humans vs. algorithms: the RIYL listening exploration cycle

I'd like to hear more about what the people who have put their lists up prefer so far (the human or algorithm recommendations). I'm still mulling on what to list, also I don't have premium spotify so I'm not sure if I can do playlists on there and might need to ask someone else to do that for me and pass on the recommendations.

you can make playlists with the free version, at least you can on a computer, I'm not sure about mobile

hey karl, you definitely need this in your playlist:

Prefab Sprout - Bonny

^ has that radio-friendly springsteen sheen, the subtle mac-esque backing vocals, and the bittersweet lyricism and general strummyness of the go-betweens

also it's the best. song. ever. (obv)

having said that, this one probaly has more of the 'Little Lies' flavour:

Prefab Sprout - Appetite

Glenn's algorithmic playlist had Cars and Girls which I thought was a good match.

ha i didn't see that! basically just put a bunch of prefab on it, i'm at one with the droids on this

Recommended for Karl:
Suzanne Vega - Solitude Standing

I'd like to hear more about what the people who have put their lists up prefer so far (the human or algorithm recommendations).

yeah, sorry for the delay! i'm not sure how representative my response is, because on one hand i'm familiar with waaaay less music than most people on ILM, and there are still a lot of songs that are blindingly obvious to others that are like "new songs" to me. (i have a sharp memory of riding in the car with a girl i had a huuuuuuge crush on in high school, listening to music, and her saying "you don't know who Don Henley is?" and just cracking up). with all that in mind...

the humans won CYCLE ONE, for me. as far as songs and bands i had never heard before, i really liked mick signals rave-ups "better world" and ledge's strawberry switchblade song recommendations. to be honest i struggled with the voices of some of the singers in the human RIYLs - i guess it's an obvious point, but when the playlist is based on pretty guitar-y pop songs with basic structures, the affect of the singer really comes to the forefront, and i can be picky about that. i think that's a hurdle with me and aztec camera, for example - there's just something about frame's voice that irks me.

on the Algorithm side, the church's "under the milky way" came closest to the kind of music i was thinking of - it might have won the cycle had i not heard it so many times before. but not a bad suggestion at all. but in general i found spotify's suggestions to be very hit or miss (in the case of huey lewis and richard marx, very miss). i don't fault the algorithm so much - i fed it pretty generic pop songs that with features that are shared by many, many songs, and there's a very thin line between a singer who can emote authentically and a really corny one, and not everyone agrees on where that line is.

the grand prize winner is the NickB's last minute Prefab Sprout "Bonny" suggestion, which might have a lot of you rolling your eyes because i think it's a really popular song? but for me, that's a song that i sort of recognized from classic radio (maybe?) but i hadn't heard in so long. and definitely not a band or song that comes to mind when i'm in the mood for whatever kind of music that is (sophisto-pop, i guess?)

at any rate, i found several great new songs (and artists/albums) that i'll be listening to more thoroughly in the coming months, so i count this as a great success (for me, at least). i'm curious to see how it will play out with other genres of music, and what happens when the input is more obscure in the first place.

now i'm going to listen to allen's list and see if i have anything useful i can recommend

I don't really know what to do with Allen's list, personally. If you gave me the first 4 songs, I would never come up with Jackson Browne as the 5th. The algorithm I used for the first list basically ignores it, too.

https://open.spotify.com/user/glennpmcdonald/playlist/2taYiw5x1E8eSPazwWGp9W?si=Sla_AhRzQZOLbbAQz-PYfw

ahem, ok, having put this post in the COMPLETELY WRONG thread here it is in the correct place. ish.

purple canteen - brains in my feet
bobby valentin - funky big feet
melvin van peebles - come on feet
chic - my feet keep dancing
duke ellington - hot feet
ronnie whitehead - cold feet
shakti - what need have i for this, what need have i for that, i am dancing at the feet of my lord, all is bliss, all is bliss

Thanks, rusho!

I spotified my list with your additions, which are definitely sending the auto-recommendations in a particular direction: https://open.spotify.com/user/eater9/playlist/2kiV39jt5QUIhgl5ZL5p53?si=sHhyxPZXSyCjXolxoq52xQ

To be specific, Spotify was recommending a lot of popular disco. Then I experimentally removed the Chic track, which seemed to have an outsized influence, and now its recommendations suddenly include Dipset and Obie Trice and Kurupt alongside Loudon Wainwright III and the Monkees.

right, the recommendations aren't going to actually know what those songs have in common like a human would. also, pretty much every recommendation engine is going to recommend you songs with more plays over songs with less plays for obvious reasons. most of them will also pay more attention to the songs with more plays simply because it has more information on chic than it does on the purple canteen. the obie trice recs probably just means that it's keying in on the melvin van peebles instead, which madlib has on one of his beat tapes.

the thing that drives me most nuts about recommendations is to what extent it recommends me stuff _i already know_. if i was five and i had time to tell it all the stuff i already knew it'd be great, but i am forty years older than that and i don't need it to suggest i listen to this amazing new group called "the who". humans of course will do this too, but i like it when people do it, because it gives the suggestion of a certain larger context, which machine-curated aggregated lists simply aren't capable of doing at this point.

so for me, definitely most of my music recommendations are from individual human gatekeepers and only rarely do i find something new simply based on aggregate data.

