Darwin’s ‘Origin of Species’, published in 1859, provided the first plausible mechanism for evolution. Just 7 years later Mendel published his work on trait inheritance, after meticulously cross-breeding 29,000 pea plants. He exposed the gene as the unit of heredity – a crucial gap in Darwin’s work – and unfortunately, no one really noticed. After his death, his personal papers were burned by his fellow monks, presumably to make space for something more pious. Luckily some of his letters survived, and were later rediscovered in the monastery archives, and modern Genetics was born.
What Mendel had discovered is the rules whereby genes are transmitted, something that hasn’t fully been established for memes. Psychology, anthropology, and marketing have predictive theories for which memes are likely to be transmitted or recombined in the brain, but we do not have a full accounting like Mendel achieved. Given this basis was in place, Fisher and others were able to formalize the maths in the 1930s, of how multiple genes interacted through time in a large population, and Genetics became more robust to scientific standards. This work validated Darwin’s hypothesis, that many small changes over long time spans were capable of yielding large evolutionary effects. Then Watson and Crick’s 1953 discovery of the Double Helix structure of DNA, finally revealed the source code. DNA was what governed the behavior revealed by the maths. Crucially it gave us something to edit, leading to many great advancements in the 20th Century.
We know how neurons work, and there’s a wealth of information about how they combine in regions to elicit observable effects when stimulated. However we can’t really explain the emergent property of consciousness: without which we can’t simulate the brain or fully understand how it functions. For that we may have to wait until the invention of true artificial general intelligence, or at least until machine learning becomes sufficiently advanced as to simulate primitive functions of the brain. In the meantime, progress can be made much like it is being done in machine learning: by treating the brain as a black box - examining what goes in, and what comes out - and then inferring how it works from there.
Once we’ve crossed that bridge, we can borrow more heavily from Genetics: after all genes and memes are both just information. Hamilton and others in the 1960s devised formulas explaining how altruism evolved: “I would lay down my life for two brothers or eight cousins”, which can be instructive in memetic survival analysis. We don’t need to know how memes transmit to unlearn the usual thinking that memes exist for the benefit of organisms. Instead, as with genes, it has been shown that organisms are merely vehicles for carrying around genes and memes. Of course genes aren’t really in control – natural selection is – but we’d be wise to adopt this helpful analogy and use it in our predictions.
Part of the reason for all the popular attention received by genetics – and why memetics exists at all – is that Dawkins synthesised all the prevailing scientific wisdom into an international best seller, “The Selfish Gene”, published in 1976. In this book the word ‘meme’ was coined, as the information equivalent of a gene. Memetics shows great promise, but is still pre-Mendel, pre-Fischer, pre-Watson & Crick. It had its time in the limelight courtesy of Dawkins at the same time as Genetics, but with none of the underlying body of scientific work to back it. Nobody has meticulously traced the inheritance of thousands of memes. Nobody has worked out the math to predict meme transmission. Nobody has revealed the source code that would make memes programmable. With advancements in machine learning, virtual reality, and neural imaging, perhaps memetics’ own Mendel, Fisher, Crick & Watson are right around the corner.