Note: This was a short-lived blog on evolutionary psychology, run by Tom Dickins, Ben Dickins, and myself, Keith Frankish, in the late 2000s. It is n longer active and is preserved here as an archive. Please note that many of posts published under my name (KF) were not in fact written by me; I merely posted them.

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Explaining Religion conference

In the popular mind, science and religion are implacably opposed; yet religion is itself a fascinating and powerful natural phenomenon, which cries out for scientific explanation. The explanatory task is a daunting one, not least because so many disciplines are relevant to it, but real progress is being made on many fronts, and a forthcoming interdisciplinary conference at the University of Bristol aims to integrate approaches from a variety of fields.

The event, which is being organized Finn Spicer, Andrew Atkinson, and Nathalia Gjersoe, is supported by the University of Bristol’s Department of Philosophy and the Bristol Cognitive Development Centre, and it will include contributions from evolutionary theory, philosophy, cognitive science, anthropology, psychology, and related disciplines.

It looks set to be a super event, and there’s a great line-up of speakers, including Jesse Bering, E.Thomas Lawson, Susan Blackmore, Ryan McKay, Christine Mohr, Deb Kelemen, Konrad Talmont-Kaminski, Robert McCauley, Bruce Hood, Ara Norenzayan, and Michael Blume

There’s more information and registration details on the conference website

Unfortunately, I won’t be able to attend myself, but if anyone who does attend would like to post a review of the event here at Evolving Ideas, do please get in touch.

A Thought About Dual Inheritance Theory

Post author:  Tom Dickins

I recently had reason to re-read Eric Alden Smith’s chapter on Three Styles in the Evolutionary Analysis of Human Behaviour. This chapter was published in 2000 and discussed the relative merits of Evolutionary Psychology, Human Behavioural Ecology and Dual Inheritance Theory (DIT). Some might say that this chapter is now out of date, and that the boundaries between these three sub-disciplines, or styles, has begun to erode with scientists now pursuing particular kinds of question with specific methodologies. Moreover there is some evidence, folk might say, that researchers recognize the need to discuss population level behavioural patterns, in order to proscribe parameters for the more proximate musings of, for example, evolutionary psychologists.

Given the rhetorical nature of the preceding paragraph one might assume that I think the boundaries are eroding. I certainly think that conceptually they ought not to have been there for evolutionary psychology and human behavioural ecology, and I suspect a deep sociological theory will reveal why such issues existed, perhaps revealing an abiding problem of funding and departmental pecking orders. I do, however, think that DIT ought to be seen as a stand-alone activity.

On page 32 Smith outlines the core of DIT. DIT claims that culture exhibits heritability, variation and fitness effects, but that cultural inheritance is different from genetic inheritance. So, neo-Darwinian modelling can be applied to cultural change but with modifications to account for the difference in inheritance. Furthermore, given this distinction between inheritance systems, cultural evolution can lead to genetically maladapted forms. Smith then moves on to claim that DIT can sustain particular forms of group selection:

“Since collective action often involves systems of widespread and indirect reciprocity (e.g. serving as a soldier on behalf of one’s society is reciprocated with various kinds of rewards to the soldier or his kin), it qualifies as a form of social exchange. Boyd and Richerson… have constructed models of cultural group selection of such group-beneficial behaviours. These models show that cultural inheritance plus conformity transmission (‘when in Rome, do as the Romans do’) can in principle create and maintain significant between-group differences despite reasonable rates of migration between these groups, thus avoiding a major obstacle facing classical forms of genetic group selection.

“The mechanisms of group selection most commonly proposed in this regard is group dissolution due to warfare, with refugees from defeated groups being absorbed by allied groups; if culturally transmitted traits that favour socially altruistic traits (e.g. contributing to the collective good of military defense and offense) decrease the probability of group defeat and dissolution, then these could spread by cultural group selection…” (Smith, 2000: 33)

Putting to one side the technical problems of group selection, another way of stating this effect (if it indeed qualifies as an effect) is that a defeated person can be housed within the population that defeated him or her and learn that contributing in a particular way to the group will sustain him or her. We can hypothesize that humans have good learning mechanisms that enable them to conform at the appropriate point.

More critically, if one removes the possibility of changing strategic response for absorbed refugees, the victorious groups will change the ratio of committed soldiers to uncommitted members both through absorption and the natural attrition of soldiers as a consequence of what they do. As these proportions change so will the population dynamics within the group. This is likely to erode between group differences and increase within group variation thus undermining the claimed possibility of group selection.

