humans vs. algorithms: the RIYL listening exploration cycle

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this may crash and burn quickly, but i want to give it a shot. the concept of this thread is to compare the recommendations of humans vs the recommendations of algorithms. it would be a way to learn about new music and also explore songs that you wouldn't otherwise listen to, in a semi-structured way.

here's how i think it could work (and rules are made to be broken, so if there's another way to do it that would be more fun/rewarding, let's do that):

1) SOMEONE POSTS A LIST OF 3-5 SONGS. these should be songs that they really enjoy. these songs should sort of share something in common or make sense together. good rule of thumb is that they should belong on the same playlist. don't explain what it is you like about them or why they belong together, just the list.

2) HUMANS IN THIS THREAD POST RIYLs (recommended if you like) that they think would fit into that playlist. imagine your niece somehow gets into talking heads and but has never heard of tom tom club or fela kuti.

3) AN ALGORITHM GENERATES RIYLs. I'm sure a number of services can do this, but for me it's Spotify. I just make a new playlist with a few songs, and then it automatically comes up with a list of additional recommended songs.

then some discussion of all the RIYLs, human and computer alike, if anyone's feeling up to it. then someone else goes next.

does this sound dumb? i'll go first.

Karl Malone, Sunday, 25 November 2018 23:56 (three weeks ago) Permalink

i will be a human in the thead who posts RIYLs for your songs

budo jeru, Sunday, 25 November 2018 23:58 (three weeks ago) Permalink

towards th' head of the thRead

budo jeru, Sunday, 25 November 2018 23:59 (three weeks ago) Permalink

humans unite

Karl Malone, Monday, 26 November 2018 00:00 (three weeks ago) Permalink

working on a quick initial playlist. i think the machine-generated part of this will be interesting. based off a few tests, i usually get a few songs that are really good and a few that are like the equivalent of the billy joel listening thread (sorry BJ)

Karl Malone, Monday, 26 November 2018 00:02 (three weeks ago) Permalink

********CYCLE ONE**********

1. Bruce Springsteen - Brilliant Disguise
2. B-52's - Ain't It A Shame
3. Fleetwood Mac - Little Lies
4. Go-Betweens - Love Goes On!

Karl Malone, Monday, 26 November 2018 00:12 (three weeks ago) Permalink

I like the sound of this. I'll try to come up with some suggestions for your list, but I'd also like to do a list and get a sample of recommendations for myself.

emil.y, Monday, 26 November 2018 00:15 (three weeks ago) Permalink

my list is a bunch of pop hits but i'm sure we'll dive into obscuros pretty soon. hopefully that also illustrates how loose the "playlist" can be. to me all those songs make sense together

Karl Malone, Monday, 26 November 2018 00:16 (three weeks ago) Permalink

yeah emil.y! you should go next! i figured i'd wait a day or so to see if anyone has any recommendations based off of those songs, but regardless i'll post the spotify recommendations sometime tomorrow. it may be more interesting for people like me who have huge blind spots in their listening, i guess.

Karl Malone, Monday, 26 November 2018 00:18 (three weeks ago) Permalink

don't explain what it is you like about them or why they belong together, just the list.

also i'm quickly realizing this may be a dumb rule, and i want to immediately renege on it.

i picked these 4 songs because i've been really enjoying late 80s pop recently. i was about 5-6 years old in the late 80's, and i didn't start listening to music until the late 90s. then i got really into music, but kind of skipped all the way back to early 80s and prior. also, when i was starting to get into music, the late 80s were at that point in the cultural cycle where they were uncool. the sound of late 80s production just didn't sit well with me. now, these days, i can appreciate it for what it is. so i'm starting to really get into well crafted pop of the era. the springsteen song in particular strikes me as just like, the perfect song, and i'm not even a big fan of him in general

Karl Malone, Monday, 26 November 2018 00:23 (three weeks ago) Permalink

Not been to RHYL in months, its going to be pretty gloomy this time of year. Word on the street is the SeaQuarium is about to close down too

saer, Monday, 26 November 2018 00:45 (three weeks ago) Permalink

My suggestion for your list was going to be something along the lines of the Wedding Present - I was going with "guitary, some seriousness but also tempered with some fun, some classic rock but also pop and indie sensibilities". But I don't really like the Wedding Present enough to think of a good example off-hand and I can't actually do listening right now.

I think the thing of not explaining why your songs go together means that the humans and the algorithms are more evenly matched - you can't give an algorithm an explanation.

emil.y, Monday, 26 November 2018 01:05 (three weeks ago) Permalink

I get RIYL-ing artists or entire albums, but individual songs is hard (even small groups of songs)... is there enough to “go on”?

my guitar friend wants his money (morrisp), Monday, 26 November 2018 01:32 (three weeks ago) Permalink

i don't know...it could be disastrous

but i do know this: machines can do it reasonably well! we have to fight back!

