Can you edit your Spotify Wrapped? AI has ruined playlists

Spotify’s 600 million users are facing one of the streaming service’s most anticipated and feared events: Spotify Wrapped. The Annual User Listening Report provides each Spotify user with a compilation of data about their activity on the platform, recalling users’ top songs, artists, albums and podcasts, with colorful graphics prepared for sharing on social media.

Since its launch in 2016, Spotify Wrapped has seen great success, largely due to our cultural obsession with self-discovery and finding explanations for our behavior. It’s kind of like astrology to our ears. Was The Tortured Poets Department your most listened to album this year? Let’s create that BetterHelp account! Were Addison Rae or Charli XCX your top artists? Let’s leave X and reduce screen time! Were you in the top 0.01% of Beyoncé listeners? What is it like to have impeccable taste? Have you listened to the sounds of rain for hundreds of hours to fall asleep? Maybe it’s time to invest in a white noise machine and a sleep study.

Aside from the normal whiplash of seeing an artist or song in your top 5 that you swore you didn’t like, or the painful realization that your taste in music is at odds with the oeuvre of mystique and niche that you As much as I’ve tried to build, Spotify’s current interface makes me look a little sideways at my Wrapped and wonder how much of my listening habits are of my own volition.

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Is label meddling responsible for Spotify’s repetitive algorithms?

Sabrina Carpenter’s sixth studio album “Short N’ Sweet” was one of the most successful albums of this year and its singles “Espresso”, “Please Please Please” and “Taste” were essential not only on radio and social media but also on streaming services. It seemed like no matter what song I heard, one of these three singles would always come on right after.

I’m not the only one who has experienced this.

Other listeners experienced the same phenomenon with Kendrick Lamar’s No. 1 single “Not Like Us.” In another installment of their summer rap campaign, Drake filed a petition accusing Universal Music Group and Spotify of using underhanded tactics to generate streams and help “Not Like Us” succeed. (Ironic for a man who was featured on the cover of every Spotify playlist throughout 2018.)

There is no evidence that labels are working with Spotify and other streaming services to increase streams for their artists. However, user experiences suggest that this may well be the case. Some have compared it to payola, the illegal practice of paying a radio station to play a song without the station disclosing the payment.

Spotify’s closest-to-payola practice (that we know of) is Discovery Mode, a marketing tool that allows artists and labels to include specific tracks in users’ personalized playlists, Spotify Radio, Autoplay, and Spotify Mixes.

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With so much outside interference in Spotify’s algorithm, I have to wonder if my listening habits are truly my own or if they were forced upon me by some suit in a boardroom or on a Teams call.

AI and algorithms create music echo chambers

In recent years, Spotify (like every other tech company) has unabashedly embraced artificial intelligence.

Early last year, Spotify introduced an AI-powered DJ to make the music listening experience more “interactive.” At first, the DJ would change genres every few songs to add some variety, making little plays between these changes to create a more “human” touch. But as I continued using it, I found that it kept playing the same or similar songs.

In September last year, Spotify launched “Daylists,” which the service described as algorithmically curated playlists that are updated regularly to “collect the niche music and microgenres you typically listen to at certain times of the day or on certain days of the week.”

Daylists are best known for their cheesy, word-salated titles, which are of course AI-generated. At the time of writing, my daily list title is “Mood Music, Calm Storm Monday Night”…whatever that means.

Spotify makes its hyper-personalization, with all of its AI features, a big draw. But often its custom algorithm can create echo chambers that feed and feed back into the same artists, songs, genres and general “vibes.” At what point does hyperpersonalization become incredibly impersonal and distant?

The Spotify homepage is an example of this. Most of the homepage is filled with recently played content. Scroll down and you’ll find algorithmic playlists full of songs the app knows you like, and a few new ones that don’t stray too far from your established listening habits. If you scroll down even further, you’ll find popular song albums and album recommendations based on your current user habits. Scroll even further and you’ll see podcasts and audiobooks, even if you don’t engage with that type of content.

There have been countless times when I have felt the need to hear something new and setting up this homepage has done little to help me. I’d rather Spotify make a mistake and offer an album or artist outside of my comfort zone than continue to fill my feed with recommendations based on user data, AI, and algorithms. These things only lull us into becoming passive listeners.

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