The problem is that AIs are gaining skills faster than humans, thanks to distillation of human knowledge of its users into AI.

And because AIs are difficult to understand internally (for at least 3 different reasons), any skill you gain using it is effectively cargo-culting. It's a fast moving, changing target, and there is no guarantee, at any point, that you have learnt something useful that's relevant for the future.

I do worry about people skills being lost through use of AI, but they are not being completely lost, but rather locked up in the ivory towers of a few AI models.

On the other hand, we already lived in a world where we are dependent on skilled minorities. Most people don't know how to build a computer or a chip, and most SW engineers don't know how their compiler or OS works; yet we use these things everyday.

I think we need a new free software (free AI?) movement. Open weights is not enough, that's still like an opaque binary. The other two obstacles to understanding are (1) the internal language of embeddings and (2) the natural language on the communication interface. We need AI models that we, as humans, can understand, in principle.

In free software movement, it's important for the users to understand the software in principle; the source code availability is just the means. Here, we face the same imperative.