observe in these studied species is that they all reduce their birth-rate during the fever pitch of population size, therefore they all apparently act for the good of the species. What should we make of this conclusion?

To solve this issue Dawkins’ retort takes us back again to the ESS (Evolutionary Stable Strategy) concept introduced in the first chapters of the book. Selfish at the gene level need not always translate itself into survival machine’s visceral urge to procreate until it collapses. Bigger numbers don’t always bring better results. What if all the resources of a given individual are wasted only on child-bearing leaving him depleted of any energy to invest into the caring of the produced offspring? That would mean a lot of them would die of famish if a poor year regarding resources is up ahead, and this would translate itself into a very poor score of gene spreading. So, birth-rate regulation is not achieved by individuals in order to help the group as a whole, but to obtain a optimum net benefit in gene spreading considering the idiosyncratic characteristics regarding future climate, resource availability, and potential disease that may change the maximum optimum number of offspring for the upcoming year. This optimum number that consists in the optimum number of child-bearing and optimum number of child-rearing is very flexible and programmed to be achieved with a high degree of precision by the predictive cognitive tools build into each and every one individual’s brain. How is that achieved you can find out more information about in chapter seven.

        Chapter 8: Genetic warfare between parents and offspring, brothers and sisters, and why sometimes it pays some selfish genes for impaired runts to die. In Chapter eight it’s time to demote the sanctity of parental altruism and its purported non-discriminatory genre. Do parents have preferences, do brothers fight for food, and if they do, what optimal behavior should an astute selfish gene imprint in their brains in order to maximally increase its copies in the gene pool?

First of all let’s squander some time on the whys of the problem. Although, for example, a mother shares 50% of her genes equally with her offspring, there may be situations in which differential investment of resources might bring her the maximum genetic pay-off. A younger offspring surely is a lot more helpless and needs a lot more assistance in food gathering than his more grown brothers, so it would pay his mother’s and even his brothers’ genes to allow him to drink one more pint of milk than his average share. This logic though won’t save the poor runt when he would be so weak and deflated from energy that the amount of fair investment needed from his mother and brothers in order to survive would not exceed the net genetic-payoff of each and every one individual of the family; in this cul de sac moment the runt can only hope for a short death in order to egress from his predicament and that is to be eaten as fast as possible by its own family.

What about the wars for food between the little brothers. Because they share 50% of their genetic material, each individual should try to deceive its parents in order to get as much food as it can. “As much as it can” but up to a certain point, that is, until the average pay-off in genetic currency of gene spreading of the individual is greater than the double the cost to any brother that he might be trying to get advantage of. This intermediate period gives justice to the 50% genes that are found only in him but not in his brothers; it gives those genes a chance to be copied an extra amount of times by depriving the 50% of genes that are in his brothers, but not in him, of the same chances. It’s a war for slots in the time machine and survival machines are just tools.

The evolution of menopause in women is also a direct consequence of the dissimilar pay-offs that specific differential investment strategies might bring. How can this be? Well, eons ago, after the female passed a certain age, the chance that any child she would have beared after that age would survive the straits of life decreased dramatically such that from that point on it would pay more to her genes to invest in her granddaughters and grandsons than in the child-bearing and child-rearing of new offspring. So the survival machines that were endowed by chance with these genes played an important role in increasing the chances of survival of their granddaughters and grandsons that also possessed the gene for menopause. The ones that did not have those genes decreased their copies in the gene pool up to the point of reaching non-existence.

        Chapter 9: The sexual arms race of mate deception, and honesty’s tender spot. Up to now Richard’s book canvassed the behavioral arms race between parents and their offspring, brothers and sisters, and between families within isolated groups belonging to certain species, or to put it more generally between survival machines or families of survival machines that share a significant amount of their genetic material. In this chapter it’s time to assault the relationship business between individuals that do not share a big number of genes, the sexual partners. Different weapons lead to different strategies. The same thing applies to mating. What’s the difference between a male and a female? The most salient and important difference from the evolutionary standpoint is their size. Male gametes are small, agile and armed with ferocious weapons ready to be used when encountering another male’s sperm. Female eggs instead, besides their lack of agility and anti-female-gametes weaponry, are a lot bigger in size.

