Category Archives: Uncategorized

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Has Dennett Undercut His Own Position on Words as Memes?

Early in 2013 Dan Dennett had an interview posted at John Brockman’s Edge site, The Normal Well-Tempered Mind. He opened by announcing that he’d made a mistake early in his career, that he opted a conception of the brain-as-computer that was too simple. He’s now trying to revamp his sense of what the computational brain is like. He said a bit about that in that interview, and a bit more in a presentation he gave later in the year: If brains are computers, what kind of computers are they? He made some remarks in that presentation that undermine his position on words as memes, though he doesn’t seem to realize that.

Here’s the abstract of that talk:

Our default concepts of what computers are (and hence what a brain would be if it was a computer) include many clearly inapplicable properties (e.g., powered by electricity, silicon-based, coded in binary), but other properties are no less optional, but not often recognized: Our familiar computers are composed of millions of basic elements that are almost perfectly alike – flipflops, registers, or-gates – and hyper-reliable. Control is accomplished by top-down signals that dictate what happens next. All subassemblies can be designed with the presupposition that they will get the energy they need when they need it (to each according to its need, from each according to its ability). None of these is plausibly mirrored in cerebral computers, which are composed of billions of elements (neurons, astrocytes, …) that are no-two-alike, engaged in semi-autonomous, potentially anarchic or even subversive projects, and hence controllable only by something akin to bargaining and political coalition-forming. A computer composed of such enterprising elements must have an architecture quite unlike the architectures that have so far been devised for AI, which are too orderly, too bureaucratic, too efficient.

While there’s nothing in that abstract that seems to undercut his position on memes, and he affirmed that position toward the end of the talk, we need to look at some of the details.

The Material Mind is a Living Thing

The details concern Terrence Deacon’s recent book, Incomplete Nature: How Mind Emerged from Matter (2013). Rather than quote from Dennett’s remarks in the talk, I’ll quote from his review, “Aching Voids and Making Voids” (The Quarterly Review of Biology, Vol. 88, No. 4, December 2013, pp. 321-324). The following passage may be a bit cryptic, but short of reading the relevant chapters in Deacon’s book (which I’ve not done) and providing summaries, there’s not much I can do, though Dennett says a bit more both in his review and in the video.

Here’s the passage:

But if we are going to have a proper account of information that matters, which has a role to play in getting work done at every level, we cannot just discard the sender and receiver, two homunculi whose agreement on the code defines what is to count as information for some purpose. Something has to play the roles of these missing signal-choosers and signal-interpreters. Many—myself included—have insisted that computers themselves can serve as adequate stand-ins. Just as a vending machine can fill in for a sales clerk in many simplified environments, so a computer can fill in for a general purpose message-interpreter. But one of the shortcomings of this computational perspective, according to Deacon, is that by divorcing information processing from thermodynamics, we restrict our theories to basically parasitical systems, artifacts that depend on a user for their energy, for their structure maintenance, for their interpretation, and for their raison d’être.

In the case of words the signal choosers and interpreters are human beings and the problem is precisely that they have to agree on “what is to count as information for some purpose.” By talking of words as memes, and of memes as agents, Dennett sweeps that problem under the conceptual rug. Continue reading

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Causality in linguistics: Nodes and edges in causal graphs

This coming week I’ll be at the Causality in the Language Sciences conference.  One of the topics of discussion will be how to integrate theories of causality into linguistic work.  Bayesian Causal Graphs are a core approach to causality, and seem like a useful framework for thinking about linguistic problems.  However, it’s not entirely clear whether all questions in linguistics can be represented using causal graphs.  In this post, I’ll discuss some possible uses of Bayesian Causal Graphs, and test the fit of some actual data to some causal structures.  (and please forgive my basic understanding of causality theory!)

Causal graphs are composed of states connected by edges.  A change or activation of a state causes a change in another.  States and causes can be categorical and absolute, or statistical and even complex in their relations.  Causal graphs are often introduced with the following kind of structure, taken from Pearl’s seminal book on Causality.  The season causes it to rain (in winter) and causes the sprinkler to come on (in summer).  Both the sprinkler being on and rain independently cause the grass to be wet.  If the grass is wet, the grass becomes slippery:

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This example is easy to understand because each state is binary and (in this simple world) each causal effect is immediate and direct.  However, finding a similar example for linguistics is tricky.  Linguists may simply not agree on what the nodes are or what the edges represent.

