3 people listening to music on their phone

Chained to the AlgoRhythm: How Spotify Standardizes Our Listening

read time - icon

0 min read

Apr 19, 2024

Does Spotify always play you the same songs? Or, even worse, does Spotify always play you the same songs as your friends?

This happened to me just the other day while working with a friend who had “claimed aux.” I was in the zone, bobbing my head to the beat… until I realized I had heard all of these songs before — in fact, earlier that morning. I couldn’t help but ask, “Hey, what playlist is this?”

He looked up from his laptop, “Oh, it’s my Daily Mix! Pretty good, right?”

Throughout my decade as a devoted Spotify user, I have witnessed the rise of personalized playlists designed to match your “unique” taste in music… but tend to sound pretty generic. Despite my constant complaints, I listen to a lot of these, and I know I’m not the only one.

… so why are we stuck in these listening loops?

First things first: how does Spotify's algorithm even work?

Let’s start with a few disclaimers. First, I am not an algorithm specialist. Second, no one really is when it comes to Spotify (who is committed to keeping things secret).1 This is what we call a black box: a system whose inputs and operations are intentionally kept invisible to the user.2 We are left guessing how the outputs — or, in this case, the recommended music — got there in the first place.

But from my intensive scouring of the internet, all evidence points to a feedback loop. This all begins with Spotify tracking your user habits — like the songs you save or skip, the genres you gravitate to, or that embarrassing album you binge-listened to all last week (you know the one).3 Using this data, Spotify then sorts you into taste clusters or groups of people who find similar artists and tracks appealing and bases your predictions on them.1 Turns out, personalization isn’t so personal after all!

The “loop” truly circles around when you constantly consume these recommendations, only providing the system with “proof” that you genuinely enjoy that music.1 In other words, Spotify is learning your taste so well that it reinforces (or maybe even determines) it.3

What’s so wrong with that? Spotify’s feedback loop traps you inside of a filter bubble, a fancy word for when an algorithm meant to personalize your experience does too good of a job, causing you only to encounter information that confirms your prior beliefs. Think of this as Spotify forming a literal echo chamber, with your music preferences endlessly bouncing back at you. There are three main problems here:

1. The user usually isn’t aware that they’re trapped inside of a filter bubble.4 And why would you ever pop the bubble if you don’t know you’re in it?

2. Filter bubbles solidify the exposure of mainstream musicians, abandoning smaller artists (whom, unfortunately, Spotify already drastically underpays anyway).5

3. The system promotes the system — that is, hits from dominant cultures, effectively endangering minority cultures who speak minority languages.6

Across these issues underlies the ultimate irony: a platform with the potential of expanding our listening tastes to new genres, underground artists, and unrepresented cultures is confining us to the depths of our minds. A platform with the potential to promote exploration and equality in the musical realm is just reinforcing the same barriers as before. A platform that could make us grow and connect as humans is making us dependent on machines.

Behavioral Science, Democratized

We make 35,000 decisions each day, often in environments that aren’t conducive to making sound choices. 

At TDL, we work with organizations in the public and private sectors—from new startups, to governments, to established players like the Gates Foundation—to debias decision-making and create better outcomes for everyone.

More about our services

Why aren’t we popping these filter bubbles?

Now we understand how Spotify’s feedback loop traps us in filter bubbles from an algorithmic perspective… but how about from a cognitive one? In other words, why do our brains like them so much? Let’s walk through the five biases that might come into play starting from when we open the app…

1. Choice Overload: Opening the app

Earbuds in. Phone out. Spotify open… but what on earth should I listen to?

For the first time in history, we are blessed with a seemingly endless selection of songs at our fingertips (or rather, our eardrums). But this becomes more of a burden than a blessing when choosing which one to listen to.

