The algorithm will destroy us. No one actually knows what it is, but we all sort of somewhat just about understand what it does. It sits right next to us at all times, carefully monitoring our every movement, and then using all that data to tell us what we should do next. And it’s everywhere.
I have friends who carefully manage their Netflix or Amazon Prime viewing history to make sure the algorithm doesn’t get confused. That way, they’re not shown recommendations they wouldn’t be interested in. I, too, get annoyed when my family accidentally logs into my Netflix account, and I then have to deal with suggestions for soppy Bollywood films or boring war documentaries for a week (imagine the travesty!).
And it gets murkier in the world of music. Last year, I became aware of a worrying trend. There’s this simmering impression that artistes and bands are trying to sound more and more like other popular artists. This isn’t anything new — the hold that good music can have over its listeners is hypnotic, and it can envelope and inspire you in many different ways. A lot of musicians end up sounding like cheap pastiches of the heroes they grew up admiring, accidentally or by design. It’s not great, but it happens.
Gaming the system
But the thing I’m talking about here is a little more devious and calculating. It’s a way of gaming the system. The artist writes something that sounds like whatever’s trending on the charts, and in this way, the music-streaming algorithms will slot it into the ‘similar artists’ category or ‘recommended listening’. And presto! They make lots (ish) of money and get lots of fans. So, if you, the listener, are spinning a lot of Carly Rae Jepsen — whose music, I’m not embarrassed to admit, I’m quite enjoying these days, both ironically and sincerely — on your streaming app, then the chances of the app suggesting songs similar to, say, ‘Call Me Maybe’, are higher. Artistes could thus end up writing songs like the aforementioned inimitable classic, merely as a way to reach a bigger demographic of listeners.
Algorithms are an essential part of modern-day consumption of digital art. They assist — sometimes enhance — the process of discovery without the active intrusion of an authoritative human voice guiding you. The computer doesn’t judge; it just throws stuff at you that it thinks you may like, based on what you already like.
But at what point do we cede control entirely, thus limiting our own exposure to new works? There was actually a low point in my life where I was searching for videos in my browser’s incognito mode so it wouldn’t fudge up my suggestions page on YouTube. It’s started happening on social media too; whenever I read an article about A Thing on my Twitter, and I reopen the app, my timeline is swarming with similar articles about that same A Thing.
Big bad machine
Clearly then, unwittingly and without even realising, I’ve become a slave to the algorithm. A small, insignificant cog in a big bad machine that will swallow me whole. But I don’t want to be. I want to reverse this development.
There are reasons of principle involved, no doubt. I don’t want to limit my horizons and feed a system that thrives on homogeneity. I want to learn things about me, and not be taught them by a machine. I want to find a voice in a sea of indistinct hums. And blah, blah, blah.
But honestly, it’s pettiness more than anything else. This year, I’ve decided to say a big eff-you to the algorithm. I intend to watch all sorts of crap on Netflix, sending the algorithm into a tizzy as it tries to figure out why this user has moved from foreign-language noirs to trashy reality TV to cringe-worthy masala films to cartoons. I want my YouTube to not be able to figure out which video or song I’ll play next.
All I want, really, is a balance between human control and machine-defined access. If it means burning it all down, cutting my own nose off as I swim around pitifully with not a clue where to click next, then so be it.
Akhil Soodis a freelance culture writer from New Delhi who wishes he’d studied engineering instead
