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This thought was in my mind for a long time, and I decided to pen down my thoughts about how algorithms are destroying art and how it affects emotions and defines what’s “mainstream”
When I was around 6 or 7, I clearly remember we had a Sony music system at home. We owned a large collection of music cassettes, over 200, from various Indian artists like Kishore Kumar, Lata Mangeshkar, Kumar Sanu and many more. We even had a few CDs for playing music in the car. This pretty much shows that my parents were big music lovers, and as a result, music was played quite often in our house.
Back then, there was no Spotify, Apple Music, or Tidal (that was widely used in India). Of course, they did exist (Spotify, for example, was founded in 2006), but what I mean is that there wasn’t really a “recommendation engine” system like today, and back then in India streaming services were not at a thing. We had to buy CDs and cassettes to listen to music, so we would only hear what we actually paid for and what we already knew about.
“This gave a sense of ownership. It makes us feel more serious towards the music. You value something you paid for, much more than what you got for free(not really free though) “
Streaming services like Apple Music, Spotify, SoundCloud, and YouTube Music rely heavily on recommendation algorithms to curate playlists that, according to them, reflect what they believe your taste is. While this personalized approach may seem convenient, it comes with a hidden cost. I believe this hidden cost at times outweighs the benefits we get :)
Oh, you love 'Every Little Thing She Does Is Magic' by The Police? Then surely you must enjoy 'More Than a Feeling' by Boston.
This recommendation system subtly dictates what we are "supposed" to listen to. Our entire listening habits are being shaped by these algorithms, which continually push us towards familiar or algorithmically predictable content. Over time, we end up consuming what the system wants us to hear, not necessarily what we might have discovered on our own. The idea of “creative listening”, exploring music outside of the algorithm’s logic, becomes increasingly irrelevant. This, in turn, reinforces what is mainstream and makes us passive participants, serving the agenda of the streaming services rather than exploring music on our own terms. This makes us more robots, instead of humans.
This might be a bit controversial, but I believe even musicians are facing a significant challenge due to these algorithms. It's almost as if the algorithm now dictates what kind of music gets created. Musicians seem to have less creative freedom when composing. The taste of the masses has been so deeply shaped by the algorithm that mainstream music is starting to feel a bit off.
Now, I know some will argue, "There are still original artists, and people still make good music." And yes, that's true, there is good music out there. But I'm talking about the mainstream scene and the majority of the market. Those who grew up in earlier decades would likely agree that people had a more refined taste in music back then. The algorithm, in my opinion, has led to this shift in behavior and taste, altering the music landscape in ways we wouldn't have expected.
This recommendation system starts defining what is “mainstream”, and people listen to those stuff much more than the “non mainstream” stuff. This reflects in the number of streams. When we used to own physical copies of the music files, we knew what we wanted to listen, and we controlled what we listen. That sense of “owning” the music felt entirely different.
For this reason almost every thing, every genre, every artist, (basically everything) had a listening audience. Now we define good or bad by what the algorithm defines us. Honestly I hate this system.
It’s pretty simple. download your stuff. Use mp3 players, Ipods, don’t use streaming services, download your music and listen it! Do it for a week or so, you will feel the difference! And if you are hardware expert, well you can make one for yourself, maybe using some raspberry pi or anything like that.
