Luke Maurits

I recently finished reading Robin Dunbar’s “Grooming, Gossip and the Evolution of Language”, a fairly short and quite readable book which advances the hypothesis that the human language faculty evolved initially for the purpose of “social grooming”, i.e. strengthening social bonds between individuals in larger social groups, and then later was co-opted for the purpose of “gossiping”, i.e. talking to each other about each other.  More generally the book is concerned with the connection between cognition and social behaviour (and contains discussion of the well known “Dunbar’s number“).

The ideas in the book are well argued and I find myself without any good reason to reject most of them, although the possibility exists that there are better argued alternatives I’m not aware of.  My biggest complaint is that Dunbar’s rhetoric seems to blur the distinction between what language fundamentally does and how we preferentially use language.  I don’t have exact quotes, but there are several places in the book where Dunbar says things to the effect of “language evolved not for the purpose of exchanging information about the world around us, as we so often assume, but for exchanging information about each other for social purposes”.  This phrasing baffles me somewhat, because other human beings are part of the world around us.  Language is, by Dunbar’s hypothesis, for exchanging information about the world around us, it just happens that kind of information about the world around us which we preferentially exchange – and possibly the only kind that our ancestors exchanged – is each other.

This might seem like an odd or insignificant complaint to make, but my motivation for reading Dunbar’s book (and for reading more in general about the evolutionary origins of language) was considering the applicability of Andersonian rational analysis to language.  My recent research has centred around the Uniform Information Density (UID) hypothesis, which is theoretically motivated by the idea that human language is a roughly optimal solution to the problem of high-speed, high-reliability exchange of information (rational analysis in general holds that human cognitive faculties represent roughly optimal solutions to specific problems).  I have heard people question the applicability of this view to language, and in particular suggest that language is not essentially “for” information exchange but rather for various social interactions.  It seems implicit in this line of argument, and in much of Dunbar’s rhetoric, that these are orthogonal or mutually exclusive goals, but after reading this book I think that in fact one is simply a special case of the other, which is good news for rational theories of language.

This reassurance aside, I think the other thing I got most of reading Dunbar’s book was an appreciation for the continuity between the behavioural (and so presumably cognitive) traits of primates, including humans.  Cognitive science seems to be a fairly anthropocentric field – for obvious reasons – but it seems to me like it would often make a lot of sense to take a more inclusive view.  Perhaps attempts at modelling individual differences should also try as best they can to model inter-species differences at cognitive tasks which non-human primates are unanimously considered capable of?

The idea of applying an evolutionary perspective to the study of psychology has been hugely controversial, and I’ve never fully understood why.  Dualistic theory of mind has been effectively dead for a very long time.  Just about everybody who thinks about these things today is of the opinion that the structure and function of the mind is a reflection of the structure and function of the brain.  The brain is made of cells, and so when it comes to scientific explanations of its structure and function, evolution is the only game in town.  Any complete account of the human mind and how it came to be must necessarily include an evolutionary component.

These are all of the objections to integrating evolutionary thinking into psychology that I have either seen or can anticipate, and why none of them hold water:

