This is the original version submitted to BBS. It was
slightly edited before publication.
ABSTRACT
The implications these models have for memetics are
discussed. The results demonstrate the power of memes (in this case
colour words) to influence both concept formation, and the creation
of innate concepts. They provide further evidence for the memetic
drive hypothesis, with implications for the evolution of the human
brain and for group differences in categorisation.
MAIN TEXT
Steels and Belpaeme’s results are, as they point out, among the
first computer simulations to show “how the memetic evolution of
language and meaning are possible”. They do not explore the further
implications of this for memetics, and I propose to do so here.
The basic principle underlying memetics is that memes (including
words) are replicators; they can compete with each other and with
other replicators in both memetic evolution and meme-gene
co-evolution. This contrasts with some other theories of cultural
evolution in which, as Wilson puts it, the genes will always keep
culture on a leash (Lumsden & Wilson 1981). For memetics there is no
obvious leash; either replicator can take on the role of dog or
owner under different circumstances. These interactions have
previously been modelled (e.g. Bull, Holland & Blackmore 2000,
Kendal & Laland 2000) and are modelled in new ways by Steels and
Belpaeme.
The critical experiment for meme-gene co-evolution is in section 4.4
where they explore the influence of language on the genetic
evolution of colour concepts. In their model, not only do word forms
compete to describe the colour space, but agents’ concepts evolve
“genetically”. In this key experiment communicative success of the
agents determines fitness, so that agents with the best
communicative skills are used to make mutated copies for the next
generation.
There are two process here that are highly relevant to memetics.
First (section 4.3), when the simulation is run many times the
successful memes (colour words) are different each time, which in
turn influences the colour concepts the agents adopt (the Sapir-Whorf
thesis). This shows the power of memetic evolution to influence
concept formation. Second (section 4.4), when communicative success
determines fitness, the adopted concepts become genetically
assimilated. This is the process that I have previously called
memetic drive (Blackmore 1999). It implies that the direction taken
by memetic evolution (in this case the winning words) drives the
direction taken by genetic evolution (in this case innate colour
categorisation). In other words, the vagaries of memetic success end
up influencing the genetically encoded colour categories.
Although Steels and Belpaeme do not mention this, it seems likely
that as the simulation proceeds, the mutated agents will
increasingly start with a fitness advantage over agents like those
that started the simulation, because their innate colour concepts
map more closely onto the memetically evolved colour words in use in
that population. In other words, outsiders would be at a
disadvantage in learning the colour words and so (in this model)
less likely to become good communicators and survive to the next
generation. This would be another reason why, when cultural or
memetic factors play a role in fitness, the divergence between
populations becomes more pronounced.
If this process occurs in human evolution, there are two significant
implications. First, our brains could have been shaped by the
results of memetic evolution. That is, the words that happened to
evolve in the past (and they might easily have evolved differently),
have influenced the ways in which we innately categorise the world.
Second, it implies that differences between populations could be
greater, or form more quickly, than is assumed on purely genetic
models or on models of cultural evolution that do not treat their
cultural units as replicators.
Is this plausible? I think so. There is plenty of evidence that, in
human mate selection, being articulate, artistic and creative
(Steel’s and Belpaeme’s “communicative success”) is highly prized.
Miller (2000) interprets this in terms of runaway sexual selection,
but the models used here demonstrate the memetic alternative.
Although it is generally assumed that people from any ethnic
background are equally capable of learning any human language
(Pinker 1994), there may still be differences to be found if we knew
what to look for. The methods used here would allow the relevant
variables, such as population size and degree of isolation, to be
modelled, and specific predictions made.
Steels and Belpaeme have confined their models to colour concepts
and words, and to some extent have generalised their findings to all
of language. The memetic drive hypothesis can be extended well
beyond this to the idea that many aspects of brain design are the
way they are because of the history of memetic evolution. For
example, the way religious memes evolved in the past (including
rituals, or concepts of gods and spirits) could have shaped our
peculiarly religious natures (Dawkins 1989, Blackmore 1999) and thus
explain the persistence of religious concepts even in highly
educated societies. The way that musical memes happened to evolve
could have designed our musical abilities (Dennett 1999) thus
explaining a skill that Pinker (1997) describes as being
biologically “useless”.
More controversially, the process of memetic drive might have
implications for understanding group differences in cognitive
ability. Indeed this troublesome issue might usefully be reframed,
building on Steels and Belpaeme’s work, in terms of group
differences in innate categorisation. Making plausible assumptions
about human population sizes, degree of isolation, and timescale,
the methods developed here could be used to model human gene-meme
co-evolution and find out whether we should expect to see existing
human populations that differ in their innate ways of categorising
the world because of differences in their past memetic evolution. In
these and other ways Steels and Belpaeme’s work should prove
valuable for testing many memetic hypotheses.
References
Blackmore, S.J. (1999)
The Meme Machine, Oxford, Oxford University Press
Bull, L, Holland, O. and
Blackmore, S. (2000) On meme-gene coevolution. Artificial Life,
6, 227-235
Dawkins,R. (1976) The
Selfish Gene, Oxford, Oxford University Press (new edition with
additional material, 1989)
Dennett, D. (1999) The evolution of culture. Charles Simonyi
Lecture, Oxford, February 17.
http://www.edge.org/3rd_culture/dennett/dennett_p1.html
Kendal, J.R. and
Laland, K.N. (2000) Mathematical models for memetics. Journal of
Memetics 4(1)
Lumsden, C.J. and
Wilson,E.O. (1981) Genes, Mind and Culture. Cambridge, Mass.,
Harvard University Press.
Miller, G. (2000)
The Mating Mind: How Sexual Choice Shaped the Evolution of Human
Nature, London, Heinemann
Pinker, S. (1994) The Language Instinct
New York, Morrow
Pinker, S. (1997) How the Mind Works.
Penguin
