I find ironic that we are talking about ML where we have vectors of thousands of quantities and then we go to measure social/economic stuff with one (or a couple of numbers).

The general discourse (news, politicians, forums, etc.) over a couple of measures will always be highly simplifying. The discourse over thousands of measures will be too complex to communicate easily.

I hope that at some point most people will acknowledge implicitly that the fewer the number of measures the more probable is that it is a simplification that hides stuff. (ex: "X is a billionaire, means his smart"; "country X has high GDP means it's better than country Y with less GDP" and so forth).