"This amazing new group called 'The Who'" is, I think, you imposing attitude on something that has none. When I work on algorithms, I'm mainly trying to use listening patterns and math to organize the music space, or to help it organize itself. Different math can do this different ways. An algorithmic list like this one:

https://open.spotify.com/user/particledetector/playlist/0AuwHC7YvKxwnxivnJw7W2?si=CiCnPaoURqasfK88UlzTwg

is not intended to surprise you, it's aspiring to quantified canonicalization. But then the same data, processed differently, can also produce this:

https://open.spotify.com/user/particledetector/playlist/1SevIVvxunwuYZXXPW03lS?si=zpI8RY1iS5WX2RTZONDwtQ

which is full of stuff you probably don't know. I find literally hundreds of new things each week using my industrial-grade internal version of Release Radar. Mixed in, of course, with things I already know, but a skip is way easier than knowing an omitted recommendation is missing...

glenn, now be honest: are you with us here or are you with the cyborgs?

see, for me the second list demonstrates the challenges of generating recommendation data based on edge cases. there might be good stuff on that list, but i'd never know, because there's so much stuff that i can tell (without listening to it, though if I couldn't tell I'd rapidly learn by listening) is bottom-feeding junk that i'm not going to waste my time on it!

the kind of recommendations for music i want is for someone to hear that i like the who's "live at leeds" and, based on that, recommend me something like winterhawk's "there and back again". machine learning, in contrast, is more likely to produce a recommendation for "mad dog" by john entwistle's ox, which, whether i've heard it or not, i don't find to be a useful suggestion.

i don't have any idea how you would even get machine learning to produce a "there and back again" suggestion based on "live at leeds", because i'm not sure that album fits in terribly well to "classic rock" listening patterns. if spotify had my listening data it might gather that i like that winterhawk record, but it would (obviously) have no idea what it actually _sounds_ like, and trying to get an understanding of it based on my listening habits would actively lead it astray - "oh hey rushomancy listened to winterhawk and neneh cherry today".

now of course you can find plenty of new things using your internal version of release radar, but most of us don't have the time or the skill set to educate the software so thoroughly as you about what we personally want to hear!

When putting together a playlist, I often find a few of the obvious-ish algo-recommendations helpful to refresh my aging memory, oh yeah, the Who, love them, great idea. But of course it'd be a way more valuable service to introduce me to music I don't already know but will dig. Even just deeper cuts from classic artists would be welcome.

Semantic theme aside, the tracks recommended by rushomancy the human (which loosely, not exactly, line up with my implicit theme) SOUND way better to me than the ones recommended by the robot.

The robot is helpful when the semantic theme is a simple familiar one, like Rain, where it's probably had abundant trite humans to learn from.

the one thing capable of overcoming !!!THE ALGORITHMS!!! it seems is the narcissism of small differences

(that isn't even really a shitpost, I think it's the root of most discomfort with "the" "algorithms," considering people tend to be fine with them when their existence is not signposted)

good post rush

Can you elaborate on what you're saying, katherine? I think I like it.

the difference between a song someone loves and a song someone despises is often individual, trivial, petty, irrational, and/or dependent upon external context -- all of which are things algorithms are bad at. that difference is also something people assign huge amounts of importance and near-moral weight to. so a lot of "we need to get away from TEH ALGORITHMS," I find, is at root "how dare someone accuse me of liking Miley Cyrus's 'We Can't Stop' because I like Charli XCX's 'Boom Clap'"

(this thread is also sort of weighted in favor of the humans by dint of having a bunch of music obsessives actively trying to beat The Algorithms, but even so)

i don't think it's narcissistic to have idiosyncratic tastes that aren't rationally explicable. i think that's human. a really effective recommendation engine should in theory acknowledge that a lot of what we like is based on context and work to create it.

at which point, we're sort of teaching machines how to control our minds, so i get a lot of the "big bad algorithms" luddism. it's manifestly true that recommendation engines are capable of being leveraged for ideological purposes. the fascists have owned youtube's recommendation engine for years. i'm not some nerd john henry trying to beat "the algorithms" to prove a point - i want them to be better and more transparent!

