The quality of the upper echelon of art may be raised, but there's still a discovery problem there. Having to sift through stuff to find the gems is already an issue imo. The OP makes a decent (pessimistic) point
My opinion on the problem of "too much content to watch in several lifetimes" will not be solved on the supply side, but the demand side.
All content is not created equal: we are social animals and what people around us do interests us much more, even if it is of lower quality. So, if anyone can generate professional-looking creative projects with relative little effort, we'll gravitate towards people creating content on niche subjects that interest us; thus creating small communities with high engagement. Even if they have low watch count, they'll matter to those participating in them. Fanfic communities already work that way.
There always be a place for conventional mainstream media outlets creating run-of-the-mill high-production-value works, with themes averaged to appeal to the masses; it's just that they'll have a lot more competition from communities of the first type.
Consider the extreme low quality visuals of SouthPark. They used their low quality imagery as joke enhancement for their presenting ideas far more sophisticated than the majority of animated media.
I might be wrong, but I could imagine that AI will push the absoulute maximum out of human creativity. To beat AI, you'll truly need to make something outstanding and I think there will be people achieving that and truly pushing the boundaries of creativity and art forward, in ways we haven't seen before. And those people will be rewarded. Everyone will have to step up their game.
Probably, artists will use AI not to "beat" it, but as a base tool for exploring the space of possibility and expanding it into new territories. People will see AI as just one more tool in the toolbox.
People using Dall-E or Midjourney naively will be like those unremarkable classicism painters in the late XIX century doing realistic yet conventional paintings which nowadays you can create as studio photographs.
Meanwhile, brilliant artists will train new AI models throwing in data collections that have never been seen before as their training input, to generate completely new styles - just like the -ism movements threw all academic conventions away in pursue of new art styles, bringing us modern and postmodern art.
I think AI will be pretty good at doing recommendations. Show you a bit of random, get your likes and dislikes, exploit what the algorithm learned. TikTok does this well already and, I expect, will continue to do well when the content is AI generated.
I work in the area of recommendations, and this is not a solved problem at all.
You can only recommend what has been shown (without doing coldstart).
One major issue is that other forms of content than 30sec clips can't easily utilize TikToks way of bootstrapping engagement when the item is fresh. Not everyone will understand or appreciate a "new Shakespeare" and it may fall by the wayside.
I too hope it gets better, but it's hard to replace a panel of experts that have sifted through their subject when it comes to quality recommendations in some fields.
Tiktok optimises for what people spend a long time looking at, but I don’t think that anyone would claim the metric it uses is what we would want to define as quality in the broader sense.
I seriously wonder if Tiktok uses eye gaze tracking in their interest assessments. If people's eyes follow the same gaze pattern on a clip repeatedly, that's a damn clear indicator of interest.
My personal hypothesis (based on nothing) is that TikTok just uses the very strong signal of watch time. If you watch a clip all the way, or multiple times, that's good. If you skip early - that's bad.
When I had Netflix I remember being frustrated that Netflix would recommend me shows "based on" content I had watched for a few minutes, decided I didn't like, and backed out of. Why would you recommend me content if you have a strong signal I dislike it?
AI won't be designed to serve the users recommendations, but what is in the best interest of the person designing the AI. There was a pretty good article on HN about this, yesterday I think, that covered this well.