Charlie Stross has been blogging about the minimum population needed to sustain an advanced industrialized civilization (and why he thinks this means no colonization of space etc). This is a topic I have no expertise on beyond a broad interest in the less Sunday-supplement inclined versions of evolutionary anthropology, which have given this question some thought. See, for example, Robert Boyd and Peter Richerson’s account of “the Tasmania effect” (p. 272 of The Origin and Evolution of Cultures ) as excerpted below. While I can’t vouch for this argument myself (and it seems to be based more on modeling than on empirical evidence, which is reasonable when you don’t have as much direct evidence as you would like, but not entirely satisfying), it is interesting and (to me) plausible,. Further, it suggests an additional twist to Charlie’s argument – that because human beings cannot learn precisely what their teachers are trying to convey, you need a larger population to counter for the lossy transmission of useful techniques.
What is less well understood is the extent to which technology is likely a product of large-scale social systems. Henrich has analyzed models of the “Tasmanian Effect.” At the time of European contact, the Tasmanians had the simplest toolkit ever recorded in an extant human society … Archaeological evidence indicates that Tasmanian simplicity resulted from both the gradual loss of items from their own pre-Holocene toolkit and the failure to develop many of the technlogies that subsequently arose only 150km to the north in Australia … Henrich’s analysis indicates that imperfect inference during social learning, rather than stochastic loss due to drift-like effects, is the most likely reason for this loss. This suggests that to maintain an equilibrium toolkit as complex as those of late Pleistocene hunter-gatherers likely required a rather large population of people who interacted fairly freely so that rare, highly skilled performances, spread by selective imitation, could compensate for the routine loss of skills due to imperfect inferences.