Memory, Social Networks, and Language: Probing the Meme Hypothesis II

Is Memetics a Science? Lessons from Language Evolution

Morten Christiansen

Abstract

Dawkins (1976) introduced the notion of a meme—an imitation-based replicator analogous to a gene—to explain the spread of cultural information across minds. Cultural evolution is construed in terms of Darwinian natural selection: Memes compete among themselves to propagate across minds. Memes that better fit the cultural domain will survive and multiply whereas less fit memes will tend to disappear. In this talk, I argue that although current memetics may provide a useful perspective on cultural evolution within the ideosphere (e.g., the spread of scientific ideas, entertainment, or wearing baseball caps backwards), the meme construct lacks the necessary constraints to provide a scientific explanation for certain key cultural products, such as language. In particular, memetic approaches do not appear to be able to explain why language is structured as it is, and why children learn language so readily; that is, why there is such a close fit between the structure of languages and the mechanisms by which languages are learned and used.

Because language is fundamentally a cultural product, memes has been suggested to provide important insights into the evolution of language (e.g., Blackmore, 1999; van Driem, 2005). As typically construed, memes are free to evolve within the cultural domain without noteworthy biological constraints, and there appear to be no intrinsic relationship between memes and the human brain. Memes typically are acquired via explicit instruction or conscious imitation with no discernable patterns of acquisition; and many memes are not universally acquired due to their inherent complexity (e.g., memes corresponding to scientific ideas, Dawkins, 1976). In contrast, language acquisition is universal, takes place effortlessly with little or no direct instruction, and is characterized by gradual progress interspersed by reliable milestones. Thus, language is very different in nature not only from the typical meme examples, such as catch-phrases or ways of building arches, but also from so-called meme complexes involving many inter-related ideas, customs, and concepts, such as Christianity or Islam (Dawkins, 1976).

Drawing on lessons from research suggesting that the evolution of language has been shaped by the brain (Christiansen & Chater, in press), I argue that a scientific approach to cultural evolution must uncover the specific constraints that shape the evolution of particular cultural products. I therefore propose to replace the notion of memes as replicators with the idea of memes as organisms, adapted to a specific environmental niche. This organismic reconceptualization of memes might make it possible to produce testable memetic hypotheses by incorporating the empirical constraints arising from specific meme environments. I conclude that although this proposal could move some part of memetic theorizing into the domain of empirical enquiry, many parts of memetics are likely to remain outside the purview of science

References

Blackmore, S. J. (1999) The meme machine. Oxford University Press.

Christiansen, M.H. & Chater, N. (in press). Language as shaped by the brain. Behavioral & Brain Sciences [target article for multiple peer commentary].

Dawkins, R. (1976) The selfish gene. Oxford University Press.

van Driem, G. (2005). The language organism: The Leiden theory of language evolution. In J.W. Minett & W.S.-Y. Wang (Eds.), Language acquisition, change and emergence: Essays in evolutionary linguistics (pp. 331-340). Hong Kong: City University of Hong Kong Press.

Morten Christiansen is Associate Professor in the Department of Psychology and Co-Director of the Cognitive Science Program at Cornell University (Ithaca, New York, USA). His research focuses on the interaction of biological and environmental constraints in the processing, acquisition and evolution of language, which he approaches using a variety of methodologies, including computational modeling, corpus analyses, psycholinguistic experimentation, neurophysiological recordings, and molecular genetics. He is the author of more than ninety scientific papers and has edited volumes on Connectionist Psycholinguistics, Language Evolution, and most recently, Language Universals.