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Q: Why is the Dawkins Meme Idea so Popular?

A: Because it is daft.

I believe there are two answers to that question. For most people it’s convenient. That requires one explanation, which I’ll run through first.

For some people, however, memetics is more than convenient. Some, including Dawkins himself and his philosophical acolyte, Dan Dennett, use it as a way of explaining religion. In that role the meme idea is attractive because it is, or has evolved into, an egregiously bad idea, one almost as irrational as the religious ideas whose popularity it is supposed to explain away. By analogy to an argument Dawkins himself has made about religion, that makes memetics the perfect vehicle for the affirmation of materialist faith.

But I don’t want to go there yet. Let’s work into it.

Ordinary Memetics

When Dawkins first proposed the idea in The Selfish Gene (1976), it wasn’t a bad idea—nor even a new one. Ted Cloak, among others, got there first, but not with the catchy name. Having worked hard to conceptualize the gene as a replicator, Dawkins was looking for  another set of examples. and coined the term “meme” as a replicator for culture. The word, and the idea, caught on and soon talk of memes was flying all over the place.

I suspect that the spread of computer technology is partially responsible for the cultural climate in which the meme idea found a home. Computers ‘level’ everything into bits: words, pictures, videos, numbers, computer programs of all kinds, simulations of explosions, traffic flow, moon landings, everything becomes bits: bits, bits, and more bits. The meme concept simply ‘levels’ all of culture—songs, recipes, costumes, paintings, hazing rituals, etc.—into the uniform substance of memes.

What is culture? Memes.

Simple and useful. As long as you don’t try to push it very far.


In his original exposition Dawkins was a bit equivocal as to whether or not memes existed inside the brain or outside in the external world. Thus at one point he refers to one copy ‘Auld Lang Syne’ existing in his brain and other copies existing in a song book (p. 194). This issue became a matter of debate among the relatively small community of thinkers who were attempting to develop an intellectually rigorous theory of cultural evolution. Some of us were known as externalists while others were internalists.

I was and am an externalist. I’ve stated my position at length in two papers published in the mid-1990s (Culture as an Evolutionary Arena and Culture’s Evolutionary Landscape) and more recently in an extensive series of notes, The Evolution of Human Culture. I have no intention of rehearsing those arguments here. But I want to make one point, and that is about human language.

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ICPhS phonetic capabilities satellite meeting – deadline extension

Re. The ICPhS phonetic capabilities satellite meeting, which has been previously advertised on this blog.
We have received a number of requests for late submissions, which we have granted, and as a result, feel it fair to have the same extension for everyone. Thus, if you would like to either submit something, or would like to redraft and resubmit your submission before the new deadline, you are advised that this is now:
 
1st March.
Thank you very much if you have already submitted a paper. What we’ve seen so far looks very exciting, and if you are happy with your paper, you obviously don’t need to do anything. We have previously advised some contributors that notifications of acceptance would appear before the end of February. This is of course now not possible, but we hope to keep the delay to as little as possible, hoping to deliver valuable feedback from the review process by mid-March.
Do no hesitate to contact hannah@ai.vub.ac.be with any further questions.
Here is the call for papers again, in case you missed it:
Call for papers
 
At this year’s International Congress of Phonetic Sciences in Glasgow, there will be a special interest group on the Evolution of our phonetic capabilities. It will focus on the interaction between biological and cultural evolution and encourages work from different modalities too. The call for papers is here (satellite meeting 3) and pasted below:
The evolution of phonetic capabilities: causes, constraints and consequences
In recent years, there has been a resurgence in research in the evolution of language and speech. New techniques in computational and mathematical modelling, experimental paradigms, brain and vocal tract imaging, corpus analysis and animal studies, as well as new archeological evidence, have allowed us to address questions relevant to the evolution of our phonetic capabilities.
This workshop requests contributions from researchers which address the emergence of our phonetic capabilities. We are interested in empirical evidence from models and experiments which explore evolutionary pressures causing the emergence of our phonetic capabilities, both in biological and cultural evolution, and the consequences biological constraints will have on processes of cultural evolution and vice versa. Contributions are welcome to cover not only the evolution of our physical ability to produce structured signals in different modalities, but also cognitive or functional processes that have a bearing on the emergence of phonemic inventories. We are also interested in contributions which look at the interaction between the two areas mentioned above which are often dealt with separately in the field, that is the interaction between physical constraints imposed by a linguistic modality, and cognitive constraints born from learning biases and functional factors, and the consequences this interaction will have on emerging linguistic systems and inventories.
Contributions must fit the same submission requirements on the main ICPhS 2015 call for papers page.
Contributions can be sent as an attachment to hannah@ai.vub.ac.be by 1st March 2015 (**extended**). Queries should be sent to the same address.
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Persister: A sci-fi novel about cultural evolution and academic funding

