Common misunderstandings of
memes (and genes)
The promise and the limits of the genetic analogy to cultural transmission processes
Francisco J. Gil-White
fjgil@psych.upenn.edu ; http://www.psych.upenn.edu/~fjgil/
Assistant Professor of
Psychology
University of Pennsylvania
3815 Walnut Street, Suite 400
Philadelphia PA 19104-6196
Word Count: Abstract = 248 words; Main text = 12,313; References = 1,154; Entire Text = 13,903.
Short Abstract: ‘Memetics’ suffers from conceptual confusion and not enough empirical work. This paper attempts to attenuate the former problem by resolving the conceptual controversies. I criticize the overly literal insistence—by both critics and advocates—on the genetic analogy, which asks us to think about memes as bona-fide replicators in the manner of genes, and to see all cultural transmission processes as ultimately for the reproductive benefit of memes, rather than their human vehicles. A Darwinian approach to cultural transmission, I argue, requires neither. It is possible to have Darwinian processes without genes, or even close analogues of them. The cognitive mechanisms responsible for social-learning make clear why.
Long Abstract: ‘Memetics’ suffers from conceptual confusion and not enough empirical work. This paper attempts to attenuate the former problem by resolving the conceptual controversies, which requires that we not speculate about cultural transmission without being informed about the cognitive mechanisms responsible for social learning. I criticize the overly literal insistence—by both critics and advocates—on the genetic analogy, which asks us to think about memes as bona-fide replicators in the manner of genes, and to see all cultural transmission processes as ultimately for the reproductive benefit of memes, rather than their human vehicles. A Darwinian approach to cultural transmission, I argue, requires neither. It is possible to have Darwinian processes without genes, or even close analogues of them. The insistence on a close genetic analogy is in fact based on a poor understanding of genes and evolutionary genetics, and of the kinds of simplifications that are legitimate in evolutionary models. Some authors have insisted that the only admissible definition for a ‘meme’ is ‘selfish replicator.’ However, since the only agreement as to the definition of ‘meme’ is that it is what gets passed on through non-genetic means, only conceptual confusion can result from trying to make a hypothesis into a definition. This paper will argue that, although memes are not, in fact, ‘selfish replicators,’ they can and should be analyzed with Darwinian models. It will argue further that the ‘selfish meme’ theoretical calque imported from genetics does much more to distort than enlighten our understanding of cultural processes.
KEYWORDS: Cultural transmission, culture, evolutionary
genetics, meme, memetics, replicator, social-learning.
Given an incredibly simplistic notion of genes, memes are not in the least like genes. . .One problem with interdisciplinary work is that any one worker is likely to know much more about one area than any of the others. Geneticists know much more about the complexities of genetics than of social groups. Conversely, anthropologists and sociologists tent to be well-versed in the details of social groups. To them genetics looks pretty simple.—Hull (2000:46)
Many of the claims made about memes could be false because the analogy to genes has not proven productive.—Aunger (2000:8)
Introduction
Should we demand that ‘memes’ be exactly like genes if we are to apply Darwinian tools of analysis to culture? No.
The formal similarities between genes and what (after Dawkins 1989[1975]) are now called ‘memes’—the units of cultural transmission and evolution—suggest cultural transmission processes are ripe for Darwinian analysis. A vigorous debate is emerging over how to think about ‘memes’ (for a recent compendium of views see Aunger 2000). This is an evolutionary but also cognitive issue because memes are stored in human brains.
New fields will always use analogies and borrowed yardsticks, and these can be a source of fresh insights, but also cause misunderstanding. The yardstick which requires ‘memes’ to be essentially identical to genes if Darwinian analyses are to apply is a source of much confusion. This regrettable error is advanced by both critics and defenders of ‘memetics’ and—to boot—the specific arguments are often based on a poor understanding of genes and evolutionary genetics. The standard chosen is therefore not only erroneous but would indict evolutionary genetics as well (genes, it turns out, are not sufficiently like ‘genes’ either!).
There are too many insistent definitions of ‘meme’—typical in a new research program given that careers (especially in social science) are often boosted by getting particular definitions adopted. The prize is large because the term ‘meme’ is on everybody’s lips. If definitions were advanced only with conceptual progress in mind, this would be fine. But here, more than in other fields, the various protagonists must be aware that the contest is memetic, yielding a tendency to produce ‘catchy’ definitions that ‘sell well’ at the expense of conceptual advance and scientific utility.
The definition of meme as a ‘replicator’ is very catchy. Introduced by Dawkins (1989[1975]), and developed by Dennett (1995) and Blackmore (1999, 2000), it has helped mobilize our intuitions for population-driven processes involving genes, which are bona-fide replicators producing perfect descendant copies of themselves. As a heuristic device there is nothing wrong with this. But as a statement of what Universal Darwinism is—i.e. find a replicator, then apply Darwinism—it is a garden path. And a tortuous one. Consider that Blackmore (2000:26) says “memes are replicators,” but on the preceding page claims that, “As long as we accept that people do, in fact, imitate each other, and that information of some kind is passed on when they do, then, by definition, memes exist.” By definition? By definition ‘replication’ takes place when perfect copies are produced, not when “information of some kind [my emphasis] is passed on…” Proponents of memetics who uphold the ‘gene standard’ must weaken and mutilate the meaning of ‘replication’—which they take to result from ‘imitation’—in order to claim that memes are ‘replicators’ and that, since they are, Darwinism applies. They insist, therefore, not on the concept ‘replication’ but on the word, the use of which is assumed magically indispensable to the possibility of Darwinian science. But this is absurd.
Critics of memetics who also uphold this same ‘gene standard,’ on the other hand, stick closely to the definition of ‘replication’ as ‘perfect copying,’ and this is good (why butcher the language?). However, they fetishize the concept, for they accuse that the poor copying fidelity of memes—i.e. memes are not, after all, replicators—supposedly makes Darwinian analyses to culture inapplicable in principle. In my view, these critics, as much as the proponents, are chasing a mirage. Replication is not necessary for cumulative adaptations through selective processes (Boyd & Richerson 2000:153-158), and is therefore not the standard both critics and proponents are looking for. Replication is a red herring.
The ‘selfish meme,’ like its ancestor the ‘selfish gene,’ is another catchy idea. It answers the question cui bono? by saying that the unit being transmitted—the meme—is the ‘entity’ which ‘benefits’ in the cultural selective process. Again, this began with Dawkins (1983:109), who stated that a meme is “a unit of cultural inheritance…naturally selected by virtue of its…consequences on its own survival and replication,” and again developed by Dennett and Blackmore. In this picture “We humans. . .have become just the physical ‘hosts’ needed for the memes to get around. This is how the world looks from a ‘meme’s eye view’” (Blackmore 1999:8). In a manner parallel to the ‘gene’s eye view,’ we are here supposed to interpret every meme that succeeds at proliferating as having done so by dint of being well designed for proliferation. Cultural selection is reduced to the continuous editing of meme content until memes end up optimally designed for colonizing human brains. I will argue that only some rather specialized kinds of memes satisfy this analytical calquing from genetics to culture. But, again, this does nothing to wreck the applicability of Darwinian analysis or the usefulness of thinking in terms of memes—it merely indicts the fetishizing of the genetic analogy. Reducing cultural transmission to ‘selfish memes’ requires that we ignore much of social-learning cognition and miss most of the picture.
It should be obvious this far that I feel no compunction to accept Dawkins’ (1989), Dennett’s (1995), and Blackmore’s (1999) definition of ‘meme’ as selfish replicator. A recent compendium of views (Aunger 2000) makes it clear that neither do many others. It is best not to insist on a research program that rises or falls on whether memes defined as selfish replicators exist. That is a careerist semantic game that tries to assume or impose as a definition something that must be investigated, and such a game does not advance the science of cultural transmission—a science that will be carried out anyways because we must.
