“This preservation of favourable variations and the rejection of injurious variations, I call Natural Selection.” - Darwin

Discussions on the risks of AI often fixate on what a handful of powerful actors decide. What capabilities will Anthropic prioritize? Will OpenAI open-source more models? What safety testing will Congress require?

But there’s another force shaping AI that acts independently of our best intentions: natural selection.

In The Selfish Gene (1976), Richard Dawkins described how evolution by natural selection might not require genes or even biological material. According to Dawkins, genes are just one form of replicator - “any entity in the universe of which copies are made”. Digital files are replicators. Ideas are replicators.

AI models are–or embed–replicators. Not all replicators lead to natural selection. Evolution, according to Dawkins, results from the “differential survival of replicators.”

Evolutionary biologist Richard Lewontin spells out the three criteria that are necessary and sufficient for a population to evolve via natural selection:

• Variation: Members of a population must differ from one another. Without variation, there are no differences in traits to select from.
• Heritability: Offspring resemble parents. Without heritability, there could be no lasting change from generation to generation.
• Selection: Different variations reproduce at different rates. Without selection, a population wouldn’t tend towards one variation over another.

So is AI evolving via natural selection? Do today’s LLMs meet these criteria?

Full post (no paywall): https://bturtel.substack.com/p/darwins-llms