I love listening to reggae and Spotify knows it too. In fact, most of my recommended tracks are reggae tunes from artists like King Tubby, The Congos and Bob Marley.  For the most part, I oblige the mysterious “recommended” tool.  What’s not to love about an app that magically recommends endless reggae playlists?

Well for starters, I also love music from many genres and eras.  Just because I’d love taking a deep dive into Alton Ellis’ catalog doesn’t mean I’d forgo listening to Frank Sinatra while making dinner or Daft Punk while exercising.  The joy of Spotify is the sheer enormous variety of music we can explore. I love the surprise of a song by an artist I’ve never heard of before.  So even though I love reggae, why do I feel bummed when Spotify keeps recommending “The Tide Is High” by the Paragons? Have I broken this magic machine?

Spotify uses a fascinating and complex set of algorithms that study data with tons of factors on several fronts.  It uses simple data points such as which song I “heart” or which songs I add to a playlist.  But there are some other not so obvious tools Spotify uses such as studying rhythms, song keys, phonetic phrases or even how likely you are to share a track with a friend. It’s a very clever science data machine designed to keep you engaged with the music and with the app itself, and I’m afraid I’m not using it to its full potential.

So what’s the connection between this love of reggae and this science data machine?  On the one hand, I love my recommended playlists to be chock full of old school reggae tracks, but say by chance the new Harry Styles track comes up and I skip it after three seconds, I’m teaching Spotify to take a hint and record a data point that I’m not that into pop music, or even worse that I’m not that into Harry Styles.  (Not true!)  But my actions would say otherwise. When I press skip, perhaps my self proclaimed eclectic tastes are not as diverse as I think they are. Next thing I know, I’ve skipped my way into reggae oblivion.

When trying to make a difficult decision like where to move, when to end a relationship or start a new job, we’re more likely to set ourselves up for success by asking for advice from a diverse data set of friends, family and even strangers. This is who I think I am and this is what I do – is just one data set from many sets that can be considered. If I skip out on seeking new activities and listening to different perspectives, my life could start to sound like one endless version of, well, The Tide is High by The Paragons.

So next time that song you’ve never heard before starts to play, why not listen to it all the way through and give more data to the algorithm? You might discover a new hobby, a new talent, a new job, a new person or even simply a new song. To me pressing “heart” on Spotify to discover the complexities of reggae music throughout the years is a love of mine. Patiently not skipping those pop songs only to discover the joy of listening to Dua Lipa on a run, well, that’s just science.