Most of us seem to accept the Oxford English Dictionary’s definition, which says: ‘an element of culture that may be considered to be passed down by non-genetic means.’[1] So ‘selfish replicator’ I will treat as a hypothesis about what the stuff that gets transmitted through non-genetic means is like. The relevant questions, then, are: (1) does this stuff look like a selfish replicator?; (2) If not, does this really make Darwinian analyses of culture impossible? Related questions are: (3) if they don’t replicate, is it impossible to find the boundaries of memes?; and (4) can we import from biology, willy-nilly, the ‘selfish gene’ idea? I will answer “no” to each of these questions. But I will still call what is transmitted culturally a ‘meme,’ and so—I will bet my house—will everybody else. The term ‘meme’ has already been selected for, so rather than forcing its meaning to coincide with a particular hypothesis about cultural transmission, let us do some science.
I.
What is required for genetic cumulative evolution?
Darwinian systems involve simple and blind algorithmic processes that nevertheless produce gradual accumulation of (sometimes very complex) adaptive design. They have three main requirements: information must be able to leave descendant copies (inheritance), new information should be routinely generated by some process (mutation), and there should be forces responsible for causing some items of information to leave more descendants than others (selection).
Genes satisfy all three. They are inherited through reproduction; new genes are routinely created because of occasional copying mistakes, or ‘mutations’, during DNA duplication; and a gene, through its effect on its carriers, affects the probability that it will increase in number. Thanks to selection and inheritance, when a particular gene causes increased reproductive success, more copies of it are passed on, and its relative frequency in the population increases (absent frequency dependent effects, eventually the whole population will have it). Thanks to mutation, new alternative genes get generated which occasionally amount to improvements, allowing the population to continue to evolve.
Cumulative genetic adaptations are possible because (1) genetic mutations typically introduce incremental rather than massive changes, and (2) the mutation rate for genes is low. It is these latter two requirements for cumulative evolution in genetic systems that inform some scholars’ intuitions that ‘replication’—that is, high-fidelity copying—is crucial to cumulative evolution through memes as well, which intuitions then damn Darwinian approaches to culture if memes are found not to replicate. For this reason these two requirements deserve further attention here.
Massive change is by definition the opposite of the accumulation of design, where each successive design change is a minor alteration on the margins of the previous template. But should we expect organic evolution to consist of small, incremental changes? Yes. The space of maladaptive designs is vast relative to the space of adaptive ones, so random changes to any current design (and mutations are random) are unlikely to cause adaptive improvements. Imagine that a monkey types a character at random as I am writing this essay. Will it improve? Without vanity, I can say that the chances are exceedingly low. A random typo is unlikely to yield English, let alone better English. But should the monkey press a key which launched a program to rearrange all of the letters in my essay, then he would be infinitely less likely to improve it—slim as his chances were anyway. In population-driven processes, for a novelty to last longer than an instant, it is typically constrained to cause a small modification.
Mutations must also be infrequent because, unless designs are relatively stable across time, we cannot get cumulative evolution. Suppose the offspring of A’s are mostly non-A’s. Even if A reproduces better than its competitors B and C, this cannot have an evolutionary consequence because the information responsible for A’s reproductive prowess is almost always lost after reproduction. On the contrary, if an A typically begets another A, then A’s higher reproductive success will soon make everybody in the population an A (absent frequency-dependent effects). Later, when a rare mutation results in a slight improvement to ‘A design’—let us call the new design A°—these A° mutants will outreproduce mere A’s and the population changes again (but only slightly).
This covers the intuitive basics of genes as replicators allowing for cumulative cultural evolution. But how similar to genes are memes? Well, memes certainly have the properties of inheritance, mutation, and selection. We constantly acquire and learn things from each other through social interaction, so in a broad sense at least it makes sense to say that the information I possess can create a ‘descendant copy’ in you (inheritance). People can make mistakes when acquiring information, and can also have stupid or bright novel ideas, which leads to new items of information (mutation). And some ideas are more popular than others, so they are copied more, stored longer, and rebroadcast more often, which in turn means they leave more descendants than competing ideas (selection). What makes some ideas more ‘popular’ than others are the properties of human social-learning psychology. This is not the only force acting to favor certain memes over others, but it is a very important one and I shall restrict myself to it here.
So much for intuitively stated formal similarities. The devil, as usual, lurks in the details. To many critics, the dangerous phrase above is “in a broad sense…information can create a ‘descendant copy.’” How broad? How similar must ancestor and descendant memes be?
Some assert that selectionist approaches cannot work because memes are not true replicators, making cumulative evolution impossible (e.g. Sperber 1996; Boyer 1994). Others, however, have not considered this a problem and proceeded to build Darwinian selectionist models that in their fundamental assumptions are quite similar to those used in evolutionary genetics, but adapted for cultural idiosyncrasies (e.g. Boyd & Richerson 1985; Lumsden & Wilson 1981; Cavalli Sforza & Feldman 1981; for a review, see Feldman & Laland 1996). As Laland & Odling Smee (2000:121) put it: “For us, the pertinent question is not whether memes exist. . .but whether they are a useful theoretical expedient.” Their critics, however, will counter that such models do not help us explain human cultural processes because the units employed are nothing like what exists in real-life cultural transmission. To find out who is right, we need first to examine closely whether it matters that memes are poor replicators.
II. Do memes mutate too much?
To Dan Sperber (1996), contagious pathogens such as viruses are a better analogy than genes for understanding the spread of cultural information. Populations of brains are infested in successive ‘epidemics’ of memes (which Sperber invariably calls ‘representations’—a favorite term in the cognitive literature). He cautions, however, that the analogy can be taken only so far.
. . .whereas pathogenic agents such as viruses and bacteria reproduce in the process of transmission and undergo a mutation only occasionally, representations are transformed almost every time they are transmitted. . .—Sperber (1996:25)
. . .recall is not storage in reverse, and comprehension is not expression in reverse. Memory and communication transform information.—Sperber (1996:31)
For example, does anybody ever retell a story exactly? No, and this is Sperber’s point.
In the case of genes, a typical rate of mutation might be one mutation per million replications. With such low rates of mutation, even a very small selection bias is enough to have, with time, major cumulative effects. If, on the other hand, in the case of culture there may be, as Dawkins [1976] acknowledges, ‘a certain “mutational” element in every copying event,’ then the very possibility of cumulative effects of selection is open to question.—Sperber (1996:102-103)
It is important to see exactly what the argument is. Genes are very stable across generations because they very rarely make copying errors during duplication—hence, for the most part, they replicate. As observed above, this allows cumulative genetic adaptations to emerge because small, cumulative changes can only be added if there is an overall template which remains—for the most part—stable. There is nothing absolute about the acceptable rate of mutation, of course. Rather, this is always relative to the strength of selection. For example, even if there is a moderate rate of mutation, cumulative evolution will still happen if the selective process culls suboptimal variants fast enough that the favored design is stable at the populational level, and from generation to generation. G.C. Williams (1966) made this principle famous in his definition of an ‘evolutionary gene,’ which is “any hereditary information for which there is a favorable or unfavorable selection bias equal to several or many times its rate of endogenous change.” This definition was taken willy-nilly by Dawkins and applied to his definition of the ‘meme,’ and recently stated very clearly by Wilkins (1998:8):
A meme is the least unit of sociocultural information relative to a selection process that has favorable or unfavorable selection bias that exceeds its endogenous tendency to change.
Sperber is accepting this move to assume (1) that ‘replicators’ are the things to look for; (2) that Dawkins’ reinterpretation of Williams gives the universal definition of a replicator, and (3) that Darwinian analyses will apply to memes only if they can satisfy this definition. In fact, Sperber eagerly forces the issue by ruling that any other conceptualization of ‘the meme’ is trivial (Sperber 2000:163). His stance is therefore that cumulative adaptations through cultural selection are possible only if we can find bona-fide cultural replicators. But memes in fact mutate in every single act of transmission, so he concludes that cultural selection cannot conceivably act fast enough because the meme’s dizzying rate of endogenous change creates a ceiling effect (Atran 2001 echoes this argument). Sperber therefore believes that we must understand how cognitive processes of information storage and retrieval cause mutations in particular and systematic directions. With this information, we can build (orthomemetic?) models of directed mutation rather than selectionist models (Sperber 1996:52-53, 82-83; 110-112) of cumulative change.