This is where choice overload comes into play. The more music available, the more we become paralyzed by our options. Cognitively speaking, it’s much easier to forfeit our choice to some algorithm, rather than going through the effort to pick out the tunes ourselves. Why should I bother with the search bar when I can just scroll through my home page and see what Spotify recommends instead…

2. Proximity: Choosing your format

To album or to playlist, that is the question.

Proximity is the Gestalt principle explaining how we categorize items lacking a clear border. In this case, the “items” we’re talking about are songs, which can be arranged and rearranged into whatever type of grouping we like.

Up until this point, songs have predominantly been categorized into albums. Of course, a lot of this was for purchasing purposes — whether this meant buying a vinyl record in the 40s, a cassette tape in the 60s, a CD in the 80s, or a file on your MP3 player in the 90s.7 Even in the early iTunes days, it was much more cost-effective to purchase entire albums rather than separate tracks.8

Of course, across all of these formats, playlists still existed (they called them “mixtapes” for a reason!) but were much less popular because they were much less convenient.9 But now with streaming services like Spotify, where we pay an upfront cost for music access, we no longer have to rely on albums. And why would we, when Spotify has so many enticing playlists to choose from… 

3. The Barnum Effect: Picking your playlist

Is my vibe more “solipsynthm” or “lowercase”?

Let’s face it: we all like feeling special. And Spotify knows exactly how to make us feel special by playing into the Barnum effect. This is when we believe that generic information that could apply to anyone applies specifically to ourselves. Although the songs in our “personalized playlists” are far from personal, Spotify uses the act of naming to create the illusion of tailored listening personas, making us feel unique, and thus, more likely to listen.

Take, for example, Spotify Wrapped, the insanely popular, dolled-up summary of your listening from the previous year. By using a variety of tactics — ranging from niche genre titles (think “electrofox” or “fallen angel” 11) to user personas (last year I was a “vampire”12) — Spotify turns our listening from ordinary to extraordinary. 

A new breakthrough invention is Spotify’s daylist, which provides you with a “snapshot” of your typical preferences at a specific point during the day. Spotify itself describes these as being “hyper-personalized.”13 And how could they not be, given how over-the-top their titles are? Who else in the world could be listening to “scary dog monday morning” at the same time as you?

Source: My cousin Alex, who kindly offered this up close and personal look into her subliminal psychology.

4. The Mere Exposure Effect: Listening to tunes

I’ve heard this song before! And this one… and this one…

Now that you’ve selected whatever playlist has the most obscure title catered to you, it’s finally time to listen to some music! But despite the title being one-of-a-kind, the songs are… not so much. Most of these, you’ve heard many times before, and everyone you know probably has too (one of my friends even calls these “algorithm songs”).

Of course, a big part of this has to do with the feedback loops and filter bubbles we talked about before. Another factor is that Spotify’s algorithm favoring singles,14 which means you are much more likely to encounter an artist’s latest hit rather than some niche track from the extended version of their self-titled album. (What a bummer, right?)

But what’s cognitively key here is the mere exposure effect: we tend to like things the more we’ve encountered them. Spotify knows this well — which is why it’ll play you a song you’ve heard 20 times before, rather than just twice. Now, multiply this by the dozens of tracks you’ll find on a playlist, and you’ll understand why there are only a few new ones in the mix.

5. Continuity: Stuck in the stream

Just keep streaming, just keep streaming…

Finally, you’ve reached the end of the playlist. It’s over, right? Of course not. The music never ends, as Spotify will keep playing recommended songs until you exit the app.

This never-ending stream of sound plays into another Gestalt principle called continuity, which describes how our eyes try to follow a smooth path when looking at something. We can apply this concept to listening as well — with our ears attaching themselves to a stream of songs.

Spotify’s founder Daniel Ek once said, “We believe that music should be like water. It should just exist everywhere.”15 The problem here (besides the fact that water is not accessible everywhere) is that music isn’t meant to play forever.  This simile comparing streaming songs to streaming water promotes the unintentional overconsumption of music — and thus, of the immense amounts of energy the databases for these platforms require.16

This begs the question: how do we stop the endless stream of sound? And how do we make our own?