Eggs are big, so consequently they are hard and expensive to produce. So, when a sperm fuses with the egg of a certain female, that female has invested right from the beginning a lot more resources in the upbringing of the offspring than the male. Because sperm is cheap to produce, and to be found in sufficient quantities, we should expect females to be vulnerable to male exploitation, but just in a special sense. That is, they should be vulnerable only to philanderer males, which most than likely will leave them after being allowed to copulate a couple of times.

Male exploitation does not lapse either. Faithful fathers are subject to the risk of cuckolding, that is, the risk of upbringing another male’s offspring while believing it is theirs. As you can see, honesty, in both sexes, is severely punished if not accompanied by certain protection schemes. Chapter 9 analyzes the Domestic Bliss and He-Man strategies, both used by the “weak” gender to counterattack the exploitation of potential philanderer males.

The Domestic Bliss strategy is used by coy females. It practically consists in the female postponing as much as possible copulating with the courting male. The more time and resources (serving food, building a nest, etc.) the male squanders on the female, the more engaged he is to her in the sense that, after copulation, he has less to gain if he leaves, genetically speaking, than he would have gained if he had left an easy female which would not demand any food or long courtship period in order to copulate.

The He-Man strategy is used by easy females. In this strategy the female assumes 100% the responsibility of the rearing of the child and seeks the males, be they philanderers or not, with the best genetic material to mate with. Long legs, powerful muscles, powerful character and intelligence may be some of those characteristics that make female He-Man strategy adopters get turned on by.

In reality we will not find 100% Domestic Bliss or 100% He-Man adopting females but something in between. An evolutionary stable strategy will emerge in which it pays to use these strategies interchangeably, or even both at the same time but targeted towards different individuals. For example it would pay a lot more for a female to trick a faithful male into rearing a physically genetically superior philanderer’s child than to rear it on her own. So, she should use He-Man with the superior man if its worth it, and Domestic Bliss with the faithful gullible male, therefore grabbing two rabbits at the same time.

        Chapter 10: The “I help you, you’d better help me!” game of animal symbiotics, and how “The domain of Danger” suffices at explaining the appearance of altruism. Why do we see animals from open fields like the Savanna living in herds? Is it just a kind of group selection where they cleverly decide to join forces in order to curdle together their frail groups so to obtain a stronger one? Buffaloes, zebras, elephants are just some examples of survival machines that decided to live this way. Additionally, birds fly in flocks, emperor penguins huddle together to escape wind and conserve heat, and sterile worker bees do backbreaking jobs so that their Queen has sufficient food and protection. It all looks like too much of a perfect theatrical act: it’s all designed, it seems, for the wellness of the group. This chapter will show us how these survival machines just seem as if they’re working for the good of the group but in reality they are just following the urges commanded by their selfish genes.

W.D. Hamilton, in a paper called “Geometry of the Selfish Herd“, introduced the concept of domain of danger. In his model this represented the hexagonal area surrounding each and every one animal in a given group that wonders the open landscape. Hamilton describes it as that area of the ground in which any point is nearer to that individual than than it is to any other individual. The smaller the area, the smaller the danger. Unsurprisingly the domain of danger of the animals at the edges of the group are much larger than of those at the center, so there will be a tendency for each animal to position itself in the center of the group. This of course leads to a more compact group, a herd.

The same theory can be applied to all kinds of wild life aggregations: bird that fly in flocks, fish that swim in schools, emperor penguins huddling together, they can all be explained using this simple model. The model says that your domain of danger can shrink or expand depending on your position relative to the group and on your behavior when predators approach. We should expect, therefore, that each individual survival machine will act in its own interest and will work to shrink its domain of danger. This, consequently, would lead to a more compact group. Chapter 10 analyzes this in more detail.

        Chapter 11: The structure of memetics and how it ties itself with its bio-mechanistic selfish ruler, the gene. A prior reading of Daniel Dennett’s Consciousness Explained might have made this chapter easier to understand, and easier to play with its premises. This chapter basically states that a new replicator has recently bootstrapped itself on the machinery created and used by the genes for their own survival. This machinery is the brain and the new replicator is called the meme. The meme practically represents the structure, the modeling, the ontology, the architecture of an idea. It must possess the same qualities as any other replicator: longevity, fecundity, and copying fidelity. How do they spread? With our help. Every idea that is appealing to us we tend to copy it by sharing it with others.