There is some irony in this. Hull (2000:47) quotes the above definition by Wilkins approvingly as a starting point for a science of memetics that he optimistically believes to be possible, although he fully expects “howls of derision” to come from unreasonable critics who will accuse this definition of not being sufficiently “operational.” Something very different has already happened, however! A prominent critic of selectionist approaches to culture—Sperber—has eagerly embraced that very definition in order to explain why selectionist approaches to culture are supposedly impossible.
It would seem as though either Hull or Sperber must be wrong, for they agree on how to define units of cultural processes that would be legitimately Darwinian, but they reach exactly opposite conclusions as to whether human culture passes or fails the test. However, I believe they are both mistaken because they are sparring on the wrong battlefield. The standard chosen, rather than enlighten, blinds us to the general requirements for a Darwinian system by insisting narrowly on the terms of one particular solution to them—the genetic one—as if this were the only possibility.
I shall accept Sperber’s point that the mutation rate for memes is 1: they mutate in every act of transmission. And I will agree, too, that often they are systematically biased. But this is neither here nor there. What matters is how big these mutations are, and how strongly biased in particular directions, as we shall see.
III. ‘Replication’ is a red herring
Sperber’s argument may seem intuitively appealing, but I think it is specious. Near-perfect copying fidelity is certainly important in genetic selection, but it is not a requirement for any Darwinian system. If the high rate of mutation is not the meme’s only distinction, then perhaps its other idiosyncrasies make it possible for regularly imperfect—or even invariably imperfect—meme-copying to support the emergence of cumulative adaptations.
I shall make the case with a toy example. But first, a few preliminaries. In genetics, a ‘locus’ is the physical location of a ‘gene’ on a chromosome. This is where the information ‘for something’ can be found. If we are talking about, say, the ‘eye-color’ locus, then the gene found there may be the ‘brown-eye’ gene, or the ‘blue-eye’ gene, and so forth. What is the analogue in memetic transmission? For example, imagine something like, say, a tennis-serve ‘locus’. Whatever is in your tennis-serve locus causes your behavior when beginning a new point in tennis. There are in principle a vast number of different behaviors that people could store at the tennis serve locus (just as there are many different sequences of nucleotides that may be stored at the chromosomal eye-color locus). Waving hello to your mom, or baking a bread, would be ruled illegal by the judges, but in principle this does not prevent you from storing such information at that locus (just as a random and useless sequence of nucleotides could, in principle, be stored at the eye-color locus).
It hardly matters that the tennis-serve locus may not be physically located in the same piece of brain for every individual. To insist on this is to push the genetic analogy to an absurd extreme where it begins to straight-jackets thought rather than inspire insights. The relevant and crucial similarity is functional, not physical: if individuals recognize that an item of information becomes relevant when, in a game of tennis, a new point is beginning, then the ‘cultural locus’ has all the requisite functional similarity to the genetic locus that we need. In cognitive terms, the cultural ‘locus’ is a tag plus retrieval function—it is a matter of categorization rather than physical location in the brain. The information retrieved at the start of a new tennis point is that which I tag as ‘tennis serve’. Waving to my mom or baking a cake have not been tagged this way (even though, in principle they could be), and, since they have not been, they do not compete to ‘occupy’ my tennis serve ‘locus.’ The true alleles of my current serve, therefore, are other behaviors which I also tag as ‘tennis serves’ because some individuals in the population perform them in the context of beginning a point in a tennis match. I may choose to acquire one of these later on, and in so doing will replace my current serve.
These obvious functional similarities readily dismiss the criticism that, because memes do not have the same kind of physical reality as genes, selectionist approaches to culture are a nonstarter. We are not talking here of the duplication of exact neuronal structures analogous to the duplication of exact nucleotide sequences in DNA, but we are speaking of the duplication of a certain behavior, understood to belong in a certain context, and in competition with other behaviors also understood to be candidates for the same context. The lack of similarity in the material basis of genes and memes is not a problem.
A. The right mix of stability and variation
To see whether a meme’s inability to properly replicate makes cumulative cultural adaptations are impossible, we must examine the full spectrum of theoretical possibilities.
Suppose that in our population, Bob’s serve is the most attractive, and seeing it performed gets people excited to make changes in their own tennis-serve loci. There is a continuum of different things that could happen, bounded by two extremes. At one extreme—replication—people acquire precisely the same content that is in Bob’s own locus. For example, you acquire the exact same top-spin service with a slight jump that Bob favors. At the other extreme—causation of random changes—people rewrite the information in their locus such that it typically bears no resemblance to Bob’s serve. Here, for example, you might ‘write’ into your tennis serve locus the idea that you should wave at mom when up to serve.
Please take note that I am not following the information in the brain here, although of course it is necessary for the process. What I am keeping track of here is the actual behaviors, and I am completely ignoring the question of what particular information content in the brain may be causing them. The latter is not always unimportant (Gil-White 2002a), but it does not concern me in the present analysis, and it is irrelevant to the points I will make. When I talk about ‘replication failure,’ what I mean here is the inability of the copier to perform a serve that is identical to Bob’s.
Let us look first at the causation of random changes. This will look silly, but we cannot gain the proper insights until we examine the full spectrum of possibilities. As silly as it sounds, suppose I put ‘wave at mom’ in my tennis serve locus after watching Bob’s top-spin serve. You will put randomly different, but typically equally dissimilar, information to Bob’s serve in your own tennis serve locus. What will happen? We are assuming that it is the content (i.e. the sequence of motions) involved in Bob’s serve that make it attractive, in turn precipitating changes in the tennis-serve loci of other people. Given this, I myself (who now wave at mom when I ‘serve’)—and all others who randomly changed the information at their tennis serve loci after watching Bob—are not similarly beacons of change; our new ‘tennis serves’ look nothing like Bob’s and they therefore get nobody excited (and mostly irritate the judge because they are not admissible). Bob’s serve has not become more common, nor has the mean serve of the population moved in the direction of Bob’s serve. Since evolution is about statistical changes in a population, the fact that this process does not produce reliable directional movement in the population’s mean serve implies that this process cannot lead to cumulative design changes. After all, the first requirement for cumulative adaptive design is the possibility of directional change.
Now consider the other extreme. This will look silly too. Here, watching Bob’s serve produces verbatim replicas in observers’ tennis-serve loci. People copy perfectly, so there is never any mutation—not ever. What happens? Because Bob’s is the most attractive serve, all of the people who now have Bob’s serve in turn become models for other people, who again copy the serve precisely and so forth. Bob’s serve spreads until everybody is serving identically. Here, too, selection cannot lead to cumulative design changes because the serves are all identical to Bob’s. The future will be spent forever more serving exactly like Bob, by everybody. No other serves will ever emerge because nobody ever makes a copying mistake.
We see that at either end—random changes, or perfect replication (100% copying fidelity)—there can be no accumulation of adaptive design. So this can occur only somewhere ‘in the middle’, where descendant changes are relatively similar to the ‘parent’ stimulus, but somewhat different. There are two ways in which this can happen: (1) descendant serves are always identical to the parent, except that every once in a long while there will be an accidental difference; or (2) the descendant serves are always accidentally different from the parent serve, but jump around relatively closely to the average of copying accuracy. In both cases we get more attractive future serves by making marginal changes to Bob’s, which in turn makes the marginally improved serve the new model (and this is what allows for cumulative adaptation). I examine each in turn.
