[meebob]

I do appreciate that the way in which a piece of code "works" and the way in which an piece of art "works" is in some ways totally different- but, I also think that in many cases, notably automated systems that create reports or dashboards, they aren't so far apart. In the end, the result just has to seem right. Even in computer programming, amateur hour level correctness isn't so uncommon, I would say.

I would personally be astonished if any of the distributed systems I've worked on in my career were even close to 95% correct, haha.

[lycopodiopsida]

Understanding what you are plotting and displaying in the dashboard is the complicated part, not writing the dashboard. Programmers are not very afraid of AI because it is still just a glorified fronted to stackoverflow, and SO has not destroyed the demand for programmers so far. Also, understanding the subtle logical bugs and errors introduced by such boilerplate AI-tools requires no less expertise than knowing how write the code upfront. Debugging is not a very popular activity among programmers for a reason.

It may be that one day AI will also make their creators obsolete. But at that point so many professions will be replaced by it already, that we will live in a massively changed society where talking about the "job" has no meaning anymore.

[azornathogron]

A misleading dashboard is a really really bad. This is absolutely not something where I would be happy to give it to an AI to do just because "no one will notice". The fact that no one will notice errors until it's too late is why dashboards need extra effort by their author to actually test the thing.

If you want to give programming work to an AI, give it the things where incorrect behaviour is going to be really obvious, so that it can be fixed. Don't give it the stuff where everyone will just naively trust the computer without thinking about it.