[angry_moose]

The two issues I've had with every discovery algorithm:

"We have [favorite band] at home" - it picks things you like from your favorite band - instruments, tempo, etc then finds bad knockoffs that are superficially similar but painful to listen to.

The "Iron and Wine" problem - some bands are so generic that they tick every single similar box and flood your recommendations. For years, it didn't matter what band/genre I tried to find recommendations from, I got Iron and Wine.

[munificent]

I think a more fundamental problem is that people like music for very different reasons. Even the same person may define "similar" very differently at different points in time.

If I want music "like" "Groove is in the Heart", is it because:

* I want mid-tempo house-like dance music

* I want major key songs with female singing

* I want songs with rap interludes

* I want 90s music

* I want fun party music

* I want music that reminds of that awesome trip I took with my friends a few years ago where we played a bunch of songs over and over

There is no right answer to this question. But, outside of just looking for playlists, no music app I've seen gives you a way to specify in what way recommended music should similar to the current song.

I see this effect most acutely when I listen to something that happens to be popular. For many people "heard it a lot when doing this fun social thing" is one of the main reasons they like a particular song. This was true for me too when I was younger. But for me today, I'm mostly oblivious to popularity. I just like stuff that sounds a certain way.

Whenever I stumble onto a song that has a particular sound I like that happens to be well-known, the recommendation algorithm just starts throwing other popular stuff at me that sounds totally different.

[belthesar]

Ironically, this is something that I think Pandora solved quite well with their recommendation engine. By virtue of creating a station around a particular vibe, even if 5 playlists all started with the same seed song, weighting other songs up and down on each station would curate a different listening experience, by virtue of finding how those are similar. Where Pandora was limited (at least, the last time I used the service) was the pre-seeding process is a bit arduous and opaque. I'm not sure how you make that easy to interact with, as going a layer beneath to the "why" a song was recommended and allowing folks to influence the graph at that layer sounds like a daunting UX challenge.

[lowbloodsugar]

See, "Groove is in the Heart" makes me think of "Calling all units to broccolino" by Calibro 35. So I might add:

* Musicians having fun with instruments.

[gs17]

> it picks things you like from your favorite band - instruments, tempo, etc then finds bad knockoffs that are superficially similar but painful to listen to.

This is pretty bad if you have strong feelings about how much screaming a metal song should have. There are songs that fit exactly what I like except for that variable and Spotify does not get that I keep skipping them for a reason. It's rarely a "bad knockoff", but it definitely hits "painful to listen to".

It's really strange to me since it successfully creates playlists around different types of music that are sort of similar but shouldn't cluster together.

[feoren]

Don't forget the "featured artist" problem: the app is paid or otherwise incentivized to show you specific artists. Enshittification ensues.