Someone has written a sci-fi space opera about a serial killer that targets researchers of cultural evolution which is also a satire on the state of academic funding systems.

That’s quite an action-packed sentence.

Persister: Space Funding Crisis I by Casey Hattrey is a short novel set in the 45th century about a cultural evolution researcher named Arianne. By this point, the decision process for academic funding takes so long that the only sensible option is to cryogenetically freeze yourself while you wait for the decision to come in. The cost of this, and the fierce competition for funding in a pan-galactic community, has made the Central Academic Funding Council Administration the most powerful force in the galaxy. Now, Arianne has been woken from chryo-sleep, not to be given a grant, but to investigate a series of gruesome murders. Someone has been killing the top researchers in the field of cultural evolution.

"In space, no one can hear you apply for funding"

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How Language Evolves Webcast

CARTA (Center for Academic Research & Training in Anthropogeny) are webcasting their free symposium on “How Language Evolves” on Friday, February 20th (1:00 – 5:30 pm PST), co-chaired by Roger Levy (UC San Diego) and David Perlmutter (UC San Diego).

How Language Evolves

 

The symposium addresses the question of how human language came to have the kind of structure it has today, focusing on three sources of evidence:

1) ways languages get new structure not present in the language of the previous generation(s) of speakers or signers;

2) what contrasts between new and mature languages reveal about how language evolves;

3) neuroscientific investigations of functional specialization for language in the human brain and its dependence on the linguistic input the language learner gets during cognitive development.

You can access the live webcast here:

http://carta.anthropogeny.org/events/how-language-evolves

 

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Tone and humidity

Does the weather effect the languages we speak?

This week, Caleb Everett, Damian Blasi and I have a paper out in PNAS (also available here) on the effects of humidity on the production and perception of lexical tone, and the subsequent predictions about the distribution of tone across the world.

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Map of humidity (lighter = more humid) with complex tone languages in red and non-complex tone languages in blue.

The basic principle behind studies of cultural evolution is that a selective pressure on communication can transform the structures of a language over time.  What we explore is whether speaking in dry environments exerts a pressure to avoid using sounds that are more difficult to produce or comprehend, leading to those sounds being selected against.

Edit: See also this FAQ page

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Issues in Cultural Evolution 2.1: Micro Evolution, Dawkins and Memes

It’s time I get back to my attempt to lay out a map of approaches to cultural evolution in a limited number of posts, say a half dozen or even less (in my first post I said three). This is the first of two or three posts in which I look at ideas of the microscale entities and processes. In this post I’ll take a close look at Dawkins’ concept of the meme as he laid it out in The Selfish Gene. In my next post or two I’ll lay out other positions while developing mine in the process.

Dawkins Defines the Meme

I’m going to take a close look at two paragraphs from the 30th Anniversary edition of The Selfish Gene (Oxford 2006). First I’ll quote the paragraphs without interruption and commentary. Then I’ll repeat them, this time inserting my own comments after passages from Dawkins.

The book, of course, is not primarily about culture. It is about biology and argues a gene-centric view of evolution. In the process Dawkins abstracts from the biology and extracts two roles, that of replicator and that of vehicle. Genes play the replicator role and phenotypes play vehicle role. From a gene-centric point of view, the function of phenotypes is to carry genes from one generation to the next.