(1) Copying involves mistakes only once in a long while. Here the information ‘written’ in a person’s tennis-serve locus is a pristine replica of the ‘parent’ serve. There is a very small probability of replication failure so, very rarely, a random modification results. Such modifications will typically make Bob’s serve less effective because a tennis serve is a complex behavior where many variables must be kept within narrow ranges to ensure success. I am assuming that only effective serves are attractive, and so most random changes will result in less attractive serves. But very, very occasionally, a random copying mistake begets a more effective—and therefore more attractive—serve, which then displaces Bob’s as people now begin making perfect replicas of the improved serve. Many iterations of this cycle will lead to ever better serves. I have just described a process of accumulation of adaptive design emerging from cultural transmission that is exactly parallel to cumulative genetic evolution by natural selection. Sperber (1996) claims that in order for selection to produce cumulative design in cultural transmission, the process should look like this. But let us take a look at a rather different process.
(2) Copying always involves mistakes, but around an average of perfect accuracy. This process is illustrated below in fig. 1. Every time somebody sees Bob’s top-spin serve, the goal is to copy it exactly, but there is always some error, and thus there is almost never a perfect copy. However, the errors are relatively small and not biased in any particular direction, so that Bob’s serve is obviously the template for all descendant serves. In this scenario, replication is the occasional exception. However, the population’s mean serve is still Bob’s, even if no individual serve is a true replica. The errors amount to a constant introduction of modest variations, from which a serve superior to Bob’s will emerge, and which then will become the new model serve—the new template to copy—for all of us. When that happens, this new serve becomes the new mean of the population, with a new cloud of error around it.
If we concentrate on the population mean, it is clear that cumulative design is taking place. This is not like genetic evolution by natural selection (where replication is very high fidelity), but it is certainly the accumulation of adaptive design due to selection (and it is faster than natural selection because variants are introduced in every copying attempt).
Fig. 1. Copying with modest errors. Think of the units in the X-axis as
being very small, so that the distance between the left-most bar and the
right-most bar is not too great—that is, we are assuming that all serves
produced are minor deviations from the target serve (which is Bob’s).
In the second case just considered replication rarely if ever
happens; the norm is replication failure. It is a good summary description of
the assumptions that go into many of the selectionist models that Boyd &
Richerson (1985) introduced in their approach. This condition of replication
failure as the norm is what Sperber claims renders cumulative adaptations from
cultural transmission impossible. But we have just seen that it is certainly
conceivable, and this lays bare that replication itself is a red herring. It is
neither here nor there. What cumulative adaptation requires is (1) sufficient
inaccuracy in the production of descendants such that superior variants can
occasionally emerge; and (2) sufficient accuracy that, at the populational
level (the mean), we can speak of meaningful, directional change (cf. Boyd
& Richerson 2000).
B. Mutations may have consistent biases
But what about directed mutation? This idea posits an attractor, created by a psychological bias, towards which serves will tend because the copying mistakes we make are on average in the direction of the attractor. That is, the mean of our copying errors will not be zero. Contra Sperber, this is still not a problem—at least not in principle.
The attractor could be anywhere at all, but we can get our bearings by again considering the two extremes, namely, (1) when the attractor is the optimally effective serve, and (2) when it is in a direction opposite to the optimally effective serve.
(1) The mutation attractor is the optimally effective serve. This case is illustrated below in figure 2. As before, suppose that every person tries to copy Bob’s serve exactly, but fails within a cloud of error with mean zero. A few people, however, can see forward to the kinds of modifications that would make Bob’s serve even better, and attempt these. This means that the actual mean ‘error’ for the whole population will be skewed by these innovators in the direction of the optimal serve. Does this prevent cumulative adaptive design? No. On the contrary, it speeds up the process that takes the population to the optimal serve because mutations in this direction are slightly more likely. The design is cumulative because foresight does not extend to the optimal serve itself, merely to slight modifications of observable serves that take them in that direction.
Fig. 2. Adaptive mutation bias. In this case the population mean is
closer to the optimum, after copying, than is Bob’s.
(2) The mutation attractor is in a direction opposite to the optimal serve. This case is illustrated below in figure 3. This could mean, for example, that there is something about the way it feels natural to move our bodies that makes us more likely to make errors in a direction away from the optimally most effective serve. But the phrase here is more likely. It doesn’t mean that copying errors in the direction of a better serve never happen. Thus, what happens is that the mean copying effort results in a serve somewhat lower in quality than Bob’s, but if the cloud of copying error occasionally produces a serve better than his, this serve will become the new target for copiers. This results in a new population mean that is again less good than the new target serve, but it is not less good than the previous mean serve in the population. Thus, the population mean will have moved closer to the optimal serve despite the fact that the mutation bias always makes it lag behind its current target.
Fig. 3. Maladaptive mutation bias. In this case the population mean is
further away from the optimum, after copying, than is Bob’s serve. However,
some copiers will make mistakes to the right of Bob, and since this yields a
better serve, it will become the model for the next generation.
Only when the attractor is so far away that it prevents the emergence of any variants better than Bob’s serve would the emergence of cumulative design be short-circuited, as shown below in figure 4.
Copying mistakes that result in improvements
Fig. 4. Overly strong maladaptive bias. Due to a strong mutation
attractor, the population mean is so far away from Bob’s serve in a maladaptive
direction that better serves practically will never appear.
The last example above shows that, when directed mutation occurs, it should be modeled together with selection. The direction of the system will then result from the algebraic sum of all the forces considered. We don’t have to decide whether either mutation or selection is the force to consider in our modeling exercises. For problems having the structure just considered, Sperber will be right that constant, directed mutation, prevents cumulative adaptation only if and when such mutation is (1) not towards the optimum and, (2) of sufficient strength. This is an empirical question, and it may be true for some domains and not for others. But we will not find the answer under the armchair.
But do we have empirical examples of cumulative cultural adaptations through selection? Yes. Other than tennis serves, we could name tennis racquets. In fact, we could name anything in the large domain called ‘technology’. Here design has obviously accumulated gradually. And even here Sperber’s dictum that replication is a limiting case rather than the norm is correct (except in the case of our very modern manufacturing techniques).
One can also point to institutions. Certainly institutions have been ‘constituting’ themselves on paper for a long time, but institutional organization pre-dates paper. Moreover, though the rules of an institution may be written, institutional behavior is always in the (sometimes very) flexible neighborhood of what is written down, rather than a rigid instantiation of it. In this sense—as living, breathing organisms—institutions are always imperfectly copied (for an example, consider that the Mexican political constitution is—on paper—almost a replica of the American, on which it was modeled). And yet institutions accrete cumulative changes. The evidence that they do so adaptively is in the incontrovertible fact that complex societies have outcompeted simple ones, and in the fact that different institutional arrangements have been the key to success in the competition between different complex societies (McNeil 1963, Landes 1998, Diamond 1997, Wright 2000). Technological and institutional change are not the only examples, merely the most obvious ones. But they occupy much of what is important in cultural evolution, so they make the case that selectionist approaches will be quite significant to explaining culture.
Given that cumulative cultural adaptations don’t require memes to replicate, this was not the litmus test for Darwinian analyses to culture. And if my critique of gene-analogy fetishism among the critics of ‘memetics’ is acceptable (for a mathematical demonstration of my core arguments, see Henrich and Boyd 2002), it simultaneously refutes the arguments of proponents such as Dawkins, Dennett, and Blackmore, who fetishize the alleged importance of ‘replication’ for opposite reasons.
IV. ‘Imitation’ is another red herring
A related point can be made about ‘imitation’ (i.e. what we do when we copy Bob’s serve). Blackmore insists on imitation as the memetic process. But she would like to consider a narrative, for example, a ‘meme.’ And yet, narratives are not transmitted by imitation. Blackmore (1999:6) gets around this by corrupting the meaning of ‘imitation’ just as she did with ‘replication’:
Dawkins said that memes jump from 'brain to brain via a process which, in the broad sense, can be called imitation' (1976:192). I will also use the term 'imitation' in the broad sense. So if, for example, a friend tells you a story and you remember the gist and pass it on to someone else then that counts as imitation.