"the narcissism of small differences" is the name of the phenomenon, I did not invent it

if you want to argue that it isn't narcissistic take it up with freud

katherine, i think your point is predicated on the idea of a listener who exists in this world but isn’t representative of the people posting itt (as far as i can tell).

many times i’ve been in stores, or bars, and asked what music was playing, only to find out like “oh this wilco? weird i thought i hated them. this song is cool tho.” same goes with streaming, whether it’s youtube or pandora or whatever. i don’t feel personally affronted if something comes on that i don’t enjoy; i simply don’t like it and just skip the track. for me it’s not really an ethical issue, and i think most people are fine liking the music they like and acepting that other people share their tastes in some respects but also listen to shit i couldn’t be bothered to listen to.

re: “beat the machines” i mean for me that’s just a joke. i’ll happily bow down to our cyborg overlords if they can start hipping me to shit as good as my friends do, or the fine people of ilm

so yeah, that’s a concept that exists. i’m just not sure that for me at least it’s particularly relevant to this discussion, which in any case i take to be a series of experiments that might yield interesting results on both sides — not some kind of take-down of the idea of the spotify algorithm or whatever

"because there's so much stuff that i can tell (without listening to it, though if I couldn't tell I'd rapidly learn by listening) is bottom-feeding junk that i'm not going to waste my time on it"

The robots, at least, are neither dismissive nor smugly dismissive.

(There are no robots, of course. "humans vs algorithms" is really a question of whether you're willing to try music without the protective shielding of somebody assuring you that listening to it won't make you uncool. So in that sense, yes, I'm on the side of curiosity and human potential, which ironically here we've labeled "algorithms". I very much believe that "not famous yet" doesn't equal "bottom-feeding junk". I find the robots useful not because I've trained them to cater to the narrowing of my tastes, but because I've trained me to not want that.)

(Also, there are no robots.)

To add the maybe-obvious part, I also love recommendations by people. I'm not for algorithms and against people, I'm for people and algorithms, and against "vs".

i think your point is predicated on the idea of a listener who exists in this world but isn’t representative of the people posting itt (as far as i can tell).

possibly -- "fear of being revealed as uncool" is probably closer to what I meant. or rather, "fear of being revealed as basic," since most of the thinkpieces aren't panic that they'll end up hearing 2009 Eurovision semifinalists or obscure basement folk dubstep or 14-year-olds lipsyncing to 15-year-olds singing over bad chiptune covers of Deltarune, but that they'll end up hearing the contents of the next Coachella lineup.

anyway, sorry to further derail; I'd offer recommendations but no one's list so far overlaps with what I could recommend

i'm not saying The Stolen Moans are "bottom-feeding junk", I can't tell one way or another not having heard them...

OK, you know what, I listened to them. They're some weird fur supremacist group. I have no idea what to make of them and based on the 229 Youtube views for their video neither does anyone else. They probably deserve to be somebody's favorite group but they're not mine. The video was definitely more interesting than the song.

Anyway, I'm not talking about that, I'm talking about stuff like "Bohemian Rhapsody (Arranged for Piano, Strings, & Chorus by Rick Wakeman". When the only stuff I can identify on a list is stuff like this, it colors my opinion of the rest of the list.

People say I will listen to goddamn anything and it's not true. I will listen to goddamn anything as long as someone tells me they like them. Putting that extra step in there, a person "telling" a machine they like a song and then that machine telling me about it, doesn't work. That's a prejudice sure but part of harmonious human-machine interaction is acknowledging our irrational prejudices.

Anyway, I'm not talking about that, I'm talking about stuff like "Bohemian Rhapsody (Arranged for Piano, Strings, & Chorus by Rick Wakeman".

if you manage to seed a recommendation engine and get that in return, I'm honestly impressed

so, back to business then? allen, what did you think of your human recommendations?

bump

im on streaming and almost never engage with algorithms but it’s not like im avoiding them either? idk

ah nevermomd didn’t even read what this thread was

Years ago, the first song I entered in Pandora was Pink Floyd "Set the Controls for the Heart of the Sun", hoping they'd follow it with songs of mystery and mood.

The next song Pandora played was Captain & Tenille "Love Will Keep Us Together"

i just looked up the pompeii version of that song on a porn-mode browser

up next is simon and garfunkel doing "the sound of silence"

frankly at this point i'll take daryl dragon over paul simon

that's youtube, btw

Years ago, the first song I entered in Pandora was Pink Floyd "Set the Controls for the Heart of the Sun", hoping they'd follow it with songs of mystery and mood.

But doing so did help show your age.

The spotify playlist for "Set The Controls for the Heart of the Sun" is weird in that it picks songs with vaguely similar aspects, except not the aspects that make Set the Controls actually interesting

ok, in keeping with the theme of the thread, my "set the controls" playlist, off the top of my head:

chico hamilton quintet - blue sands
om - pilgrimage
oneida - people of the north
the slits - earthbeat/wedding song
blues control & laraaji - awakening day

you decide

^ will listen as soon as i get wifi in my house or i can make it to the coffee shop before work

i also asked my floyd nerd friends and one of them recommended "om pax om" from the film "sign of aquarius", maybe that one as well