Comment by acdha

This is a hard problem because those answers vary so much regionally. For example, according to this survey about 80% of RNs are white and the next largest group is Asian — but since I live in DC, most of the nurses we’ve seen are black.

https://onlinenursing.cn.edu/news/nursing-by-the-numbers

I think the downside of leaving people out is worse than having ratios be off, and a good mitigation tactic is making sure that results are presented as groups rather than trying to have every single image be perfectly aligned with some local demographic ratio. If a Mexican kid in California sees only white people in photos of professional jobs and people who look like their family only show up in pictures of domestic and construction workers, that reinforces negative stereotypes they’re unfortunately going to hear elsewhere throughout their life (example picked because I went to CA public schools and it was … noticeable … to see which of my classmates were steered towards 4H and auto shop). Having pictures of doctors include someone who looks like their aunt is going to benefit them, and it won’t hurt a white kid at all to have fractionally less reinforcement since they’re still going to see pictures of people like them everywhere, so if you type “nurse” into an image generator I’d want to see a bunch of images by default and have them more broadly ranged over age/race/gender/weight/attractiveness/etc. rather than trying to precisely match local demographics, especially since the UI for all of these things needs to allow for iterative tuning in any case.