Why do some memes seem more sexy to us than others? Does us have any meaning if we arrive at the conclusion that we are just the set of memes that are cobbled together in our brain? First of all this second layer of replication, memetics, is very well tied to the first one, the biological; good memes are the ones capable of exploiting the first layer, manipulating it through the emotions which they are capable of spawning in the brain of the conscious observer. Good memes make themselves felt often and spread very easily in the brains of survival machines unbeknownst to their genes.

Unbeknownst, but unappreciative? That is what Richard Dawkins says, although he doesn’t provide any evidence for his opinion. Memes, just like genes, he argues, should act in their own interest and increase their numbers in the meme pool at the expense, if this is the case, of the genes that created their platform. Contrary to what Dawkins argues, we shouldn’t be so rampant at accepting this without further debate. If memes were allowed to ruthlessly develop into something that would have no evolutionary advantage to the genes that allow their unhindered sexing on the scene they created, consequently the later would die so there would be no platform for the memes to dance on. A mutual compatibility of interests must have evolved, which both the genes and the memes take advantage of, in order for them to exist now-days. And i should opine that we should have no middle ground here. We should not expect to find that in half the situations memes take advantage and genes lose, and the other way around. Instead we should expect that in the majority of situations the memes’ actions benefit both the genes and their own interest. The first level, the biological, the gene pool, must be given priority just because if it weren’t for it there would be no memes.

        Chapter 12: The case for the Nice Guy and the search for middle ground. The Prisoner’s Dilemma Game is a reliable tool used to model a simplified model of reality that fits well with the observed facts, and it helps the reader to render the possibility that selfish genes endow their survival machines with cooperation behaviors also, not only with ruthless selfishness. It’s smarter, as a survival machine that you are, to create social relationships based on mutual cooperation. More to this, it even pays more to develop these relationships with close kin because they share more genes with you.

So what is this game of Prisoner’s Dilemma? To keep the story short, and leave the bulk of your curiosity get satisfied by reading the book, it’s a game of behavior where acts of cooperation or defection, geared towards an individual or certain individuals, are assigned different points. These points are translated into nothing else but chances to survive and offspring brought to existence, or to put it more clearly into the numbers of genes that you increase or decrease in the gene pool. The exact architecture of the game practically tries to explain that a smart survival machine should try to cooperate with as much individuals as it can, but retaliate if those individuals refuse to do so.

A variety of strategies can be developed with a myriad of possible behavioral directions but the main point is this: Kind, cooperative, forgiving, but unable to be bullied or to be duped individuals will develop the ESS (Evolutionary Stable Strategy) that will be the most stable. Of course, there will be flip-flops between ESSs of cooperation and ESSs of selfish individuals, but the overall conclusion of the chapter is that kindness and altruism should, depending on certain constraints, be found in a multitude of situations. So, the Nice Guy but Wise Guy is to be found plentiful in nature.

        Chapter 13: The Extended Phenotype: The switch from clear to cloudy when you play the boundary drum. So, the past twelve chapters managed to convince us that the only entity worth paying attention to, from the evolutionary standpoint, is the gene, the real replicator, the only element that survives the passage of time. This last chapter tries to answer the questions of what is the purpose of organisms. Why do genes need them? Why don’t they bathe in some genetic soup similar to the primordial soup that covered the planet billions of years ago? Why bother with the extra complexity? This question, partly answered in the beginning of the book, is another story well covered in another of Richard’s books.

If i were to summarize this last chapter it would mean i would ruin the book review on The Extended Phenotype which this chapter is based on. If your read The Selfish Gene, which is just an introduction to the real informational juice, then reading The Extended Phenotype is an absolute must.

EPILOGUE: It doesn’t matter how many books you read, it only matters what books you read. If i were to list my Top Ten Must Reads of all time The Selfish Gene would certainly occupy a place in the first positions.