Karl Malone, Monday, 26 November 2018 01:37 (three weeks ago) Permalink

The "Recommended Songs" thing on Spotify playlists is based on playlist co-occurrence. I also have an internal variant that is based on listening patterns instead of playlist patterns, so here's what THAT one thought for these inputs:

https://open.spotify.com/user/glennpmcdonald/playlist/3X179t4DX6atJImPJWxL7x

glenn mcdonald, Monday, 26 November 2018 04:10 (three weeks ago) Permalink

is that true for "Playlist Radio" as well?

Karl Malone, Monday, 26 November 2018 04:13 (three weeks ago) Permalink

Playlist radio is also based on listening (as opposed to playlist appearances), but for "radio" purposes it tries to pick the most popular artists among the ones that are somewhat collectively similar to the seeds. The generator I used (for the link I posted above) starts from the same data, but is more biased towards the most similar artists over the most popular, and goes for more artist diversity...

(There are lots of algorithms...)

glenn mcdonald, Monday, 26 November 2018 04:24 (three weeks ago) Permalink

Great thread idea.

hopefully that also illustrates how loose the "playlist" can be. to me all those songs make sense together

they seem pretty cohesive, the go-betweens one doesn't have the same 80s pop sheen of the others but they all share a similar emotional colour. Don't know if mine all quite catch that but I've tried to pick some that might be less familiar on your shores:

Aztec Camera - Good Morning Britain
It's Immaterial - Driving Away from Home (Jim's Tune)
The Lotus Eaters - The First Picture of You
Icicle Works - Little Girl Lost
The Colourfield - Thinking of You
Strawberry Switchblade - Since Yesterday

Toss another shrimpl air on the bbqbbq (ledge), Monday, 26 November 2018 10:22 (three weeks ago) Permalink

This will be good.

Allen (etaeoe), Monday, 26 November 2018 12:57 (three weeks ago) Permalink

I made a playlist too:

Class McCombs, “Don’t Vote”
Tim Hecker, “The Piano Drop”
EMA, “California”
Current 93, “The Blood Bells Chime”
Jackson Browne, “These Days”

Allen (etaeoe), Monday, 26 November 2018 13:32 (three weeks ago) Permalink

Glenn, have you (or anyone else) shared the evaluation metric you use (or your evaluation methodology generally)?

Allen (etaeoe), Monday, 26 November 2018 13:32 (three weeks ago) Permalink

For most things at Spotify we start by looking at depth (session lengths for whatever the feature is) and retention (what % of people come back and use the feature repeatedly over time), and how/if use of the thing correlates with overall Spotify usage and retention. For some things you can also look at save/heart/add-to-playlist rates to see if we're getting people's attention. But all of these dynamics can be very different for different features, or even slight variations on how the "same" feature is presented. We also do a lot of qualitative evaluation by looking at lots and lots of examples ourselves. But these are mostly aggregate evaluations, which don't necessarily tell you anything about how well any individual case is going to go...

glenn mcdonald, Monday, 26 November 2018 14:06 (three weeks ago) Permalink

Fun thread idea!

Recommended for Karl:

Translator - Everywhere That I'm Not
The Rave-Ups - Better World
Romeo Void - Just Too Easy
Michael Penn - Walter Reed
Voice of the Beehive - Monsters and Angels

Recommended for Allen:

Jack Hayter - Blind Man's Fog
Ulver - Southern Gothic
Tindersticks - Dying Slowly

mick signals, Monday, 26 November 2018 15:00 (three weeks ago) Permalink

so the only song mentioned in this thread so far i've heard is "little lies". i'm afraid i'm going to have to concede this to the computer.

dub pilates (rushomancy), Monday, 26 November 2018 15:09 (three weeks ago) Permalink

real human RIYL for etaeoe:

f.j. mcmahon "five year kansas blues"
maitreya kali "ice and snow"
widowspeak "my baby's gonna carry on"
demonlover "ate a cicada"
stargate "driving hyperreality"

budo jeru, Monday, 26 November 2018 19:24 (three weeks ago) Permalink

i've only heard two of the so-far 10 human suggestions for karl here. by contrast i've heard about 70% of glenn's spotify playlist. for that reason alone i think the humans are winning, just because discovering new things is so much more fun.

budo jeru, Monday, 26 November 2018 19:34 (three weeks ago) Permalink

thank you very much ledge and mick signals for your recommendations, i'm listening through them now! ledge, you're spot on about the go-betweens not having the same sheen as the others. i kept hesitating on adding it, for that reason, but got impatient and just went with it)

here are the RIYLs from our computer overlords

********CYCLE ONE RESULTS*******

Input:

Bruce Springsteen - Brilliant Disguise
B-52's - Ain't It A Shame
Fleetwood Mac - Little Lies
Go-Betweens - Love Goes On!

