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>Could you please send me by Email your text on memes?
I include the HTML source in a separate message, so that you can use the links.
>I am wondering whether anyone has really pushed forward theorizing about
>memes from the ideas outlined by Dawkins.
I have and a several other people have, some of which are referenced in the
text you requested. It is true that the field is still in its infancy and
the different approaches need to be tied together. But I am convinced that
much better models can be developed than the ones we have seen until now,
and there certainly is quite some progress beyond Dawkins. (including
corrections of some of Dawkins's assumptions).
> I have to say that so far I
>have not been persuaded that there's anything much to say; its a nice
>way of looking at things, but (perhaps) that's all. Memetic information
>is arguably so mutable in human brains that attempts to study it are
>likely to be stymied for the foreseeable future. We study genetics by
>studying what happens to individual genes in different situations; but
>memes keep changing their nature so much it's not clear to me anyone can
>do that. Or have they? I'd be grateful for any clarification.
The mutability is one problem, the fact that memes are difficult to define
or distinguish is another (related) problem. However, the reasoning Dawkins
made about genes can be largely extended to genes: you don't need to know
how exactly a certain gene is structured in order to make predictions of
the kind "if there is genetic variability over a certain dimension, then in
particular circumstances certain genetically determined features will
become more prominent, while others will recede". (cf.
http://pespmc1.vub.ac.be/MEMSTRUC.html). You don't need to know the genetic
code for resistance to heavy metals to be able to predict that organisms
living in polluted environment will develop such resistance, and that this
resistance will be stored in the genes. Similarly, you could develop models
predicting that certain types of meme-induced behavior will develop or
disappear in certain situations.
For example, Dawkins has recently compared religions to "viruses of the
mind", implying they are nothing more than memetic parasites and thus by
definition harmful. However, it is well-known that parasites can be
classified according to the dimension of "virulence": the more easily a
parasite spreads to other hosts, the more harmful it can afford to be to
the present host. The less easily the parasite can infect other hosts, the
more it is to the parasite's benefit to keep the host in good shape. In the
limit case where the parasite can only reproduce when the host reproduces,
the good of the host (inclusive fitness) becomes identical to the good of
the parasite, and the relation turns into a mutually beneficial type of
symbiosis.
In that view, religions too can be classified according to virulence: e.g.
the more dangerous types of sects correspond to memes that can only survive
by actively seeking new converts. The behavior induced by the sect's belief
(e.g. tendency to commit collective suicide) is too harmful for the host to
allow long term survival of the "parasite" in the host or the host's
offspring. On the other hand, most long time established religions (e.g.
catholicism, buddhism, islam) etc. are normally transmitted "vertically",
from parent to offspring, and not "horizontally" from preacher to convert.
Evolutionary theory would predict that such memes are mostly beneficial.
This argument was developed by my colleague Ben Cullen at a Symposium I
organized last May. I have myself argued for the beneficial effect of
traditional religious memes on evolutionary grounds, extending the work of
the famous anthropologist Donald T. Campbell in a memetic framework. See:
Heylighen F. (1992): "Selfish Memes and the Evolution of Cooperation",
Journal of Ideas , Vol. 2, #4, pp 77-84.
Heylighen F. & Campbell D.T. (1995): "Selection of Organization at the
Social Level: obstacles and facilitators of metasystem transitions", World
Futures: the Journal of General Evolution 45, p. 181-212.
This is just one example of the way in which theorizing about memes can
lead to non-trivial, verifiable predictions. Of course, as you say,
because of their fuzzy and variable nature memes are inherently difficult
to model, but I have hope that models developed in Artifical Intelligence
to represent knowledge (e.g. production rules) can be applied to model
memes, thus allowing simulation of meme spread and evolution over different
agents. (this would just be a multi-agent version of genetic algorithms, or
similar alife type evolutionary simulations). The main thrust of my own
research is the development of a system of selection criteria that
determine which memes (or pieces of knowledge) will survive and which memes
won't. These criteria are different from the criteria describing genetic
evolution because of the way memes are transferred: by "multiple parenting"
(cf. http://pespmc1.vub.ac.be/MEMGEN.html).
________________________________________________________________________
Dr. Francis Heylighen, Systems Researcher fheyligh@vnet3.vub.ac.be
PESP, Free University of Brussels, Pleinlaan 2, B-1050 Brussels, Belgium
Tel +32-2-6292525; Fax +32-2-6292489; http://pespmc1.vub.ac.be/HEYL.html