• “Evolutionary psychology is bad because it will (or might) end up providing a scientific justification for racism, sexism, or some other unpleasant -ism”.  This is a straight up example of the well known is-ought fallacy.  It’s absolutely not a valid argument against EP or anything else.
• “Evolutionary psychology is a junk science full of speculative “just so” stories without any hard evidence”.  This may well be a valid criticism against some, or even many, of the particular ideas which have been developed under the guise of evolutionary psychology, but it’s not a good reason to discard the entire field.  The appropriate response to bad science which combines evolution and psychology is good science which combines evolution and psychology, not a declaration that evolution and psychology shall never meet.   Such a declaration can only be justified by an argument that good evolutionary psychology is impossible in principle.  As far as I know, no convincing argument of this kind has been made, and it seems unlikely to me that one ever will.
• “But, but, but, what about culture?”.  Bringing evolutionary thinking into psychology does not eliminate the possibility of cultural explanations for some phenomena, and in turn the explanatory power of culture does not completely eliminate the need for evolutionary thinking.  Culture isn’t magic: any given cultural influence on thought necessarily has to (i) be an influences on something, and that something has to have existed prior to the particular cultural influence under consideration, and (ii) have bene acquired by some mechanism, which again has to have existed prior to this particular cultural influence.  Evolution is the only thing which can terminate the infinite regress which results from trying to use culture as an explanation for everything.  Biological evolution and cultural evolution are complementary processes, and not at odds with one another.
• “Not everything in an organism’s phenotype represents an adaptation to some function.  The evolutionary process can also lead to traits which are exaptations, or spandrels”.  This is a prefectly valid claim in and of itself (although it’s not necessarily true – I haven’t done enough reading on the “Darwin Wars” to definitively come down on the side of Dawkins or Gould, although I’d love to have done so and fully intend to do so), but it doesn’t really remove the role for evolution in psychology.  It discredits one particular conception of evolutionary psychology, i.e. the conception in which everything is an adaptation.  But all this does is force us to widen our conception of what evolutionary psychology is, from “explaining as much of psychology as possible in terms of adaptations” to “explaining as much of psychology as possible in terms of adaptations, exaptations or spandrels”.
• “The mind is emergent magic!  Chaos, fractals, self-organisation!”.  My characterisation of this school of thought is tongue-in-cheek, but it does represent a perfectly legitimate take on the human mind.  However, once again, it’s not a magic ticket away from evolution.  The full complexity of the human mind may well emerge in some seemingly magical way from the simple, local interactions of individual neurons in the human brain, but that same complexity does not emerge from extremely similar simple, local interactions of individual neurons in the brains of cats and dogs.  Clearly there is some set of preconditions for the emergence of various psychological traits, and if we establish what those preconditions are we will be faced with the task of explaining how evolution drove our brains to meet those preconditions from a previous state which did not.  Evolution cannot have proceeded with foresight toward those preconditions because of the benefits that would emerge from them: each step along the way must have yielded its own benefits, and the story isn’t complete until we know what those steps were and why they happened.

No matter what your particular beliefs are about how the mind or evolution works (well, assuming they’re not dualist in the case of the mind), there’s just no way you can completely separate the two.  “Evolutionary psychology” isn’t some distinct subfield which you can ignore or choose not believe in.  All of psychology is under the influence of evolution, and it is a totally legitimate goal of the science to eventually account for all of these influences.  It’s conceivable that we can completely ignore this part of psychology until “the end”, characterising the functionality of all the various psychological traits without any recourse to evolutionary thinking at all and then tying it all together with an evolutionary story at the end.  But why should we do that?  To the extent that we can without sacrificing scientific rigour, we should try to uncover the evolutionary story as we go.  Not only is it damned interesting, but it can be legitimately used to constrain hypotheses in areas of the science where we haven’t yet made a lot of progress, making it a useful tool.  Besides, it’s just as conceivable that we can’t completely ignore this influence.  If nothing else, I think a basic grounding in the latest facts and hypotheses surrounding the evolutionary emergence of human intelligence should be considered an essential part of a thorough education in psychology.

Seed Magazine recently posted a rather neat video called “The Evolution of Life in 60 Seconds” which, as the name suggests, is an attempt to depict the 4.6 billion year history of life on Earth into a single minute, in the form of a changing cluster of words. It’s a cute little video and gives you a good sense for just how incredibly recent everything we take for granted actually is.

