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Music AI

Spotify's Editorial Playlists Are Losing Influence Amid AI Expansion (bloomberg.com) 14

Once a dominant force in music discovery, Spotify's famed playlists like RapCaviar, which significantly influenced mainstream music and artist visibility, are losing ground. As the music industry shifts towards algorithmic suggestions and TikTok emerges as a major music promoter, Spotify's strategy evolves with more automated music discovery and less emphasis on human-curated playlists, signaling a potential end to the era where a few key playlists could make a star overnight. Bloomberg reports: Enter TikTok. In the late 2010s, as the algorithmic controlled, short-form video app emerged as a growing force in music promotion, Spotify took notice. On an earnings call in 2020, Spotify Chief Executive Officer Daniel Ek noted that users were increasingly opting for algorithmic suggestions and that Spotify would be leaning into the trend. "As we're getting better and better at personalization, we're serving better and better content and more and more of our users are choosing that," he said. From there, Spotify began implementing a number of changes that over time significantly altered the fundamental dynamics of how playlists get composed. Among other things, the company had already introduced a standardized pitching form that all artists and managers must use to submit tracks for playlist consideration. One former employee says the tool was created to foster a more merit-based system with a greater emphasis on data -- and less focus on the taste of individual curators. The goal, in part, was to give independent and smaller artists without the resources to personally court key playlist editors a better chance at placements. It was also a way to better protect the public-facing editors who in the early days were sometimes subjected to harassment from people disgruntled over their musical choices.

As the automated submission system took hold, the editors gradually grew more anonymous and less associated with particular playlists. In a handbook for the editorial team, Spotify instructed curators not to claim ownership of any one playlist. At the same time, Spotify began introducing multiple splashy features meant to encourage algorithm-driven listening, including an AI DJ and Daylist, two features that constantly change to fit listeners' habits and interests. (Spotify says "human expertise" guides the AI DJ.) Last year, Spotify laid off members of the teams involved in making playlists as part of its various cuts. And over time, the shift in emphasis has had consequences outside the company as well. These days, the same music industry sources who in the late 2010s learned to obsess over what was included and excluded from key Spotify playlists have started noticing something else -- it no longer seems to matter as much. Employees at different major labels say they've seen streams coming from RapCaviar drop anywhere from 30% to 50%.

The trend towards automated music discovery at Spotify shows no sign of slowing down. One internal presentation titled "Recapturing the Zeitgeist" encourages editorial curators to better utilize data. According to the people who have seen the plan, in addition to putting together a playlist, editorial curators would tag songs to help the algorithm accurately place them on relevant playlists that are automatically personalized for individual subscribers. The company has also shifted some human-curated playlists to personalized versions, including selections with seven-figure followings, like Housewerk and Indie Pop. These days, Spotify is also promoting something called Discovery Mode, wherein labels and artist teams can submit songs for additional algorithm pushes in exchange for a lower royalty rate. These tracks can only surface on personalized listening sessions, a former employee said, meaning Spotify would have a financial incentive to push people to them over editorially curated playlists. (For now, Discovery Mode songs only surface in radio or autoplay listening sessions.)
The shift toward algorithmic distribution isn't necessarily a bad thing, says Dan Smith, US general manager at Armada, an independent dance label. "The way fans discovered new music was radio back in the day, then Spotify editorial playlists, then there were a few years where people only discovered new music through TikTok," Brad said. "All those things still work ... we're all just trying different ways to make sure songs get to the right people."
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Spotify's Editorial Playlists Are Losing Influence Amid AI Expansion

