September 5th, 2016
(written by lawrence krubner, however indented passages are often quotes). You can contact lawrence at: email@example.com
The traditional regime of recommendation systems has been obsessed with (1). What’s the uplift of recommendation algorithm A vs recommendation algorithm B? Which is driving more click-thrus and conversions?
There’s something fundamentally broken in the this way of thinking though. I don’t care what the computer says. I care about what my friends say. The meaningful music I’ve discovered over the last 10 years has been music liked by someone I respect. Friends. Other musicians I like. Music critics. Online celebrities.
Because how do I decide when to really give music a chance? What music should I really listen deeply to? And which music do I listen to passively without much thought and consideration?
When a friend tells me I really should try out an album, my first interaction with the album might be clumsy and painful. I might not like it. But I tell myself “my friend Sean really knows music.” He’s a thoughtful guy, and I want to understand what interests him. So I keep listening. I give the album a second chance, and a third. I really want to like it. I put work into it. And eventually I do enjoy it.
When a computer recommends music (or movies, art…) I give it one fleeting chance. If I don’t like it I don’t put additional work into it. It’s either a catchy tune that I like on first listen, or I ignore the music. The music feels cheaper. Like top 50 radio. Despite the actual “accuracy” of the recommendation, I have a hard time disentangling my enjoyment of the music from my relationship with the thing doing the recommendation. Stupid computer, what does it know?