With such a loose definition of ‘imitation,’ a reader such as myself cannot understand what standard Blackmore upholds when she insists that ‘imitation’ is what identifies the subject matter of ‘memetics’ (cf. Plotkin 2000:76-77).
But this is another red herring anyway. We need a handle on the social-learning cognitive mechanisms which, in combination with individual-learning processes, are responsible for affecting the distribution of memes (cf. Plotkin 2000; Laland & Odling Smee 2000). Imitation is important, but we don’t need to fixate on it. Different domains will involve different processes and will need mid-level theories particular to them, but “In every case the Darwinian population approach will illuminate the process…” (Boyd & Richerson 2000:144).
The imitation of a motor act, the acquisition of a native language, and learning one's culture-specific social constructions have different developmental trajectories. . .Each is based on different psychological mechanisms. It is almost certainly the case that the characteristics each displays in terms of fecundity, longevity, and fidelity of copying are also different in each case, and different precisely because each is based on different mechanisms. The suggestion that “we stick to defining the [sic] meme as that which is passed on by imitation” Blackmore (1998), if taken literally, is an impoverishment of memetics for reasons of wanting to maintain copying fidelity.—Plotkin (2000:76)
The insistence on imitation, as Plotkin suggests, comes precisely from this obsession with replication (copying fidelity). Imitation, narrowly (i.e. properly) understood, is the mechanism that strikes some observers, Blackmore included, as closest to the production of carbon copies. So they insist on the word ‘imitation’ because it confers the cachet of ‘replication,’ which in turn supposedly grants in exclusivity the legitimacy to undertake Darwinian analyses. Absurd.
And here again, the critics of ‘memes’ agree with this fetishism of ‘imitation’ only so they can reach the opposite conclusion. Atran (2001) in a section title, says, “No Replication without Imitation; Therefore, No Replication” (because there is no real imitation), and thus—absent replication—no applicability of Darwinian selectionist analyses to culture. This is hardly better, and refuting Blackmore’s error is simultaneously to refute this one. If imitation and replication are neither here nor there when it comes to establishing a litmus test for the possibility of a Darwinism of culture, then one cannot reduce one’s advocacy or skepticism of this project to whether there is or isn’t imitation and/or replication.
It is true that some cultural transmission scholars have made
much of ‘imitation’ (e.g. Boyd & Richerson 1985, 1996, 2000; Tomassello et
al. 1993), and they have stressed its indispensability to cumulative
cultural evolution. Less misunderstanding would result if they said imitation
was the ability which initially set humans along the path of cumulative
cultural change, and that other tricks have since become possible (it is not a
coincidence that when the above authors stress imitation they are comparing
humans to nonhumans). For example, I have recently argued that language became
possible when imitation led to the emergence of prestige hierarchies (Gil-White
2002). But this emergence of language now makes prestige-biased transmission
often a process of influence that pushes attitudes back and forth along
a continuum, rather than imitation (Henrich & Gil-White 2001). Another
example: narratives can accrue cumulative changes through selection, and I
doubt that Robert Boyd, Peter Richerson, or Michael Tomassello will disagree.
But narratives don’t spread through imitation, even if the evolution of
imitation was necessary for the emergence of language, which is indispensable
for narrative. We must distinguish the phylogenetic indispensability of
imitation from its current importance in cultural transmission.
V. Platonic inferences
So far I have ignored the following problem: although individuals do not make replicas of the memes they try to copy, they do try to. However, what could their target be? After all, our tennis player, Bob, never replicates his own serve perfectly either! Bob’s performance is itself a cloud of error around a mean. So copiers must be abstracting an ‘ideal Bob serve’—which they try to emulate—from Bob’s performances. Sperber (1996:62-63) dismisses this as ‘a Platonist approach’ (indeed Plato would have liked the argument that we strive to copy not the thing we see, but its ‘essence’, as we infer it, so to speak). To Sperber, formal properties cannot be causal.
I believe the opposite. It makes perfect sense that we infer and abstract an ‘ideal’ serve as Bob’s goal, and then strive for it. For evolution to have designed our social-learning psychology otherwise would not have been adaptive, given that the performances of the people we copy are statistical clouds (cf. Dennett 1995:358; Dawkins 1999:x-xii; Blackmore 1999:51-52; Boyd & Richerson 2000). In a selectionist model it is therefore perfectly valid to define ‘the meme’ as the abstraction for which Bob strives, and to track the population mean as people try to copy this abstraction. I do not agree with criticisms that selectionist models have illegitimately relied on assumptions of discrete memes (Atran 2001), or that “the notion of replication certainly is one idealization too many for models of cultural transmission” Boyer (1998). The problem being modeled will determine whether the simplification is legitimate, and many such models actually include copying error as a parameter anyway.
However, there is no question that there is an important role here for cognitive psychology and anthropology. We need a better understanding of how the brain decides which aspects of a performance are important and which irrelevant. Understanding such cognitive filters will tell us, for a particular domain, what is the ‘meme’. But not having yet a good handle on such things is no obstacle (pace Atran 2002:ch.10) to current selectionist models (review in Feldman & Laland 1996) for these are concerned with the formal, emergent properties of Darwinian systems that, by assumption, are capable of cumulative adaptation, rather than with the histories of any specific, individual memes. As such, they teach us how to think about cultural evolutionary processes involving broadly specified types of (relatively abstract) memes, and the long run properties of dynamic systems having two interlocking systems of inheritance: genetic and cultural. What I have tried to do here is show that the assumption of selectionist models—that cumulative adaptation is rampant in cultural transmission—is a very reasonable assumption.
VI. What are the boundaries of ‘a meme’?
Some critics (e.g. Atran 2001) accuse that memes don’t have well-defined boundaries, but even “well-disposed” anthropologists can’t see where to draw them. Maurice Bloch (2000) expresses his misgivings as follows:
As I look at the work of meme enthusiasts, I find a ragbag of proposals for candidate memes, or what one would otherwise call units of human knowledge. At first, some seem convincing as discrete units: catchy tunes, folk tales, the taboo on shaving among Sikhs, Pythagoras's theorem, etc. However, on closer observation, even these more obvious 'units' lose their boundaries. Is it the whole tune or only a part of it which is the meme? The Sikh taboo is meaningless unless it is seen as part of Sikh religion and identity. Pythagoras' theorem is a part of geometry and could be divided into smaller units such as the concept of a triangle, angle, equivalence, etc.
Bloch has rather quickly pronounced defeat. These problems are hardly insurmountable, and they are not any different from similar conceptual problems faced in evolutionary genetics.
What is ‘the meme’: the whole tune or only part of it? A Darwinian unit is of whatever size selection favors. This is why in evolutionary genetics Dawkins (1983:87-89) doesn’t like to insist on the gene as a cistron (‘start’ codon to ‘stop’ codon). He is right. The cistron is more useful to molecular biologists. A tune, just like a cistron, has a starting point and an ending point, and, just like a cistron, this is a matter of performance, not selection. For the tune, a musical performance; for the cistron, the construction of a polypeptide chain. Our intuition that the whole tune is a unit does not come from an analysis of what people can remember and what they rebroadcast, about what spreads and doesn’t spread, but rather from our understanding of the conventions of musical performances. That the whole tune is a unit of performance does not make it a unit of selection.
The key point is that there are memes about which things to perform, and how much of them to perform, and these are of a different kind, and are found at different cultural ‘loci,’ than the loci which store tune fragments. At one cultural ‘locus’ we find beliefs about which piece should be played compete. This locus can house a finite number of such beliefs; ‘Beethoven’s 5th deserves to be played’ has consistently triumphed in securing a spot in it. Another locus is where memes compete to specify how much of a piece should be played. Here the belief ‘play a piece from beginning to end’ has fared well against competitors. Thus, it is because these two memes are successful in their respective loci that Beethoven’s 5th is played often and in its entirety—not because the symphony itself is encoded whole in the heads of listeners! What listeners remember of the piece is stored in yet another locus where tune-fragments compete to be remembered. For the most part, only the opening theme survives (it is very catchy).