Algorithmic Output (via Spotify's "Recommended Songs based on the songs in this playlist")

The Church - Under the Milky Way
Prince - U Got the Look
Heart - Who Will You Run To
Cyndi Lauper - Change of Heart
Huey Lewis & the News - Jacob's Ladder
Richard Marx - Don't Mean Nothing
Crowded House - Don't Dream It's Over
Madonna - Who's That Girl
Sea Urchins - Pristine Christine
Pretenders - Don't Get Me Wrong

Karl Malone, Monday, 26 November 2018 19:36 (three weeks ago) Permalink

Eager for emil.y's list; meanwhile, the machines are giving me real bad suggestions for how to continue this:

Jimmy Webb - Feet in the Sunshine
Beach Boys - Take a Load Off Your Feet
Parliament - Agony of Defeet
Joanna Wang - Feet
Blind Richard Yates - Sore Bunion Blues

mick signals, Monday, 26 November 2018 19:58 (three weeks ago) Permalink

can i make the humble suggestion that we hold off on adding new playslists until we can get a good amount of human feedback for the ones already posted, and have a chance to compare those RIYLs to the computer suggestions, and discuss etc?

like MS if you're cycle number 3, emil.y can be 4, i'll take ticket number 5 but i'll hold off until we can sort of process y'know idk i mean this is karl's thread his call i guess

budo jeru, Monday, 26 November 2018 20:03 (three weeks ago) Permalink

i do think it'd be good to hold off a bit and take turns to the extent that we can, but ultimately i'm cool with however people want to go about it.

Karl Malone, Monday, 26 November 2018 20:05 (three weeks ago) Permalink

Emil.y called her slot before me! I think it's possible that more lists will yield more contributions, by giving would-be contributors like rushomancy more potentially familiar starting points, but also happy to wait.

mick signals, Monday, 26 November 2018 20:12 (three weeks ago) Permalink

yeah, i think you could be right about that, too! maybe we can just play it by ear (no pun intended), try to take turns for a while and see how it goes, and if it's too much of a hassle or it doesn't really generate much good discussion anyway, then start letting the playlists fly at wll

i mean honestly i'm in rushomancy's boat, too - i am not a walking encyclopedia wikipedia of music so a lot of this is new to me too. a lot of the suggestions i got (both human and spotify) are from artists i know of but am not really that familiar with. like, i've heard romeo void before but when i try to pin down what they sound like in my head, i can't really think of it. so it'll be fun to revisit them. richard marx, though...my understanding was that he was a synonym for "really bad MOR music", but that could just be residue from the stuff i mentioned upthread about that time of the 80s having a bad reputation, musically, when i was growing up.

Karl Malone, Monday, 26 November 2018 20:18 (three weeks ago) Permalink

Shall list originators provide a spotify link so everyone can start out hearing the seed songs at least?

mick signals, Monday, 26 November 2018 20:25 (three weeks ago) Permalink

sure, i can do that! should i also append the spotify recommendations to the end?

Karl Malone, Monday, 26 November 2018 20:27 (three weeks ago) Permalink

The really bad MOR recommendations? I would say no, not until the humans have been completely trounced and subjugated.

mick signals, Monday, 26 November 2018 20:29 (three weeks ago) Permalink

hooray! haha

ok, here's my playlist: https://open.spotify.com/user/weinventyou/playlist/5YECUJC0WWfj5b71h7UYSg?si=qDHhinuqRPOuLzeGI9TXhQ

i made it collaborative, so if people want to add their own recommendations directly on the playlist, go for it! i went ahead and added the suggestions from ledge and mick signals

Karl Malone, Monday, 26 November 2018 20:32 (three weeks ago) Permalink

"things like this THAT I DON'T ALREADY KNOW" is a different task than "things like this"...

glenn mcdonald, Monday, 26 November 2018 20:33 (three weeks ago) Permalink

True; since neither Team Human nor Team Computer was trying for the former task, it's slightly interesting to notice that the crunching of aggregate listening data produces a more familiar suggestions list than the amateur biological brain does.

mick signals, Monday, 26 November 2018 20:46 (three weeks ago) Permalink

sure but isn't the whole point of RIYL to hip you to things you haven't heard already?

budo jeru, Monday, 26 November 2018 20:53 (three weeks ago) Permalink

That's one potential mode, but hardly the only one. Karl's setup didn't precisely define the task, but he did say "imagine your niece somehow gets into talking heads and but has never heard of tom tom club or fela kuti", which more suggests the mode in which there are notionally "correct" answers and we're seeing which method comes closer to finding them...

glenn mcdonald, Monday, 26 November 2018 21:25 (three weeks ago) Permalink

the crunching of aggregate listening data produces a more familiar suggestions list than the amateur biological brain does.

obviously i don't know what karl has or hasn't heard but i was aiming for songs slightly off the beaten track. spotify's & glenn's playlists might be a better match but 'manic monday' or 'don't get me wrong' seem too familiar to be useful.

