Online research in philosophy

This commentary stresses the importance of Atran's work for the development of a new cognitive anthropology, but questions both his particular use of Dawkins's “meme” model and the general usefulness of the meme model for understanding folk-taxonomies as cultural phenomena.

The meme is an evolutionary replicator, defined as information copied from person to person by imitation. I suggest that taking memes into account may provide a better understanding of human evolution in the following way. Memes appeared in human evolution when our ancestors became capable of imitation. From this time on two replicators, memes and genes, coevolved. Successful memes changed the selective environment, favouring genes for the ability to copy them. I have called this process memetic drive. Meme-gene coevolution produced a big brain that is especially good at copying certain kinds of memes. This is an example of the more general process in which a replicator and its replication machinery evolve together. The human brain has been designed not just for the benefit of human genes, but for the replication of memes. It is a selective imitation device.

Dawkins’ concept of the meme pool, essentially equivalent to Popper’s World 3, is considered as an expression in modern terms for what Averroes knew as the ‘active intellect’, an immortal entity feeding into, or even creating, the ‘passive intellect’ of consciousness. A means is thus provided for reconciling a materialist Darwinian view of the universe with a conception of non-personal immortality. The meme pool/active intellect correspondence provides a strong basis for regarding science as a communal enterprise producing enrichment of the meme pool and expansion of consciousness, and emphasizes the virtues of memetic conservation in relation to vanishing cultures.

All around us the techno-memes are proliferating, and gearing up to take control; not that they realise it; they are just selfish replicators doing what selfish replicators do – getting copied whenever and wherever they can, regardless of the consequences. In this case they are using us human meme machines as their first stage copying machinery, until something better comes along. Artificial meme machines are improving all the time, and the step that will change everything is when these machines become self-replicating. Then they will no longer need us. Whether we live or die, or whether the planet is habitable for us or not, will be of no consequence for their further evolution.

Darwinian theories of culture need to show that they improve upon the commonsense view that cultural change is explained by humans? skillful pursuit of their conscious goals. In order for meme theory to pull its weight, it is not enough to show that the development and spread of an idea is, broadly speaking, Darwinian, in the sense that it proceeds by the accumulation of change through the differential survival and transmission of varying elements. It could still be the case that the best explanation of why the idea has developed and spread is the conscious pursuit of human goals. Meme theory has the potential to do explanatory work in diverse ways. It can challenge the goal-based account of cultural change directly. Other possibilities for meme theory include explaining the acquisition of our goals and showing that memes and genes evolve together, each affecting the selective forces acting on the other. Raising the question of meme theory?s explanatory payoff brings out the importance of the ?selfish-meme? idea and the idea of non-content biases. Both have the potential to challenge the claim that our goals are in the driver?s seat. In order to show that a Darwinian theory of culture is more than an idle redescription, however, it is necessary to make the case that it offers explanatory gain over its competitors, in particular over the common sense goal-based account.

Meme replication is described as a 4-stage process, consisting of assimilation, retention, expression and transmission. The effect of different objective, subjective, intersubjective and meme-centered selection criteria on these different stages is discussed.

The science of memetics faces a serious problem. The concept of the meme emerged from evolutionary biology and the theory of replicators, and within this context it is well understood, if highly controversial. But out on the web, and in popular discourse, the word ‘meme’ is horribly abused. It is confused with ‘idea’ or ‘concept’ or treated as something ethereal or non-material floating about quite separate from behaviours and artefacts.

If there is one proposition that would-be memeticists agree on, it is that the flourishing of an idea-its success at replicating through a population of minds-and the value of an idea-its truth, its scientific or political or ethical excellence-are only contingently and imperfectly related. Good ideas can go extinct and bad ideas can infect whole societies. The future prospects of the meme idea are uncertain on both counts, and the point of this book is not to ensure that the meme meme flourishes, but to ensure that if it does , it ought to. It works toward this worthy end by creating a landmark, a fixed point not of doctrine but of evidence and methods, some shared acknowledgment among some leading proponents and critics about how the issues ought to be addressed.

This paper describes a computational model of how ideas, or memes, evolve through the processes of variation, selection, and replication. Every iteration, each neural-network based agent in an artificial society has the opportunity to acquire a new meme, either through 1) INNOVATION, by mutating a previously-learned meme, or 2) IMITATION, by copying a meme performed by a neighbor. Imitation, mental simulation, and using past experience to bias mutation all increase the rate at which fitter memes evolve. Memes at epistatic loci converged more slowly than memes at over- or underdominant loci. The higher the ratio of innovation to imitation, the greater the meme diversity, and the higher the fitness of the fittest meme. Optimization is fastest for the society as a whole with an innovation to imitation ratio of 2:1, but diversity is comprimized.