Follow your own (algo)rhythm

Let’s get one thing straight: the point of this article is not to completely write off Spotify. I think it’s an amazing tool with crazy potential — that is if we learn to use it right.

Most of the articles I read offered advice on how to “trick your algorithm” into giving you better recommendations. The options here are endless — from ignoring the like button to playing your playlists in reverse order to even starting from scratch with a brand new account.17,3 Although you can give these strategies a try, the unfortunate truth is that they won’t get you very far.

One of my favorite case studies I stumbled into was a Medium writer named Jordy who listened to 15 minutes of “something new” every day for an entire year.18 Although Jordy discovered that “waking up [with] a different artist every day feels great,” he didn’t actually find that many changes to his algorithm. And if that’s the case from a year’s worth of effort, then the rest of us are simply screwed.

Plus, merely “fixing” your algorithm would be missing the entire point. The bigger problem here is that of intentionality — making decisions for yourself, and, more importantly, by yourself. Music is a huge part of how we identify ourselves. This should be based on the textures, the timbers, the lyrics of songs, and not so much on whether we’re feeling “scary dog monday” — which, although entertaining, doesn’t really mean anything. As our friend Jordy says, “the search bar and your own efforts are still your best allies,” meaning it’s time to get creative with our searches.

But this doesn’t have to be a lonely endeavor. Spotify is awesome because it not only connects us to millions of artists, but millions of other listeners. We should take advantage of this by seeking out other users’ playlists to make listening an active process, rather than the passive one it’s become. To restore music’s status as a communal activity, rather than an isolating algorithm. Plus, I’m sure you’ll actually come across some new stuff you like along the way.

So, what do you say? Are you ready to pop the bubble and swim upstream?