Toss another shrimpl air on the bbqbbq (ledge), Monday, 26 November 2018 21:27 (three weeks ago) Permalink

yeah exactly

budo jeru, Monday, 26 November 2018 22:03 (three weeks ago) Permalink

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.

emil.y, Tuesday, 27 November 2018 15:34 (three weeks ago) Permalink

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

rob, Tuesday, 27 November 2018 16:23 (three weeks ago) Permalink

hey karl, you definitely need this in your playlist:

Prefab Sprout - Bonny

my name is leee john, for we are many (NickB), Tuesday, 27 November 2018 17:04 (three weeks ago) Permalink

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

my name is leee john, for we are many (NickB), Tuesday, 27 November 2018 17:08 (three weeks ago) Permalink

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

my name is leee john, for we are many (NickB), Tuesday, 27 November 2018 17:09 (three weeks ago) Permalink

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

Prefab Sprout - Appetite

my name is leee john, for we are many (NickB), Tuesday, 27 November 2018 17:18 (three weeks ago) Permalink

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

Toss another shrimpl air on the bbqbbq (ledge), Tuesday, 27 November 2018 17:22 (three weeks ago) Permalink

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

my name is leee john, for we are many (NickB), Tuesday, 27 November 2018 17:28 (three weeks ago) Permalink

Recommended for Karl:
Suzanne Vega - Solitude Standing

MarkoP, Tuesday, 27 November 2018 17:52 (three weeks ago) Permalink

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.

Karl Malone, Tuesday, 27 November 2018 18:20 (three weeks ago) Permalink

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

Karl Malone, Tuesday, 27 November 2018 18:29 (three weeks ago) Permalink

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

glenn mcdonald, Tuesday, 27 November 2018 18:55 (three weeks ago) Permalink

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

dub pilates (rushomancy), Wednesday, 28 November 2018 01:01 (two weeks ago) Permalink

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

mick signals, Wednesday, 28 November 2018 15:32 (two weeks ago) Permalink

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.

mick signals, Wednesday, 28 November 2018 19:36 (two weeks ago) Permalink

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.

dub pilates (rushomancy), Thursday, 29 November 2018 03:08 (two weeks ago) Permalink

"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 mcdonald, Thursday, 29 November 2018 04:31 (two weeks ago) Permalink

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

budo jeru, Thursday, 29 November 2018 04:40 (two weeks ago) Permalink

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!

dub pilates (rushomancy), Thursday, 29 November 2018 10:37 (two weeks ago) Permalink

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.

mick signals, Thursday, 29 November 2018 14:27 (two weeks ago) Permalink

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.

mick signals, Thursday, 29 November 2018 15:02 (two weeks ago) Permalink

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)

aloha darkness my old friend (katherine), Thursday, 29 November 2018 19:17 (two weeks ago) Permalink

good post rush

budo jeru, Thursday, 29 November 2018 19:23 (two weeks ago) Permalink

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

mick signals, Thursday, 29 November 2018 19:35 (two weeks ago) Permalink

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)

aloha darkness my old friend (katherine), Thursday, 29 November 2018 20:22 (two weeks ago) Permalink

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!

dub pilates (rushomancy), Thursday, 29 November 2018 20:51 (two weeks ago) Permalink

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

aloha darkness my old friend (katherine), Thursday, 29 November 2018 21:04 (two weeks ago) Permalink

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

aloha darkness my old friend (katherine), Thursday, 29 November 2018 21:05 (two weeks ago) Permalink

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

budo jeru, Friday, 30 November 2018 01:30 (two weeks ago) Permalink

"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.)

glenn mcdonald, Friday, 30 November 2018 02:07 (two weeks ago) Permalink

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".

glenn mcdonald, Friday, 30 November 2018 12:13 (two weeks ago) Permalink

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

aloha darkness my old friend (katherine), Friday, 30 November 2018 14:48 (two weeks ago) Permalink

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.

dub pilates (rushomancy), Friday, 30 November 2018 14:55 (two weeks ago) Permalink

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

aloha darkness my old friend (katherine), Friday, 30 November 2018 15:01 (two weeks ago) Permalink

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

budo jeru, Sunday, 2 December 2018 20:01 (two weeks ago) Permalink


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