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  • by ffkom ( 3519199 ) on Friday January 05, 2024 @05:59PM (#64135237)
    Firefly [wikipedia.org] did music suggestion perfectly three decades ago. You did not need to "register" or create an account. You just entered a few song titles you like, and based on a big correlation matrix collected from all the users inputs it would suggest other music to you which you probably liked, too. No need for "AI", no need for ad-financed "curators" or such. Like so many good things, Firefly was bought and then shut down by Microsoft. They never could good things just live.
    • by ffkom ( 3519199 )
      Interesting, the descriptions of Firefly I can read now contradict my memory of the service I learned to know under that name back then. I definitely remember not being asked for a "login" or any personal data, but it seems harvesting personal data quickly became a business model.
  • ..is the recommendation robot
    It has never fed me anything I didn't like, and I discovered lots of new stuff I like
    I don't follow pop culture and my musical tastes are niche, but the robot gets it right

  • Considering the songs I listen to and the recommendations which come from YT, I would hope any recommendation from Spotify would still be better. I'm not sure how YT gets me to Taylor Swift from Accept or Carpenter Brut.

    • The normal YouTube recommendation algorithm doesn't seem to be tuned for music at all. Basically it sees "music video" and will recommend you anything else it identifies as "music video" and is popular, without any more granular consideration as to the type of music.

      "YouTube Music" does it much better, at least on par with classic Pandora and last.fm/Audioscrobbler, which worked very well. I've never used Spotify, so I don't know how it compares to those.

      Interestingly, YouTube used to have a human-c

  • ... human-curated playlists ...

    I'm not impressed, I found them to be 1) 5 top-10 songs and 95 bottom-200 songs, or 2) good but including more genres then I wanted. The lack of copy, multi-select and multiple delete made duplicating a playlist, a time-consuming chore.

  • Having been a little frustrated with how mundane Spotify's algorithmic playlists were getting, I loaned my phone to a friend for a few hours over the Xmas period, and invited them to play whatever music they want in Spotify.

    The Spotify playlists have now completely backflipped and are playing virtually no media from my previous echo chamber.

    Whilst the change is refreshing, its clear that Spotify is still stumbling around in the dark where music categorisation and variety is concerned.
    • Recommendation algorithms need to be written to take changing tastes into account and use more active learning. It's not like there's a lack of papers [sci-hub.se] about [smcnus.org] it [inesctec.pt].
  • It always has been trash. I found maybe two bangers in a playlist of 173? Trash. Meanwhile YouTube algorithm giving me raw underground artists like Dee Thuddy. TikTok has banger after banger on some random persons video about eyelashes. Spotify is the new Pandora

  • by SoCalChris ( 573049 ) on Friday January 05, 2024 @07:41PM (#64135407) Journal

    Hey Spotify, before fucking around with AI can you please just make the random function actually be random? My playlist of roughly 2,500 songs is on a repeat of around 100 songs. It's annoying as hell. I don't want the shuffle feature to be smart. It doesn't need AI. Just make it random.

    Once you've got that wrapped up, feel free to add the AI playlist, along with all of the other features taht you've implemented that I'll also ignore. Be a music streaming service. Not a podcast provider, not a tiktok clone.

    • I've been using Soundcloud and it does the same thing. I have hundreds of liked tracks, but "shuffling" them seems to only rotate through a small subset of them.

      Thanks for letting me know the grass isn't greener over there. I was getting frustrated with the bad interface and thinking about switching.

      It's amazing these "premier" streaming services fail at basic tasks foobar2000 did for free, 20+ years ago. Hell, even Winamp did this stuff.

      • I suspect that there's a financial incentive for them to keep playing the same stuff over and over. Like maybe they only pay an artist per person who listens to a track in any given month. So if they play the same track twice, they only have to pay once maybe? So they limit the number of unique songs that they present to a listener? That's the only reason I can think of that this is still like this, and apparently is this way on other services too.

        I'm about ready to just download all this shit via torrent a

    • by chthon ( 580889 )

      I noticed this too, although it currently seems to do a better job than a few months ago.

      But after a while one can not but notice that some numbers are played more than others.

      It seems to help to have a playlist with many numbers (I have some of 1000 and 5000 tracks), and keep listening to them. However, stopping listening, switching over to another one, and then back seems to give popular numbers more priority in the beginning of the list.

      Same with radios, too much popular numbers of the selected genre

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