Have set this out in ten chapters, Dawkins then turns to culture in the eleventh chapter, where he introduces the meme in the replicator role in cultural evolution. The paragraphs we’re examining are on pages 192-193:

Examples of memes are tunes, ideas, catch-phrases, clothes fashions, ways of making pots or of building arches. Just as genes propagate themselves in the gene pool by leaping from body to body via sperms or eggs, so memes propagate themselves in the meme pool by leaping from brain to brain via a process which, in the broad sense, can be called imitation. If a scientist hears, or reads about, a good idea, he passes it on to his colleagues and students. He mentions it in his articles and his lectures. If the idea catches on, it can be said to propagate itself, spreading from brain to brain. As my colleague N. K. Humphrey neatly summed up an earlier draft of this chapter:’… memes should be regarded as living structures, not just metaphorically but technically. When you plant a fertile meme in my mind you literally parasitize my brain, turning it into a vehicle for the meme’s propagation in just the way that a virus may parasitize the genetic mechanism of a host cell. And this isn’t just a way of talking—the meme for, say, “belief in life after death” is actually realized physically, millions of times over, as a structure in the nervous systems of individual men the world over.’

Consider the idea of God. We do not know how it arose in the meme pool. Probably it originated many times by independent ‘mutation’. In any case, it is very old indeed. How does it replicate itself? By the spoken and written word, aided by great music and great art. Why does it have such high survival value? Remember that ‘survival value’ here does not mean value for a gene in a gene pool, but value for a meme in a meme pool. The question really means: What is it about the idea of a god that gives it its stability and penetrance in the cultural environment? The survival value of the god meme in the meme pool results from its great psychological appeal. It provides a superficially plausible answer to deep and troubling questions about existence. It suggests that injustices in this world may be rectified in the next. The ‘everlasting arms’ hold out a cushion against our own inadequacies which, like a doctor’s placebo, is none the less effective for being imaginary. These are some of the reasons why the idea of God is copied so readily by successive generations of individual brains. God exists, if only in the form of a meme with high survival value, or infective power, in the environment provided by human culture.

Dawkins says more about memes (the chapter runs from 189 to 201), but I’ll confine my commentary to those two chapters. Before I do that, however, I’d like to quote two short paragraphs from the end of the chapter (pp. 199-200):

However speculative my development of the theory of memes may be, there is one serious point which I would like to emphasize once again. This is that when we look at the evolution of cultural traits and at their survival value, we must be clear whose survival we are talking about. Biologists, as we have seen, are accustomed to looking for advantages at the gene level (or the individual, the group, or the species level according to taste). What we have not previously considered is that a cultural trait may have evolved in the way that it has, simply because it is advantageous to itself.

We do not have to look for conventional biological survival values of traits like religion, music, and ritual dancing, though these may also be present. Once the genes have provided their survival machines with brains that are capable of rapid imitation, the memes will automatically take over. We do not even have to posit a genetic advantage in imitation, though that would certainly help. All that is necessary is that the brain should be capable of imitation: memes will then evolve that exploit the capability to the full.

That I believe is the core of Dawkins’ contribution, that the entity that directly benefits from cultural evolution is some cultural entity, not any individual human being, though the cultural entity is necessarily dependent on individual humans for its existence. Continue reading

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Tokyo Lectures in Language Evolution

This will certainly be of interest to rep typo readers. Info below:

We are pleased to announce that the Tokyo Lectures in Language Evolution will be held from the 2nd – 5th of April 2015 at the Komaba II Campus of the University of Tokyo. The event will bring together researchers from around the world to give an intensive series of courses and lectures introducing modern approaches to research on the origins and evolution of language.

Invited Speakers:

Registration Fees:

  • Faculty:        20,000JPY
  • Students:     Free

Please note, there are limited seats available so please register here to ensure your place.

Poster Session:

The event will host a poster session for participants to present their own work. Submission instructions are available here.

Key Points:

Dates:                         2-5 April 2015
Poster Call Deadline:  4 March 2015
Location:                     Tokyo, Japan
Any enquiries regarding the event should be directed to darwin@langev.tokyo.

We hope to see you in Tokyo!

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Serotonin and short-term/long-term orientation

This week I discovered that an analysis using Causal Graphs that James and I did in 2013 has been backed up by more recent data.  This demonstrates the power of Causal Graph analysis, which we’ll be discussing in our workshop on Causality in the Language Sciences (submission deadline extended!)