That these loci are independent (though not unrelated, of course) is made evident by the fact that very catchy but tiresome pop-tune fragments will get remembered so easily that the preference for the entire song not to be played will spread (at least after the initial success of the song in question). It is thus possible for the tune-fragment, on the one hand, and the negative preference for the song which contains it, on the other, to be simultaneously at high frequency, and remain so for a while. Try and see if you can forget ‘The Macarena’ (and tell me honestly whether you would like to hear it played). Of course, for such a tune-fragment to persist across the generations, a reasonable fraction of people must preserve the belief that the piece which contains it ought to be played. The opening theme to Beethoven’s 5th will probably continue to make it, but my future children will never know ‘The Macarena’.
What we have discovered here is that for a meme to spread—here, the opening theme to Beethoven’s 5th—it needs a favorable ecology of other memes at other loci (for example, ‘Beethoven’s 5th deserves to be played’; the memes necessary to play a violin; the meme that violinists should be paid; etc., etc.). This discovery looks a lot like an earlier discovery: that any gene cannot hope to prosper unless it is surrounded by a favorable ecology of genes at other loci in its own organism, and also in the ecology of phenotypic effects of other organisms’ genes. What else is new? If this discovery does not hurt the possibility of population analyses in biology, why should it be fatal for culture?
Yes, the Sikh taboo is more likely to spread and remain stable in an ecology of religious memes that are congruent with it. Yes, Pythagoras’ theorem cannot be learned without first possessing the meme that says what a triangle is. But neither can the gene for reciprocity spread, for example, unless there are genes already for, say, social aggregation. None of this is new, or especially difficult.
Another vexing problem raised by the question “what are the boundaries of ‘a meme’?” refers to the level of abstraction. When somebody tells me a story, and I retell it, I will never give a verbatim rendition of the story I heard. Many of the details will change. There are good reasons to think that most of the details are not even stored in memory (Schank & Abelson 1995). I can feel the critic pouncing: “Aha! There is no stability!” But at what level? Suppose that the skeleton of the story is very stable. If so, the fact that story details are not even encoded in the listener’s brain—and therefore change radically from version to version—is as worrisome to Darwinian analyses in culture as silent mutations in the DNA code are to evolutionary genetics (i.e. not at all). What we need to keep track of is the story skeleton. Changes there will be the real mutations. I shall ignore further development of this point here as I will soon give it an article-length treatment (Gil-White, in prep.).
VII. Meme ‘content’ is not everything
Recently, Sperber (2000) makes a concession to the point that we make Platonic inferences but then insists that these are almost always triggered rather than bootstrapped. Atran (2002, 2001, 1998), and Boyer (1998, 1994) make essentially the same point.
The argument is that observation produces ‘inferences’ which are
best described as the triggering of a pre-existing knowledge structure. Sperber
(2000:165-66) gives the example of language, interpreted from a Chomskian point
of view, “where language learners converge on similar meanings on the basis of
weak evidence provided by words used in an endless diversity of contexts and
with various degrees of literalness or figurativeness.” From this it follows,
he says, that language learning is much more about triggering pre-existing
knowledge than bootstrapping new knowledge. Rather than stable and discrete
memes competing with each other in a selective contest, goes the argument,
memes will mutate quickly and fuzzily, and morph inexorably into the shape
favored by a content-bias ‘attractor,’ which is specified by our innate cognitive
endowment.
Not everything is like that, Sperber admits. “Learning to tap dance involves more copying than learning to walk,” but, he insists, “For memetics to be a reasonable research programme, it should be the case that copying [as opposed to the triggering of pre-existing knowledge], and differential success in causing the multiplication of copies, overwhelmingly plays the major role in shaping all or at least most of the contents of culture.” But it doesn’t, he claims. Rather (as if this were an alternative!) he claims that “the acquisition of cultural knowledge and know-how is made possible and partly shaped by evolved domain-specific competencies…”
In my view Sperber sets up a straw man—a false test—for several reasons. First, because, as noted above, he is asking us to choose between complements rather than between alternatives.
Second, because, for a great many domains the triggering of inferences makes a rather different point. Our toy example will assist us here too. As observed earlier, learning Bob’s serve requires that we abstract his goal from his statistical cloud of performances. This is an inference, sure, and it relies on “pre-existing knowledge” too. But knowledge about what? Primarily, about the purpose of a serve in a game of tennis. In other words, knowledge that does not come from an innate, domain-specific module as Sperber would have it, for the brain of a human hardly comes prepared to trigger “tennis” (and many people around the world don’t play it). An important form of cumulative bootstrapping takes place already merely in the fact that the rules of tennis need to be understood first in order properly to infer the specific thing that Bob is going for when he serves. There is no straightforward or absolute reduction to the triggering of innate modules here.
Third, because Sperber’s linguistic example is not even that good. Although there is undoubtedly much innate knowledge dedicated to the bootstrapping of language, a model that reduces linguistic historical processes to nothing more than triggering of innate knowledge can never explain how Indo-European became Hindi but also Spanish.
Fourth, because Sperber’s test is unfairly asymmetric. In his formulation, the mechanism he does not favor—the copying of knowledge—must be “overwhelmingly” dominant, but his favored explanation need only be “partly” responsible for his prescriptions to be the most sound. Tails, he wins; heads, we lose! We hardly need this.
Finally, even should we grant all of Sperber’s assumptions and accept that all attractors will be innate, and that there will be attractors for everything, he is still wrong. Henrich & Boyd (2002) show that so long as more than one attractor can exert influence over a given meme, and the attractors are strong relative to selection pressures, the dynamics quickly become a contest between the discrete alternatives favored by each attractor, engaged in a selective contest. So even here the fuzzily-morphing-into-the-attractor model is not right—selection still happens.
A. Non-content biases and their importance
The last line of defense for Sperber would then be that, even so, the contest is all between innate attractors and so one cannot expect cumulative cultural evolution acting on arbitrarily varying memes. Atran (1998) and Boyer (1998) agree with this view that transmission is mostly about moderate variations around ‘core memes,’ which are strongly constrained by innate mental biases that focus on a meme’s content. A related view has stressed that the main causes of ‘triggered inferences’ will be local non-cultural environments (e.g. Tooby & Cosmides 1992), so cultural differences reduce to the environmental conditions surrounding the various local human populations. Others, however, argue—not in stead (content biases are important too) but in addition—for the importance of non-content biases that allow arbitrary differences to spread and remain stable (Boyd & Richerson 1985; Henrich & Boyd 1998; Henrich & Gil-White 2001; Gil-White 2001a, 2001b).
To see why we believe in the rampant spread of arbitrary differences, we must describe the relevant social-learning cognitive biases. Assume that Bob is your hero because he is a great tennis player. Bob likes a Wilson racquet. What do you do? Buy a Wilson racquet. Bob wears leather pants; you buy leather pants. Or suppose everybody in your high school class is getting leather pants. What do you do? Get leather pants (you don’t want to look like a deviant). In these examples you acquire the meme not because the meme itself captivates you; what seduces you are the contingently associated features: the meme’s source, or its relative frequency. In these observations lies a key—and very misunderstood—virtue of the selectionist approach pursued in the tradition pioneered by Boyd & Richerson (1985): the importance of ‘non-content’ transmission biases.
The memes that do well and spread widely in a population are those which, for whatever reason, the human brain has a ‘taste’ for. But, as seen above, some of these ‘tastes’ may have nothing to do with the actual content of a meme (what the meme actually ‘says’, ‘prescribes’, or makes people do). Of course, many biases involved in social learning will focus on a meme’s content. Boyd and Richerson call these ‘direct biases’ (and I am calling them ‘content biases’). However, as students of culture from an anthropological perspective, they have devoted much attention to the long-term consequences of non-content biases that can cause the accumulation of arbitrary differences between societies. The non-content biases relevant to this problem are conformity bias and prestige bias.
