“Spotify playlists, and Spotify charts, and Spotify plays, have become the number one tool that labels and artists and managers are using in order to break artists and measure success,” said industry analyst Mark Mulligan, speaking to Wired earlier this year. “If you get things working on Spotify, that’s going to crank the wheel.” Anyone who’s opened Spotify and found themselves clicking on their Daily Mix playlist, or fired up the app’s Discovery Weekly playlist already knows this. The app, and the impact of its playlist placements, are now an almost unspoken reality of the industry’s digital growth.
And so we come to this week’s news, of Spotify playing coy about what determines the song of the summer. In a blogpost published on Wednesday, the streaming service’s US team announced a – you guessed it – playlist of the tracks that they “predict” will soundtrack your BBQs, house parties and whatever other photogenic events you’ll be attending in the sunshine. “To create this year’s Songs of Summer predictions,” they wrote, “Spotify tapped the insights of its genre and trend experts, analysed its streaming data and considered factors such as a song’s performance on the charts, on key Spotify playlists and how it’s performing over time. The team also factored in buzz on social media to create a list of songs perfect for essential summer moments.”
At a glance you’d look at this and think, ‘oh cool, Spotify are predicting the future. That’s fun! They’re fun!’ But when you take a closer look, a couple of issues become clear. First, that you walk right into a chicken-and-egg situation. Do songs chart well because it’s been playlisted dominantly, and thus listened to by lots of people on Spotify? Or does it make that Spotify playlist position because it’s performing well on the charts? We don’t know about those inner workings within Spotify. But it’s bizarre for the company to both aggressively use reams of data to thrust certain songs under our noses, then act as though it doesn’t consequently set the agenda for what casual music listeners grow to like.
Amid some big changes in the music industry, new RCA Records CEO Peter Edge and longtime colleague Tom Corson, who was promoted to president and COO in August, have officially shuttered historic labels Arista and Jive. J Records, launched by Clive Davis in 2000 as an “instant major,” will also see its artists bequeathed to RCA.
In the digital age, one might think these closures mean there is little value, awareness or loyalty to a label by name, but the execs insist it’s quite the opposite. “The concept is that there is value in branding RCA and not having it confused or diluted by other labels,” says Corson.
That’s an odd quote in answer to a statement about label identities not having value, as, of course, there is no real identity to the RCA ‘brand.’ The writer’s statement is perceptive, and brings up a good point. Labels seem to matter less and less as we rely on proprietary software for streaming music. Apple Music and Spotify only mention the label of origin on a release’s ‘page’ as a required copyright line in fine print at the bottom. One certainly can’t search for a favorite label and listen to a streaming ‘playlist’ of its new offerings, unless it is a pre-packaged playlist that someone put together to focus on that label. Spotify at least lets labels have profiles, which come up if you search for the label name. But these don’t offer much information beyond label curated playlists … not even a list of the latest releases.
I’ve written a bit about the problems with curation on streaming services, and removing label identity could be seen as a part of that issue. The labels that inspired me when I was young (Factory Records, SST, 4AD, and so on) had attraction as a type of curator, in that I knew what I was getting into – for the most part – if, for example, I listened to a 4AD release in the ’80s. There are certainly some great indie imprints active now that benefit from a closely moderated identity, sonic and otherwise. Or, at least, they could benefit, if the streaming services would give labels some credit.
But the quoted article above may reveal the problem. The major labels, being the ones that shout the loudest at the streamers, don’t need or care to foster this sonic identity. One could say Jive had a sound … there are a group of classic dance records that come to mind when I think of the label, and it could be argued they were identified by a certain pop style in recent decades. But that’s hardly important in the age of streaming, so it’s fine to make things less complicated and throw it all under the RCA blanket. And that makes sense for them … label identity, and having streaming services highlight labels and their intrinsic sounds, can only benefit the independents.
Just as computers cannot yet create powerful and imaginative art or prose, they cannot truly appreciate music. And arranging a poignant or compelling music playlist takes a type of insight they don’t have—the ability to find similarities in musical elements and to get the emotional resonance and cultural context of songs. For all the progress being made in artificial intelligence, machines are still hopelessly unimaginative and predictable. This is why Apple has hired hundreds of people to serve as DJs and playlist makers, in addition to the algorithmic recommendations it still offers.
More recently, algorithms have begun producing playlists that can feel a lot more nuanced and tailor-made. The world’s biggest streaming service, Spotify, which has more than 75 million users, is pushing the state of the art, using vast amounts of data to make personalized recommendations.
Spotify’s deep-learning system still has to be trained using millions of example songs, and it would be perplexed by a bold new style of music. What’s more, such algorithms cannot arrange songs in a creative way. Nor can they distinguish between a truly original piece and yet another me-too imitation of a popular sound. (Spotify’s Chris) Johnson acknowledges this limitation, and he says human expertise will remain a key part of Spotify’s algorithms for the foreseeable future.
Though some consider human curation to be elitist, I feel music fans and listeners welcome and crave it. Who doesn’t enjoy a trusted source giving suggestions of cool new music to discover? It’s been the secret of success for certain radio shows, record store clerks, magazine music reviewers, and music blogs. The whole mixtape phenomenon is built on it. My SoundCloud stream is built on it. Basically, if you’re into discovery, you’re into the trusted recommendation … or, in modern industry-speak, “curation”.
Despite my love of human recommendations, I am genuinely curious about Spotify’s algorithmic ‘Discovery’ playlist and want to dig more into it. (There are some technical issues I have with Spotify’s OS X app that keep me from using it more which I won’t go into here.) The team at Spotify seem very confident in what the technology is able to do, and anything that encourages listeners to check out new music is all right by me. But I can’t help but wonder if a human / tastemaker guided algorithm – a mixture of computer recommendation and ‘music fan’ supervision – might be the way to go. From this article, it sounds like this is where we are headed.
An area that I find frustratingly overlooked is the realm of the Pandora-like ‘sounds like’ radio stations. These don’t work for me, not on any of the services, and this ‘radio’ would be my most accessed feature if they did. Pandora drove me crazy because (as an example) I’d program a Joy Division station, and then would hear “Love Will Tear Us Apart” every single time I chose it, but didn’t necessarily want to give it a ‘thumbs down’ and banish the song from its repertoire. I might want to hear it now and then … but not every single time. Of course, I’m not picking solely on Pandora here as none of the services get this radio feature right. If I create a ‘station’ based off Brian Eno’s “Lizard Point” – a beatless, droning composition opening his album Ambient 4: On Land – I’m sure all the services will give me large doses of ’70s art rock instead of the ambient music I’m looking for.
Apple Radio – the one pre-dating Apple Music – tried to address this to a degree with a slider allowing the user to choose if he/she wanted to hear more of the ‘hits’ or, with the slider all the way to the right, to choose an adventurous discovery-oriented path. It wasn’t perfect, but the concept was solid and I would have loved for Apple to fine tune it rather than ditching it altogether in Apple Music at present. Regardless, we’re a long way from computers getting it right (and potentially achieving music snob A.I.) but it’s a fascinating study to see the aims and attempts to move us closer. And, once again, all this effort going into helping listeners find new independent artists is a terrific thing.