What I understand from what GP was saying, is that AI Alignment today is more akin to trying to analyze and reduce error in an already fitted linear regressor rather than aligning AI behaviour and values to expected ones.

Perhaps that has to do with the fact that aligning LLM-based AI systems has become a pseudo predictable engineering problem solvable via a "target, measure and reiterate cycle" rather than the highly philosophical and moral task old AI Alignment researchers thought it would be.

Not quite. My point was mostly that the term made more sense in its original context rather than the one it's been co-opted for. But it was convenient for various people to use the term for other stuff, and languages gonna language.