Much research in social psychology suggests that humans have biases to prefer memes that are common relative to competing memes at a particular cultural ‘locus’ (Miller and McFarland 1991; Kuran 1995; Asch 1956, 1963[1951]). Boyd and Richerson (1985:ch.7) and Henrich & Boyd (1998) give models to explain the adaptiveness of informational conformism as helping individuals pick up useful memes that others have already converged on. Gil-White (2001a) argues that interactional-norm conformism is adaptive because it gains the conformist the maximal number of potential interactants.
Boyd and Richerson have also speculated (as indeed have many others) that prestigious individuals are copied more often than others, and Henrich & Gil-White (2001) recently took these speculations and developed a lay model to explain the evolution of such a cognitive bias, reviewing also the evidence for it extant in the social-scientific literature. We argue that prestige-bias is adaptive because successful individuals (i.e. with better memes) tend to have prestige.
These two biases care nothing about content: conformity bias cares about relative frequency, and prestige bias about source. As far as these biases are concerned, the memes could be ‘about’ anything at all. Thus, in domains without strong content biases, we should see the following effects. First, the memes of prestigious individuals will tend to become more common, but these will be unpredictably different for people in different communities given that every individual has an idiosyncratic life history (e.g., I, but not you, may fall off the horse after washing my feet in a stream, and conclude superstitiously that the stream was somehow directly responsible), and such differences will be larger between members of different communities (even if we both fall of our horses after washing in the stream, I am more likely to come up with the idea if my group already believes streams have supernatural powers). This sort of process will engender arbitrary differences between societies.
The second effect is that, once common, conformity will keep such memes at high frequency in a community as large as the sample for the conformist bias. This will keep such arbitrary differences between societies stable generation after generation. Such differences in turn become acquired ‘content biases’ on future evolution.
The conformist and prestige biases therefore offer themselves as an appealing joint explanation for the different historical trajectories which have caused dramatic variation among the world’s cultures. (Drift can also act to bootstrap arbitrary differences to frequencies high enough for conformity to kick in and stabilize them.) Together they can explain why two populations living in the same environment could become quite different, culturally—something that happens all the time.
B. Don’t reduce everything to ‘content’
The issue of cultural variability has been an anthropological concern throughout the 20th century, and it has led to the theoretical excess of ‘cultural relativism’, which holds that human brains are—for any and all purposes—blank-slates upon which a local culture can write literally anything at all. That this is false should have been obvious (but it hasn’t been). But perhaps some anthropologists are now guilty of overreacting in claiming that the blank-slate view of culture is always wrong.
The picture of the human mind/brain as a blank slate on which different cultures freely inscribe their own world-view. . .[is] incompatible with our current understanding of biology and psychology.
. . . the brain contains many sub-mechanisms, or ‘modules’, which evolved as adaptations to. . .[ancestral] environmental opportunities and challenges (Cosmides & Tooby 1987, 1994; Tooby and Cosmides 1989, 1992) [and]…are crucial factors in cultural attraction. They tend to fix a lot of cultural content in and around the cognitive domain the processing of which they specialize in.—Sperber (1996:113)
Other anthropologists in this tradition have expressed similar views in the process of exploring some interesting content biases as the reason for the widespread recurrence of certain memes. For Boyer (1994) these are certain religious ideas; for Atran (1998) concepts of living-kinds; and for Hirschfeld (1996), intuitions about so-called ‘races’. These are all valuable enterprises, but these authors seem to think that the discovery of these content biases amounts to a refutation of the possibility of acquiring any unconstrained memes (Boyer 1998), and therefore a refutation of the possibility of stable, arbitrary differences between cultures (Hirschfeld 1996:21-22), which in turn implies a refutation that such nonexistent differences could lead to cultural group selection (Atran 2002:ch.10). One should not conclude that finding content biases in some domains excludes the possibility of arbitrary differences in other domains without strong content biases. Sperber seems to present the issue above as an either/or question: the brain is not a blank slate, therefore cultural content is fixed around the cognitive domain of our evolved biases. But we must adjudicate this on a domain-by-domain basis. The blank-slate assumption may in fact be a reasonable approximation in a great many domains.
With a different slant, Blackmore (1999) and Dennett (1995) also argue for the primacy of content, but they place the focus on the meme, rather than on innate psychology. Cultural evolution is here a selective process that makes memes increasingly better propagators. As Dennett (1995:362) puts it,
Dawkins (1976:214) points out that ‘…a cultural trait may have evolved in the way it has simply because it is advantageous to itself.’ (…)
The first rule of memes, as for genes, is that replication is not necessarily for the good of anything; replicators flourish that are good at…replicating—for whatever reason!
Memes that ‘look’ like what the brain ‘wants’ will spread even if they lack the effects that the brain is adaptively ‘hoping for’. This is valid, but the emphasis on content as such is overplayed. Dennett and Dawkins suggest that the only thing affecting a meme’s spread is whether the meme itself is good at replicating, and that selection will successively edit the meme’s content so that it is ever better at replicating. This is the ‘meme’s eye view’: only the properties of a meme (i.e. its content) determine its spread. But a meme can be lucky. It can happen to find itself in the head of a prestigious person, or, thanks to prestige-bias bootstrapping (or even random drift processes), it may find itself at high frequency through no ‘fault’ of its own. In both cases the meme’s content takes a back seat. In fact, the meme may be favored despite its content. This means that prestige-biased and conformist transmission are excellent explanations for why some maladaptive memes spread and remain stable, even when the memes themselves are not good at replicating. I hardly think that Dennett’s ‘first rule of memes’ is a rule at all, let alone the first. It is in no way necessary as an all-encompassing perspective on the processes involved in cultural transmission.
I am hardly alone in making this criticism (e.g. Conte 2000:88; Laland & Odling Smee 2000:134; Boyd & Richerson 2000), and I am hopeful that the authors criticized here can be convinced. After all, Atran (2002:ch.10), partially acknowledges that “from a cognitive standpoint, some cultural aspects are almost wholly arbitrary.” Boyer (1998) recognizes the importance of prestige bias, and Sperber (1996:90-91) explicitly recognizes its power to generate arbitrary differences between societies. Meanwhile, Blackmore (1999:ch.6) talks about source biases that I don’t believe exist (e.g. ‘imitate the good imitators’) but which, as source biases, should undermine her view of meme-selection as solely the result of meme content. Dawkins (1999:vii) starts his introduction to Blackmore’s book by describing prestige bias. And Dennett and Dawkins are clearly aware of frequency-dependent effects such as conformism (Dennett 1995:352). Following these authors’ own observations about non-content biases to their logical conclusions entails that arbitrary differences between cultures are not only possible but likely, and to the extent that they are stable they generate selection pressures at the group level (Boyd & Richerson 1985:ch.7; Henrich & Boyd 1998).
We can now closely evaluate the sometimes facile claims made about memes, whether by proponents or critics. Susan Blackmore (1999, 2000) has recently become the most outspoken proponent of the notions I have just criticized, although the main points are owed to Dennett (1995) and also to Dawkins (1989). Her most pithy formulation, and the one that makes all of her intended links, is the following (Blackmore 2000:26):
…memes clearly vary and therefore fit neatly into the evolutionary algorithm. In other words, memes are replicators. The importance of this is that replicators are the ultimate beneficiaries of any evolutionary process. Dennett (1995) urges us always to ask cui bono? or who benefits? And the answer is the replicators…
I believe every link in this argument to be mistaken. Blackmore begins by saying that it is because memes vary that they fit into the evolutionary algorithm. But this is false. Grains of sand vary, and they do not fit into the evolutionary algorithm. Memes fit into the algorithm only if they vary and remain reasonably stable in the process of transmission. If mutation were both infinite and infinitely random, then “what is passed on in imitation” (how Blackmore [2000:25] defines memes) would certainly vary but they could not be analyzed with Darwinian tools.