  1. Turk, V. (2021, January 18). How to Bust Your Spotify Feedback Loop and Find New Music. Wired. https://www.wired.com/story/spotify-feedback-loop-find-new-music/?bxid=5be9e3cb3f92a40469fa5dd0&cndid=48651749&esrc=AUTO_PRINT&hasha=57e1de08311c5ccb83304408b2ad36bb&hashb=179243c5f24a2d9196eb57c29675cecbf0526b18&hashc=80208e51041fb06b4b4023ce53b3108f40a544b8fb433dbe480ef00c854cf79a&source=EDT_WIR_NEWSLETTER_0_DAILY_ZZ&utm_brand=wired&utm_campaign=aud-dev&utm_mailing=WIR_Daily_011821&utm_medium=email&utm_source=nl&utm_term=list1_p4 
  2. Yasar, K., & Wigmore, I. (2023, March 17). What is black box ai? definition from TechTarget. WhatIs. https://www.techtarget.com/whatis/definition/black-box-AI 
  3. Tolcheva, S. (2022, May 4). How to Break Out of the Spotify Feedback Loop by Finding New Music. MUO. https://www.makeuseof.com/break-out-of-spotify-feedback-loop-with-new-music/ 
  4. Ryu Won Kang and Adam Lam, J., & Kumar, T. (2022, August 14). How you may be trapped in a filter bubble of music due to AI. The Strand. https://thestrand.ca/how-you-may-be-trapped-in-a-filter-bubble-of-music-due-to-ai/ 
  5. Ovide, S. (2021, March 22). Streaming Saved Music. Artists Hate It. The New York Times. https://www.nytimes.com/2021/03/22/technology/streaming-music-economics.html 
  6. Government of Canada. (2019, May 29). Report — International Meeting on Diversity of Content in the Digital Age. Canada.ca. https://www.canada.ca/en/canadian-heritage/services/diversity-content-digital-age/international-engagement-strategy/report.html 
  7. Kendall, J. (2024, February 22). From Discs to Digital: The Odd History of Music Formats. LANDR Blog. https://blog.landr.com/music-formats-history/ 
  8. Harris, M. (2020, February 4). Save Money in iTunes With the “Complete My Album” Option. Lifewire. https://www.lifewire.com/save-money-in-itunes-with-complete-my-album-option-2438722 
  9. Radauskas, G. (2022, October 25). The Playlist: An origin story like no other that charts the rise of Spotify. Cybernews. https://cybernews.com/news/review-the-playlist-spotify-series 
  10. Spotify Advertising Team. (2020, July). Five years of discovery and engagement through Discover Weekly. Spotify Advertising. https://ads.spotify.com/en-US/news-and-insights/five-years-of-discovery-and-engagement-through-discover-weekly/  
  11. Van Buskirk, E. (2015, October 2). 50 Genres With The Strangest Names On Spotify. Hypebot. https://www.hypebot.com/hypebot/2015/10/spotify-identifies-50-genres-with-the-strangest-names.html 
  12. Hoover, A. (2023, November 29). Spotify Wrapped is Back Again. Are You a Vampire or a Shape Shifter?. Wired. https://www.wired.com/story/spotify-wrapped-never-going-away/ 
  13. Spotify. (2023, September 12). Get Fresh Music Sunup to Sundown With daylist, Your Ever-Changing Spotify Playlist. Spotify. https://newsroom.spotify.com/2023-09-12/ever-changing-playlist-daylist-music-for-all-day/ 
  14. Tobias. (2023, September 11). Why its better to release singles than albums on Spotify. Playlist-Promotion. https://playlist-promotion.com/why-its-better-to-release-singles-than-albums-on-spotify/#:~:text=Spotify%27s%20algorithm%20tends%20to%20favor,%2C%20and%20ultimately%2C%20more%20revenue 
  15. Busari, S. (2011, December 8). Spotify founder: I’m not music industry’s savior. CNN. https://www.cnn.com/2011/12/08/tech/web/spotify-daniel-ek/index.html 
  16. Blistein, J. (2019, May 24). Is Streaming Music Dangerous to the Environment? One Researcher Is Sounding the Alarm. Rolling Stone. https://www.rollingstone.com/music/music-features/environmental-impact-streaming-music-835220/ 
  17. Collins, B. (2022, October 12). How To Stop Spotify Feeding You The Same Old Songs. Forbes. https://www.forbes.com/sites/barrycollins/2020/06/11/how-to-stop-spotify-feeding-you-the-same-old-songs/?sh=129158aa44c5 
  18. Q., J. (2021, July 1). Does Listening To Something New Everyday Affect Your Spotify Feedback Loop?. Medium. https://medium.com/the-riff/how-does-listening-to-something-new-everyday-affect-your-spotify-feedback-loop-9aeff86cce89 

About the Author

Gabrielle headshot

Gabrielle Wasco

Gabrielle Wasco is a Junior Content Editor at The Decision Lab. She recently graduated from McGill University with a Bachelor of Arts in Psychology and English literature, sparking her love for scientific writing. Her undergraduate research involved analyzing facial and body movements to help identify the smallest unit of nonverbal communication. As she begins her internship with The Decision Lab as a content writer, Gabrielle is excited to widen the accessibility and impact of behavioral science through effective communications. She looks forward to learning more about how seemingly minute decisions shape our lives. In her free time, you may find her cross country skiing on Mont Royal or playing music in the park.

Read Next

blue photo of romans

Taking a Hard Look at Democracy

Tom Spiegler, Co-Founder and Managing Director at The Decision Lab, joins Nathan Collett to talk about what behavioral science can tell us about the 2020 US election and the state of democracy more generally.


A New SPIN on Misinformation

We all stretch the truth from time to time. The real problem is when our lies spread to thousands of people, assisted by recent technological advancements such as social media or artificial intelligence. This has a real impact on the decisions people make—such as who to vote for or whether to get vaccinated.

Notes illustration

Eager to learn about how behavioral science can help your organization?