A recent paper demonstrates a correlation between various genetic factors and life history strategies (Minkov & Bond, 2015).  Minkov & Bond find that the prevalence of three gene polymorphisms (5-HTTLPR serotonin transporter gene, the androgen receptor gene AR and the dopamine receptor gene DRD4) correlate with measures of how willing people are to take risks, such as long-term/short-term orientation.

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We’re written before about 5-HTTLPR (here and here), which was previously associated with individualism/collectivism.  However, the paper above, and a previous one in 2014 by Minkov, Blagoev & Bond, find that the correlation is stronger for long-term/short-term orientation.

What’s interesting for us is that James and I predicted this in our 2013 paper on spurious correlations (the one with acacia trees and traffic accidents).  Here’s figure 4 from our paper, which was generated using a causal graph algoritm (explained in more detail in this post):

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The relevant part is here, which predicts that 5-HTTLPR prevalence is causally related to Long-term/short-term orientation, but is causally independent from collectivism:

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We suggested that the relationship between 5-HTTLPR and collectivism is mediated by the probability of migrating into harsher climates (a kind of risk-taking), and produced a computational model to demonstrate the principle (we also did some analyses which showed that measures of climate are correlated with 5-HTTLPR, but we haven’t reported these).

The more recent papers above also suggest that the genetic traits are linked with long-term/short-term orientation, but did so my greatly expanding the sample of genetic prevalence.  So how did we get our result?  In our analysis, we averaged 5-HTTLPR prevalence across countries, which is not realistic.  This makes me worried that the correlations are being inflated by non-independence of the samples.

The authors are confident of the robustness of the correlation:

“If all these associations were spurious, their association would be miraculous, especially at the national-regional level. If there is no real association between the LHSGF and the reported measures of LHS and TO, what then explains the extremely high correlations?”

However, as our paper argues, spurious correlations are more likely when datapoints are linked through historical descent or borrowing (Galton’s problem).  In the case of this paper, genetic traits are obviously historically related, and it’s likely that cultural values and life history strategies are also culturally transmitted.

I tried testing whether the correlation is robust to historical or contact relationships.  I used geographic proximity as a proxy for how closely related different cultures are.  For each country, I found the geographic coordinates of the capital city.  The graphs below demonstrate that there’s at least some geographic clustering (and a hit of a founder effect for the genetic data, as predicted by our migration model):

Geographic distribution of the genetic index

Geographic distribution of the genetic index

Geographic distribution of the life history strategy index

Geographic distribution of the life history strategy index

I then calculated the distance between each pair of countries in geographic terms (great circle distance), the National life history strategy genetic factor index and the genetic factors.  (for the genetic factors, I did a principal components analysis, as in Mikov & Bond, and used the first component, which had an eigen value of 2.62 and explained  65.5% of the variance, compared to Mikov & Bond’s 2.04, and 68%).

This gives us three distance matrices:  distance in miles, distance in life history strategy and distance in genetic traits.  I then used a Mantel test to compare these.

Genetic and life history measures are correlated (r = 0.88, p < 0.0001), as in the paper above (in the regression, r = 0.78-0.84).  Both the genetic and life history measures were correlated with geographic distance (r = 0.36, p < 0.0001; r = 0.27, p = 0.0003), which suggests that they are not independent (i.e. a country is likely to be more similar to its neighbour than a distant culture).

However, there is still a significant correlation between genetic and life history measures when controlling for geographic distance (r = 0.87, p = 0.0001).  In fact, the correlation is barely affected at all when partialling out the geographic distance.

So, it appears that the correlation is somewhat robust to controlling for non-independence.  But will it play out in the long-term?

Source data and analysis script: MikovBond_Mantel

Edit: Michael Minkov has been in touch, and argues that psychological phenomena, such as happiness, values, attitudes etc. can’t be borrowed across cultures.  They depend on particular economic conditions, which also can’t be borrowed in the same way that a word or an artefact can be borrowed.

Edit2: Above, I used raw distance, but log distance is probably a better measure.  Both genetic index and life history index are more strongly correlated with log geographic distance (r = 0.42, p < 0.0001; r = 0.35, p < 0.0001).  However, there’s not much difference in the correlation between genetic and life history measures when controlling for log geographic distance (r = 0.86, p < 0.0001).