Second, Blackmore says that because memes fit into the evolutionary algorithm, they must be replicators. This again is false. Units can fit into the evolutionary algorithm even if they don’t replicate, as I have argued with the example of Bob’s tennis serve. Boyd & Richerson (1985:ch.3) already demonstrated long ago that this is true even for the case of blending inheritance (though nobody ever takes notice). Recently, Henrich & Boyd (2002) provide another demonstration of why replication is a red herring.
Third, Blackmore argues that because memes are replicators, and since “replicators are the ultimate beneficiaries of any evolutionary process,” our analyses must always be in terms of how the memes benefit. False again, as shown by the existence of non-content biases. But this last argument of Blackmore’s is so ‘sexy’—it is responsible for most of the attention which her work, and the preceding work of Dennett and Dawkins has received—that it is worth a thorough refutation, which I turn to next.
VIII. Memetic Drive—the ‘meme’s eye view’ gone mad
Can we reduce everything ultimately to the interests of ‘memes’? Blackmore (1999:8) says that “We humans. . .have become just the physical ‘hosts’ needed for the memes to get around.” But this would mean that, just as a chicken is an egg’s way of making another egg (the ‘selfish gene’ perspective), a brain is just a meme’s way of making another meme (the ‘selfish meme’). But lest anybody forget, genes have something to do with making brains!
The problem here is that ‘ultimate’ is not as definite a concept as Blackmore might like to imagine. Since, in the long run, as the economists say, we are all dead, we must specify the time-scale for any evolutionary problem. Human brains are under selection pressure to develop genetically specified meme-catching biases that filter out maladaptive memes and zero-in on adaptive ones, and this means that genes and memes are caught in an interactive, historical feedback process—what Boyd & Richerson (1985) have called ‘dual inheritance.’ Even when Blackmore (1999) talks about dual inheritance, however, she is fond of reducing everything to memes, including the mind. This is her concept of ‘memetic drive’ which is supposedly her most radical idea (Aunger 2000:11), and which underlies most of her arguments about what ‘memetics,’ conceived as the study of selfish replicators, can explain:
Genes are instructions for making proteins, stored in the cells of the body and passed on in reproduction. Their competition drives the evolution of the biological world. Memes are instructions for carrying out behavior, stored in brains (or other objects) and passed on by imitation. Their competition drives the evolution of the mind.—Blackmore (1999:17)
On the one hand we have the brain, a biological organ, specified by genes. Blackmore recognizes that competition among genes is responsible for the features of biological organs, so one may hazard that by ‘mind’ she cannot simply mean ‘brain’. But if so the best we can do is say that ‘mind’ is the set of interconnections that end up instantiated in the brain at the end of some developmental process which involves cultural inputs. In other words, the mind is partly a bunch of memes—partly, because not everything that ends up instantiated in the brain is acquired socially, as some of it is innately given.
To make the best case for Blackmore’s argument, let us artificially restrict ‘mind’ to “connections that result from the social acquisition of information.” Can we now say that competition among memes drives the evolution of the mind in the same way that competition among genes drives the evolution of the biological world? Yes. If we define ‘mind’ as whatever memes end up in a brain, then, tautologically, competition among memes drives the evolution of minds. The tautology is not entirely useless because the meme concept emphasizes Darwinian processes that have been neglected. But it is better to say it without a tautology which, to boot, requires a new technical definition of ‘mind’ (though I understand this is another sexy term with magical properties). Better to say: “short term cultural evolution is the product of competition among memes because a ‘culture’ is a distribution of memes.” Is this a truly new or radical argument? Certainly not by the standards of cultural transmission theory, relative to which Blackmore (1999:15-17) believes she has advanced so much that her ideas are in fact christening an entirely new and autonomous discipline which has yet to begin.
But perhaps my translation was not adequate, and Blackmore has
something else in mind. Perhaps by ‘mind’ she really does mean ‘brain.’
In chapter six of her 1999 book she actually argues that memes selected for big
brains to serve their own—the memes’— ‘interests’ (what she calls ‘memetic
drive’). In other words, the ‘interests’ of memes set processes in motion that
select for genes, which in turn code for brains that prefer those same memes. A
brain is just a meme’s way of making another meme.
This is radical but wrong. A meme cannot select for a gene unless it is widespread (meta-populationally) and stable (inter-generationally). But there are only two avenues for such a widespread and stable meme to emerge. In the first, the meme is selected by an innate ‘content bias’ in the brain’s design, making it widespread and stable. But for Blackmore this is a catch-22, because what puts the meme in a position to select for the gene is the fact that this same gene evolved first.
The second avenue is if a process such as group selection through conformist transmission (Boyd & Richerson 1985; Henrich & Boyd 1998; Boyd & Gintis, in prep.) makes a meme widespread and stable, even though there was originally no innate content bias to prefer it (e.g. some form of altruism). Suppose that, once common, it is costly not to acquire this meme, or else it is costly to do so slowly or with errors (for example, suppose that the meme to punish non-altruists has also spread in this fashion). In such a case genes coding for an innate content bias specific to that meme will be favored (here, genes for altruistic tendencies), and we may say that the memes have selected for the genes in a Baldwinian process.
This can certainly work, but it is not radical by the standards of cultural transmission theorists, some of whom have been pushing this sort of argument for years (e.g. Boyd & Richerson 1985), and it also does not, as Blackmore claims it does, put the memes in the “driver’s seat” to the detriment of the ‘interests’ of the genes when it comes to brain design. Much less does it call for an entirely new discipline.
One must not confuse the true statement that competition among memes—the replicative ‘interests’ of memes—is what causes (short term) cultural evolution, with the false statement that the replicative ‘interests’ of memes—against the ‘interests’ of genes—drive the longer-term process of brain design. The brain cannot be designed against the ‘interests’ of genes simply because those genes have to be selected for, and they cannot be selected for without differential reproductive success! Thus, when memes select for genes it will be only because the ‘interests’ of memes and genes coincide. Granted, they may only coincide after the meme has become widespread (and this is very interesting), but they will still have to coincide. And a coincidence is just that—it is not a radical “turning of the tables” on our understanding of what shapes brains, as Blackmore would have it. The design of the brain will still be about biological reproductive success in the environments that selected for this design, not for the propagative success of memes in the absence of a biological instrumentality. Let us stop worrying about non questions based on false observations, such as “We seem to have a brain ‘surplus to requirements, surplus to adaptive needs’ (Cronin 1991:355),” and, “. . .our abilities are out of line with those of other living creatures and they do not seem obviously designed for survival” (Blackmore 1999:67-68).
Conclusion
I conclude by listing the morals. The first is that we need not narrowly genetic Darwinian thinking, but a ‘population thinking’ attitude that considers—in its own terms—the properties of statistical populations capable of inheritance and subject to selection (Boyd & Richerson 2000). A narrow comparison of the details of genes and memes is not the right test, though there is hardly any reason to abandon the heuristic horsepower of the analogy.
The second moral is that if we believe psychological biases are the main source of selective forces acting on memes, then the discovery and implications of non-content biases should be taken seriously. This detracts nothing from the importance of content biases, it merely adds to the repertoire of forces that must be considered.
The third moral is that we have talked quite enough. The only reason that there is this much misunderstanding about what memes can or cannot be, what they must or must not be for Darwinian analyses to apply, is that psychologists and anthropologists know so little evolutionary genetics, on the one hand, and this is not easy to remedy. But on the other hand, psychologists and anthropologists have done very little to advance something they are eminently qualified to do: analyze the natural histories of particular memes in different domains, and the proximate cognitive biases responsible for such processes. Some of the points I have made here came to me as revelations after tracing the spread of one particular meme in the communities I study in western Mongolia (Gil-White, in prep.), and others as a result of trying to give a full account of one particular social-learning bias (Henrich & Gil-White 2001). More revelations will follow, as in any science. But, as in any science, we need to resist the pleasures of navel-gazing in the armchair in order to get our hands dirty and toil at the empirical problems.
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