I think it would be very useful to put a short summary of that piece here. The piece would really benefit from a summary abstract for this audience, and that could go in the link post here.

I skimmed it and I think I'd summarize it as "maybe we should apply something like human psychometrics to LLMs for alignment". A brief description of psychometrics would also be useful.

I may have more comments after reading it more carefully.

I know a ton about psychometrics when applied to humans, and I've been thinking on and off about whether some of these methods could be applied to neural networks. Overall I'm bearish about the prospects, but I eventually got one idea that stayed quite promising even after thinking about it for a while. I've been distracted from implementing it by an idea for solving the alignment problem, though, so I've been shelving it for a bit, but if anyone less distractable wants to collaborate then I'd be up for that. It needs to wait until I've published my idea on the alignment problem as that seems the highest priority.

Basically the issue is, psychometrics in humans isn't magic. You've got ability measurements which basically work by giving people a bunch of example tasks from the ability you want to measure, and then you've got other measures e.g. personality measures which basically rely on people remembering their own tendencies. Neither seems to promise all that much innovation for LLMs.