Unlike the coding models it seems like the generative art models do a lot more harm than good.

I've been having some similar thoughts lately about some application spaces being more harmful than others.

Coding, for example, seems somewhat benign, because code has to fulfil clear metrics: Either it works or it doesn't. Either it performs or it doesn't. As long as you are able to provide those metrics, you can to some extent treat it as a black box without losing much from a system view (lifecycle, long-term maintenance, keeping things working, broader qualified efficiency like re-use are of course other stories).

But on the other hand, delegating decision-making and thinking to models feels plain harmful to me. I have so many stories around me from office settings these days: "We have to pre-pone meeting XYZ, and we don't have enough time to prepare, so I made this AI analysis <power point deck>". This was then mis-prompted to fit a foregone conclusion, no one has time to do it or capacity to refute a 2000 word slop deck (except by slopping back), and crazy stuff becomes plan of record. This is really going to be a problem for organizations ...