So, either absorbed refugees can change and conform, in which case the explanatory action is at the psychological level and we are back to normal evolutionary concerns with regard to the selection of such learning mechanism, or they cannot and the constitution of the groups will change and prevent sufficient between group differences for the kind of selection wished for.

My charitable suspicion is that DIT folk heuristically think of groups as organisms with phenotypes, and see them competing in a given ecology with other such individuals. However, once they have modelled some dynamic interaction between such individuals, perhaps in a similarly approximate way that gene-level selectionists might look at individuals, they remember that they are groups, that the inheritance is within and between groups, that it is different from genetic inheritance in many other ways (not least its low fidelity), and so they try and force the group selection point. Indeed, they call it cultural group selection in an attempt to move away from contentious issues in biology.

To conclude, I think that this use of (cultural) group selection by DIT theorists shirks explanatory responsibility. What is interesting is how humans ever begin cooperating in the first instance, how human psychology facilitates the emergence of stable equilibria in a variety of social games. Evolutionary psychology will tell you that evolutionary game theory will predict the emergence of certain strategies that are the product of gene-level dynamics. By establishing these strategies we can then begin to look at the psychological mechanisms that are, by extension, part of this strategic response, and then map the variation in these phenotypes. Such activities are entwined with behavioural ecological concerns about facultative responding to different ecological facts, in order to (try and) maximize fitness. I recognize this is a rather a skimming treatment of the situation, but it serves to emphasize what DIT is not delivering. DIT at best might highlight something to look at – the operation of conformity or some such – but by forcing what is at best an analogy with genetic inheritance, and thereby biological evolution, the discipline misses the intrinsic puzzle of the phenomenon, a phenomenon that evolutionary social psychology can take care of. To this end, DIT is in no sense a style of evolutionary analysis, as Smith has claimed.

(If you want to see how to think about all of the underlying biology properly then you should read West et al. (in preparation). This paper is the best I have read on the topic of cooperation, and deals with the claims from group selectionists decisively and fairly. It deserves to be widely cited upon publication.)

Three Drivers of Evolution at Organism Level

(John Jacob Lyons, 18 September 2009)

The four dimensions of evolution identified in Jablonka and Lamb’s book ‘Evolution in Four Dimensions’ were described as; genetic, epigenetic, behavioural and symbolic. Although this is an extremely useful book, the dimensions proposed are not considered the best basis on which to carry forward research on evolutionary theory. The ‘symbolic’ dimension relates to one particular aspect of cultural evolution and, although there can be interaction between adaptive cultural change and genomic change, the use of the word ‘symbolic’ appears inappropriate and too narrow to denote this interaction. Genetic and epigenetic processes often operate in tandem and it may be misleading to nominate them as separate dimensions. An important deficiency is that the nominated dimensions are not from the same class of objects. They are not separate and different evolutionary processes and neither are they separate, independently generated drivers of evolution.

I want to suggest three independently generated, primary drivers of evolution at organism level that, I believe, would provide a better basis for future research; random genetic mutation, natural environmental change and behavioural change – including niche construction.

These categories can all be described as independent drivers of evolution. They are mutually exclusive but, of course, not exhaustive at this level of analysis. Sexual selection is a powerful driver and species would still evolve within the constraints of their existing gene-pool and without considering new mutations. Then there are the effects caused by artificial human selection; both within the human species (eg contraception) and those imposed on other species (eg selective breeding). However, I have highlighted three evolutionary drivers that, I believe, have been somewhat confused in previous work in evolutionary theory.

Each of these primary drivers is described below in a little more detail below.

Driver 1 – Random genetic mutation

This is often called (Classical) Darwinian Evolution. A mutation of this kind will be adaptive if it results in an adaptive phenotype; either increasing the viability/ fecundity of the organism or increasing both. The expected incidence of the mutation in the next generation will increase and will increase further in future generations as long as the mutation continues to be adaptive.

Driver 2 – Natural environment change

Particular extant alleles of particular genes/ epigenetic-markers will be more adaptive in the changed environment, again resulting in an expected increase in the incidence of this particular allele-set in future generations.

