[usgroup]

I think that you make some excellent points.

I think we need to stop conflating maths and abstraction with genius and general intelligence: it's too important to be politicised. I also think we should assume that any healthy adult can learn to do maths well by virtue of nothing other than having a human brain. If the normal healthy adult does not do maths well then that should be treated as a pedagogical problem rather than a reason to stratify society.

I think that maths in many ways can be treated analogously to language, and I think what we need to do is express maths in a way better suited for normal human language faculties. I very much like the artificial language Lojban as an architecture ingraining combinatorial and first-order logic into regular self-expression. Imagine speaking Lojban your whole childhood and having this rich vat of lived logical analogies to draw on when learning.

Effecting minds in this way and focusing on median improvements in the functionality of the majority is in my opinion has many many times more potential than any sort of elite screening or stratifying programme.

[Retric]

Better tools are also going to shift the frontier.

To use Neural Networks as a poor analogy. Given identical training data and different random starting weights you end up with different end results. Thus, even with identical potential at conception people would end up with different strengths naturally.

Better training clearly shifts the median, but when you start talking about populations of extreme outliers from a billon+ people that’s going to be meaningful. Especially as differences compound over time.

Currently their is a trickledown effect where useful techniques end up shifting the landscape. RSA encryption pushing little bits of what would otherwise be abstract number theory into a few high school classrooms etc.