What's interesting is how AI makes this problem worse but not actually "different", especially if you want to go deep on something. Like listicles were always plentiful, even before AI, but inferior to someone in substack going deep on a topic. AI generated music will be the same way, there's always been an excessive abundance of crap music, and now we'll just have more more of it. The weird thing is how it will hit the uncanny valley. Potentially "Better" than the crap that came before it, but significantly worse than what someone who cares will produce.

DJing is an interesting example. Compared with like composition, Beatmatching is "relatively" easy to learn, but was solved with CD turntables that can beatmatch themselves, and yet has nothing to do with the taste you have to develop to be a good DJ.

In other words, AI partially solves the technique problem, but not the taste problem.

In the arts the differentiators have always been technical skill, technical inventiveness, original imagination, and taste - the indefinable factor that makes one creative work more resonant than another.

AI automates some of those, often to a better-than-median extent. But so far taste remains elusive. It's the opposite of the "Throw everything in a bucket and fish out some interesting interpolation of it by poking around with some approximate sense of direction until you find something you like" that defines how LLMs work.

The definition of slop is poor taste. By that definition a lot of human work is also slop.

But that also means that in spite of the technical crudity, it's possible to produce interesting AI work if you have taste and a cultivated aesthetic, and aren't just telling the machine "make me something interesting based on this description."