Driver 3 – Behavioural change – including niche construction

Initially, one or a small number of organisms learn a behaviour that proves to be adaptive. This behaviour may or may not affect the physical environment. Manifestation of the adaptive behaviour will often be positively and causally correlated with particular allele-sets that make the organism more likely to manifest the behaviour.  Selection pressure will result in an increase in the expected incidence of the allele-sets’ constituents in the following generation (see Behavioural Genetic Priming). This will, in turn, increase the expected number of organisms manifesting the behaviour in that generation. This positive feedback loop will continue to increase the incidence of the adaptive behaviour in future generations. In due course, all organisms in a population may be, to a greater or lesser extent, genetically primed to manifest the behaviour with a minimal trigger from the environment. I say “to a greater or lesser extent” since there may well be other adaptive behaviours and other sources of selection pressure in play that are underpinned by overlapping gene-sets. This would eventually result in optimal allele configurations for the complete set of adaptive behaviours and other sources of selection pressure but a suboptimal configuration for any particular adaptive behaviour.

Driver 3 can be described as an adaptive acquired characteristic and, although the characteristic itself cannot be assimilated into the genome, its positive association with concomitant, genetically mediated predispositions means that it is ‘able’ to prime the genome to increase manifestation.

If we add back the other drivers of evolution previously mentioned we get:

Driver 4 – Sexual Selection

Driver 5 – Natural Selection within current gene-pool

Driver 6 – Artificial Human Selection

Driver 7 – Hybridisation

Is this an exhaustive set of evolutionary drivers?

Genetic Priming; So What's New

(prepared 14 June 2009 by John Jacob Lyons)

The ‘Baldwin Effect’ has been defined as an adaptive trait change in an organism – that occurs as a result of its interaction with its environment- becoming gradually assimilated into its developmental genetic/ epigenetic repertoire. My ‘genetic priming’ hypothesis seeks to clarify the process involved in the Baldwin Effect and to correct several points in the definition above that relate to the effect of this process.

The process consists of an inter-generational positive feedback loop between the adaptive trait and the positively and causally correlated subset of the genome that tends to support the trait. This is described in greater detail in my article in the ‘Evolving Ideas’ blog. As stated there, selective pressure will result in the manifestation of the trait earlier and earlier in the development of the organism.

However, the adaptive trait will never be “ – assimilated into its developmental genetic/ epigenetic repertoire.” What will happen is that selective pressure will result in the allele-configuration of the relevant subset of genes ‘trying’ to change in order to optimize the support given to the trait. In doing so, it may well be in competition with other adaptive traits ‘trying’ to optimize the subset to support them. This will obviously result in sub-optimization for any particular individual trait. The ultimate result will be that the genome will have been, within the aforementioned constraint, primed to support the manifestation of the original adaptive trait. An example will make some of these points clear.

It is well known that, over the human EEA, post-weaning lactose tolerance developed in temperate regions in which cattle were farmed. In this case, the adaptive trait was milk consumption (Vitamin D enables absorption of calcium; particularly adaptive in temperate regions) and the correlated subset of the genome was that involved in controlling lactose tolerance. The positive feedback explained above has resulted, in these regions, in the ubiquitous priming of the human genome toward post-weaning lactose tolerance and not in a genetically assimilated tendency to consume milk! There has been no assimilation of the adaptive behaviour; only genetic priming of the associated subset of the genome.

I suggest that, subject also to many relevant cultural evolutionary factors of course, humans have been genetically primed for language, religiosity, morality and love/ attachment/ empathy in a similar way.

The next two posts

The next two posts our guest posts by John Jacob Lyons.

A failure of sentiment or of reasoning?

Should you give to charity? Looking at the arguments associated with two recent books it would seem that you are damned if you do and damned if you don’t. But take a second look from an evolutionary perspective and it seems that sins of omission and of commission inhere at a different grain of analysis.

The first book is Peter Singer’s The Life You Can Save: Acting Now to End World Poverty (argument summarised here). Singer is raising consciousness. Writing to an American audience he lays out the facts about how little America actually gives in aid and how much less it gives to the very poorest countries. En route he dispatches arguments that America’s large private sector offsets the lack of public largesse – it doesn’t. But Singer doesn’t stop here. With his utilitarian bent on full display, he compares these aid figures with the amount the US government is willing to pay to save American lives (from road traffic accidents for example) and the amount it costs to save African lives. This gives a rough figure of how much America values the lives of its citizens over others: ten thousand to one. Singer acknowledges the inevitable inequity (the expanding moral circle is not a Boolean guide to action) but questions its degree. He also discusses the effectiveness of aid and points to the effectiveness of at least some interventions while calling for more research (even arguing for prospective control studies – given that there is never enough aid for all who need it). The conclusion is that people in developed countries need to be more generous because their money is more valuable in developing countries than in their own pockets even if some is squandered by the corrupt or unwisely spent by the inept. Acknowledging uncertainty in this way is a clever argumentative strategy on his part and one that seems to turn the tables on opponents of aid who fail to consider the least convenient possible world (or even a minimally inconvenient counterfactual). Thus we are cogently coaxed away from our moral complacency.