I find it hard to put into words just how captivating I find the history of the Earth (which Wikipedia has an excellent article on), and even more so how utterly inspiring I find it that we have actually been able to figure out as much about it as we have. I have thought for a while now that if I ever inexplicably find myself with an extreme excess of time and money and the desire to develop an entirely new tool set that I would love to participate in a project to make a documentary which squeezes those 4.6 billion years into say, 120 or 150 minutes. I would like it to be something completely accessible to, say, a 14 year old, who is soon to have to make decisions about what to study in high school, but still interesting to adults. I’d also like to try to balance the emphasis between simple statement facts – “this is what happened, and when” – and an explanation of the scientific processes which led us to those facts – “this is how we know what happened“, or perhaps better “this is why we think this happened“: Just-so stories won’t inspire anybody.

This blog entry represents quite a substantial departure from my usual subject matter, in that it has a lot to do with molecular biology. To say that this is not my area of expertise would be an understatement. I have no formal education in biology beyond the bare minimum that every Australian high school graduate must get – I ditched it for physics and chemistry at the first possible opportunity. My entry point into the material discussed here is this paper, which I found by virtue of it being cited in this paper, which is substantially more relevant to my current field. So I make no guarantees of complete factual accuracy in what follows, although I’d like to think I haven’t misunderstood anything too severely.

Phylogenetics is the study of evolutionary relatedness between organisms – identifying which plants or animals have common ancestors. The end result of such study is the production of phylogenetic trees, or “trees of life”, which look something like this and diagrammatically convey our best estimate as to when and where two closely related species have diverged earlier in evolutionary history. Historically, I get the impression this has been a 1very labour intensive process, and one where it has been difficult to get any sort of objective measure of reliability: evolutionary relatedness has had to been inferred based on observed similarities in things like large-scale physical traits or behaviour.

Modern molecular biology, however, has opened the door to, appropriately enough, so-called molecular phylogenetics, in which evolutionary relatedness is determined in a more direct and objective way by comparing organisms in terms of molecular structure – specifically, DNA or some form of RNA. In this case each organism is represented by a GATTACA-style sequence of base pairs and we assess relatedness by using some sort of mathematical model of the evolutionary process itself. As a simplest approximation, we might represent evolution by a sequence of independent mutations, where a particular base pair is picked uniformly at random from the entire sequence and replaced by another base pair picked uniformly at random from the 16 possible pairs. It is possible to refine this first order approximation by making mutations in some areas of the sequence more likely than others and/or making some mutations more likely than others.

With a collection of aligned sequences and such a mathematical model of evolution, we can then proceed to infer phylogenetic trees by any one of a number of possible techniques – by appealing to parsimony, and seeking the tree which minimises the total number of required mutations; by appealing to maximum likelihood and seeking the tree whose underlying sequence of mutations is more probably than that underlying any others; or by using Bayesian inference to compute a posterior probability distribution over trees. These heavily computational approaches to molecular phylogenetics are called (once again, appropriately enough), computational phylogenetics. The Bayesian case is the most immediately interesting to me, because it’s the only one I’ve read about in significant detail and because the specific algorithms used typically belong to the same broad class of algorithms that I use in my own work (Markov Chain Monte Carlo approximations), although Wikipedia suggests that this technique is controversial at best. The trees produced via Bayesian methods in the paper cited above, though, certainly seem reasonable to my non-expert eye.

The awesome explanatory power of the ideas of evolution mapped onto genetics is poignantly apparent when we step back and think about what is being achieved here. We are providing as input to a computation the structure of certain molecules sampled from organisms – invisible, tiny fragments of whole animals – and, making only assumptions about mutation processes on these molecules (which are known for a fact to occur) we are receiving as output tree structures of relatedness which are in excellent broad agreement with the tree structures we made in the pre-genetic days based on our observations of macroscopic physical features of whole animals. How inspiring! How giddyingly exciting it is to think that it is by no means impossible that in the future, after we have refined our techniques of , developed more efficient and accurate numerical methods for Bayesian inference or other statistical techniques, and greatly increased the processing speeds of our computers, we may be able to input into a great machine cell samples from all the plants and animals we have discovered and, after a lengthy process of computation, be rewarded one day with a glance at the complete history of all life currently found on this planet!