Serendipity (in life and music)
In Daniel Pink’s virtual talk to a group of Kellogg students yesterday, one of his “major keys” to life was: serendipity is in charge of life
Speaking to a group of people who are not only naturally inclined to try to plan and control but then taught to do so over the course of getting an MBA, Pink’s point was that life’s most unexpected turns will hand us our greatest opportunities. He promised these will be impossible to predict, yet will make a lot of sense in retrospect. Finally, he urged us to be open to this serendipity and to cede the impulse to plan and control.
This wasn’t new advice, but valuable nonetheless because the impulse to plan and control is a very strong reflex that needs to constantly be reminded to chill out.
This tension between serendipity and control reminded me of a debate going on in the music world, about whether algorithms are ruining the serendipitous element of how we discover music. In an interview on FiveThirtyEight’s podcast earlier this week, Ben Ratliff, music critic and author of Every Song Ever, commented:
Music is mysterious. And I don’t want robots completely in control of my sense of discovery.
He calls out features such as Spotify’s Discover Weekly and Pandora’s personalized radio stations as reducing the human element of music down to a set of numbers and equations which do not fully represent the wholeness of a person’s musical tastes and personality. Furthermore, he worries that by categorizing individuals into set listener profiles, we miss the opportunity to find things outside of our comfort zone. He postulates, “Something is being lost isn’t it? Isn’t the thing that’s being lost you and your efforts to figure out what you like and what you respond to?”
My issue with his argument (and others similar to it) is it inherently assumes all music listeners identify with music in the same way. As I’ve found in my research, not all people have the desire to research and discover music in an active, in-depth manner. Some people are perfectly content to listen to whatever music on FM radio. Others spend hours on hours reading music reviews on Pitchfork or scanning Soundcloud for the latest remixes of their favorite tunes. As I mentioned in my article on the adventuresome quotient, Some people have very specific, ingrained music tastes whereas others have a more flexible set of preferences that they are willing to adapt as they stumble upon new songs, artists, or genres.
Simply stated, some people are music buffs while others are not.
For those who are not, they are listening almost purely to music curated by others, whether it be the FM radio DJ or an algorithm. They are being put in a carefully calculated box according to their past listening habits and are happy to stay in that box. Before algorithms existed, they also weren’t seeking to push the boundaries of their music comfort zone.
The music buffs, however, are not only listening to tunes curated by others, but also putting in the work to find songs on their own accord. By nature of their love for music, they are exploring all sorts of sources of new music and constantly expanding their tastes. They aren’t at risk of missing out on that feeling of discovering an awesomely weird new song because they have multiple sources of discovery. For these people, the algorithms are another piece of the magic, not a replacement of it.
This is how I view algorithmic recommendations — simply as one more source of new music with the potential to reach an audience who was previously unreachable.
Libby Koerbel loves to analyze ambiguous questions, listen to live music, and meet new people. She is an expert strategist with experience at the Boston Consulting Group, Pandora, Universal Music Group, Muzooka, and Pritzker Group Venture Capital. She is currently a MBA student at the Kellogg School of Management.
This post is a part of a series on how millennials discover content. Read some of the initial findings on millennial trends & new music discovery, as well as some musings on: innovation in music production, your adventuresomeness quotient, framing uncertainty, curation wars, music tastes, sticky subscription models, and abundance.