But then there is the second book, by economist Dambisa Moyo: Dead Aid: Why Aid Is Not Working and How There is a Better Way for Africa (she is interviewed here). She and Singer don’t seem to have engaged directly so far as I can tell, but her arguments seem effective counters to Singer’s. It would indeed be complacent not to give to charity if at least some good came of it, but what if it did more harm than good? More Africans are poor now than in the past, not just more people, but a vastly higher proportion – this despite a deluge of aid. Aid is sequestered by and sustains corrupt regimes (and yes this still includes Zimbabwe). And while Singer argues that NGOs circumvent this by direct work in the community, she makes the general argument that this damages the credibility of the relatively less effectual government, further weakening democracy. Deeper than this, in fact, aid can directly interefere with the means of production within Africa – she gives the example of 160 mosquito net makers and their dependents who were taken out of business and themselves became dependent on aid as a result of the arrival of nets from abroad. So Moyo wants to shake us from a different sort of complacence – that which favours pity over reason. And she has positive things to say about trade. In a qualified way she praises China for the huge amount it has done for Africa compared with Europe and America simply by trading with Africans (there is an implicit moral point here that traders interact as equal partners while aid leads to dependency). She is a fan of microcredit and recommends this website where you can lend small sums to shop owners, agriculturalists, etc. all over the world who have an effective plan.

So one way of reading this is as a barney (argument) about the effectiveness of aid. But when you attend to the details (especially those in Moyo’s argument) perhaps a “third way” presents itself. What is interesting about microcredit, for example, it that it is somewhere between trade and aid – as a lender you do not charge interest so you are foregoing interest you might have earned. So does the lender take on this opportunity cost out of pity? To me this looks like enlightened generosity – the right mix of sentiment and reasoning on the lender’s part and the right mix of incentives at system level to benefit people in poor countries.

I favour Moyo’s point that aid can be counterproductive although I think this might be because it hasn’t been evidence based and therefore this might be fixable. Of particular concern given the patchwork distribution of aid (and the prevalance of religious charities) is the lack of available contraception. A recent study in PLoS Medicine illustrates this with results that are beautifully congruent with evolutionary theory (or at least the trade-offs assumed in life history theory). Mhairi Gibson and Ruth Mace carried out a retrospective study in which they assessed the effects of the installation of water taps (faucets) in some villages (and not in others) on mortality and health in children and mothers. It seems that the decreased maternal effort associated with obtaining water results in energy being redirected towards increased fecundity. I limn from a multivariate analysis here, but essentially villages with a water supply showed decreases in infant mortality and it seems that fertility increased in mothers with access to taps, but this was associated with no better maternal health and, in fact, with poorer infant health including a greater risk of malnourishment and stunting. The authors point to the growing African population as a severe problem (and here I am reminded of Jared Diamond’s controversial suggestion regarding the causes of the Rwandan genocide) unless interventions are designed to address fertility in concert with more traditional development goals.

The call for more research ought to be heeded, but in our current state of partial ignorance I would suggest that Moyo’s argument that aid can be counterproductive is not a feeble excuse for inaction but a reasonable concern.

Postnote: Charlie Rose (as ever) conducts a courteous but thoroughgoing interview with Dambisa Moyo raising Singer’s arguments briefly and many of the most interesting issues discussed here…

Simulation or instantiation

I just went to a talk today in my institution by Professor Robert Pennock who spoke a little about education and a little about artificial evolution of intelligence. The latter stole the limelight due to the intrinsic coolness of robots (real or simulated) with goal-directed behaviour. But among his many departmental affiliations at Michigan State is the Philosophy Department so I was interested to hear what he had to say on this score. No doubt because this was a general lecture this content was mostly geared towards understanding why the argument for design is incorrect – familiar territory for evolutionists (though I liked his updating Paley’s argument from watch implies watchmaker to neat iPod app implies SDK programmer). But my parenthetically referring to robots as simulated above was deliberate. He made what I thought was a small but elegant point about this.

