My Annual Playlist Tradition To Feed the Algorithm

One of my favorite annual traditions is dumping every song that resonates with me into a massive Spotify playlist. I try not to overthink what goes in these playlists. If a song catches my attention or triggers a gut reaction in me, it goes in. Here’s the one for 2023, which is just getting going:

Each playlist is best served shuffled, and each one is on high rotation throughout the year — not only because I enjoy hearing what created a positive, visceral reaction in me, but also because I’m training Spotify’s algorithms to give me more of what I love. I know, I know. I should aspire to pop my musical filter bubble and try new things. But, hey: I like what I like (electronic music) and no amount of Taylor Swift is going to change that.

I give the playlist a name that alludes to an inside joke or experience. This way, it always evokes a moment in time and any memories associated with it.

In 2022, it was called “Serious Bidness” for a very important “board meeting” I attended with a bunch of friends that quickly descended into silly, boozy ‘bidness.’

In 2021, I called it “Owl Radio” for the nocturnal creatures hooting nightly in my backyard. I love owls!

In 2020, I innocently (and unoriginally) called it “The Buzzzzz.” By March, I had to add “-kill” in parenthesis to capture the pall of the year. Boo, 2020.

I’d like to think that “there’s no algorithm for cool,” that only someone with ears like mine can create playlists like these, oriented around a sound and a vibe, but that’s not 100% true. As Twitter’s former Head of HITL Curation, David Smydra, pointed out to me during our conversation for my podcast, The Art of Curation, Spotify is a great example of machine learning done right—an algorithm for cool in action.

“I will confess I’m regularly impressed by how well Spotify recommends things both in collections and the diversity of collections,” Smydra told me. “More than any music streaming service, it breaks out of a mold really quickly…It’s giving me more things that are similar to and related to what I’ve asked for but they’re taking me in new directions or exposing me to new artists that I haven’t come across yet. That just really nails so much of what this work is about.”

What do you think? Is there an algorithm for cool, and what are some other great examples?