:A mother rat will build a nest for her young even if she has never seen another rat in her lifetime. Similarly, a spider will spin a web, a caterpillar will create her own cocoon, and a beaver will build a dam, even if no contemporary ever showed them how to accomplish these complex tasks. That is not to say that these are not learned behaviors. It is just that these animals did not learn them in a single lifetime—they learned them over thousands of lifetimes. The evolution of animal behavior does constitute a learning process, but it is learning by the species, not by the individual, and the fruits of this learning process are encoded in DNA. – Ray Kurzweil, How to Create a Mind
It’s important to take this effect into account when comparing learning speeds for AI and humans. E.g AlphaGo may have learned for decades of human computation time, but human Go players take advantage of both biologically evolved mechanisms that make strategic thinking easier, as well as generations of accumulated cultural knowledge.
An important question will be: how much of this evolutionary learning are we actually using for science, engineering, social system design, programming?
If we can extrapolate from recent trends, then the answer seems to be “not that much”.
We’re very uncertain about how hard doing science is. As an example, I think back in the day we would have said playing board games that are designed to tax human intelligence, like playing chess or go is really quite hard, and it feels to humans like they’re really able to leverage all their intelligence doing it.
It turns out that playing chess from the perspective of actually designing a computation to play chess is incredibly easy, so it takes a brain very much smaller than an insect brain in order to play chess much better than a human. I think it’s pretty clear at this point that science makes better use of human brains than chess does, but it’s actually not clear how much better. It’s totally conceivable from our current perspective, I think, that an intelligence that was as smart as a crow, but was actually designed for doing science, actually designed for doing engineering, for advancing technologies rapidly as possible, it is quite conceivable that such a brain would actually outcompete humans pretty badly at those tasks.