Is artificial evolution simulated evolution or an instance of evolution? Pennock argued that the distinction between these descriptions depended partly on pragmatics and partly on what causal processes are of interest. Since the artificial evolution paradigm he discussed modelled the minimal parameters for evolution by natural selection he was happy to describe it as an instantiation even though the mechanisms of metabolism and reproduction were not quite nature-identical or gooey enough. He pointed out that these mechanisms were not known to Darwin and yet we would still call his theory a theory of evolution.

To my mind this is equivalent to the claim that evolution is substrate-neutral. However in so far as parameters necessary for selection are dependent upon genetic mechanisms we might dispute this. In fact the metabolic and reproductive rules in the software he described entailed these parameters (often explicitly – he affirmed that recombination, a source of variation that can break up clonal interference, was modelled in some of his project). So I agree with his implicit point that modelling can be more or less precise along different dimensions such that there is an arbitrariness about the dividing line between simulation/instantiation unless a modeller’s purpose is borne in mind. But I am not sure that specifying what is modelled, and how precisely, is enough. This is because evolution is diverse and is caused by multiple processes at the population genetic level. This is clear in my field of wet-lab experimental evolution in which large populations and strong selection pressures often inflate the perceived important of selection.

Finally he was asked a semantic question about the distinction between machine learning and artificial evolution – a particularly germane one since he was describing the evolution of intelligent systems. Essentially he described the second as an example of the first in which genetical algorithms did the learning by selection. But this calls to mind an earlier distinction I remember hearing (apologies for not attributing) regarding robots that learn about their environment through feedback. An effective robot would understand its environment, i.e., whittle down its set of models, by taking actions that resulted in the maximum discrepancy between the predictions of each model. But when it came time to act in the environment, the best actions were those that minimised the predicted discrepancy between surviving models. (Something like this might be relevant to earlier efforts on this blog to explain the functions of play). I wonder if, in particularly rugged fitness landscapes, this distinction between testing and optimal inference may be important when it comes to design assisted by genetical algorithms. The ability to allow heritable variation in mutation rate may become more important in such instances.

Non-locality

A disclaimer about what follows: this is a substantial digression from any area I might claim knowledge of.

Quantum theory is counterintuitive in interesting ways. Many people emphasise the strangeness of indeterminacy and adduce it to argue that the mind contains or operates special causal levers. I don’t see a great benefit to uncaused causes for a free-will enthusiast or, for that matter, for first-cause mysticisers, so I tend to be sceptical of many popular claims of this nature. Indeterminacy is counterintuitive and interesting but determinacy isn’t a pin in the grenade of rationalism.

Non-locality  – or the capacity for state changes to propagate between entangled particles with no intermediaries and with no delay – has always seemed more interesting to me. This recent popular article emphasises its incompatibility with general relativity. It turns out that non-locality’s absolute simultaneity poses a significant challenge for physics and, given our ideas of the geometry of spacetime, for our understanding of causation.

Reading this stimulates in me the intuition that perhaps locality is in some sense incoherent. Just how close do two objects have to be (à la Zeno’s paradox) for interactions between them to be considered local? Is it necessarily all that peculiar that events in the future might determine events in the past?

I think that our concepts of locality and ontology are linked in such a way that revisions may be required in both. If X and Y make up the entity Z then any properties of Z will be shared by X and Y regardless of where and when X and Y are. This argument makes the description of instantaneousness redundant and I suspect that quantum entanglement is somewhere between the situation just described and one in which X and Y are truly separate entities. Perhaps the problem of non-locality cuts into ontology. I would very much appreciate any more expert thoughts on the matter…

Pleiotropy

I’ve posted a few times on pleiotropy. Pleiotropy, or the multiple causal connections that a given gene is involved in, is the bête noire of evolution by selection because it increases the probability that a mutation at that gene will be deleterious (even though it may be beneficial within one context). Modularity is required at the gene level to allow functional change to occur by selection and this has motivated some to propose that cis-regulatory elements (CREs) are crucial to the evolution and development of form.

But modularity can also occur at the level of genetic networks and it is often asserted that such networks can be co-opted in their entirety to fulfill novel (non-homologous) functions. In the context of testing this idea, this recent article addresses the consequences of this for the pleiotropy of CREs. If network co-option really is that common, pleiotropic CREs will also be common at least among those genes that tend to be found within networks rather than upstream. This seems to be a nice example of entrenchment in evolution.