If I was God Emperor for any sort of content algorithm, I’d want to try a decentralized “simulated annealing” of feature vectors based on up/down votes, subscriptions, etc. That lets you create linear combinations (eg on Wikipedia the vector for King - Man might be close to Royalty) and share them around on different platforms. This makes The Algorithm^TM a lot more transparent and user-driven, since you can feasibly program on a per-user basis all sorts of policies for how their own preference vector updates, or they could have layers of linearly combined vectors for base style, mood, binging, etc.

What I like about this is it doesn’t presume some kind of inherent value - it implies a philosophy that everything is equally valid/valuable to someone, and people just have different preferences for what they prefer. If it’s something utterly vile that everyone downvotes into oblivion, that’ll naturally sink into the recesses of feature-space that occupy the opposite of whatever “all humans” value. It’s also dead simple to implement, you just need an update policy (N-dimensional modular incrementing?) and a way to search a database by a given metric (cosine distance is the new hotness with AI, but back when I first thought of this I used hamming distance).