The Recommendation Machine
Paul Cantor

There aren’t any bears on these trails, are there?

No Recommendations — the Future

Todd Hannula

for Sobremesa

I only get together with my brothers once a year because we are scattered across the globe with our families. These times together are special — reconnecting with each other and sharing everything we can within a limited amount of time. This makes the conversations dense.

Every minute is about sharing.

A couple of years back we went to Glacier National Park, it was boys only, so the conversations were wide ranging and the sharing was off the scale.

Our rented house was nearly 45 minutes from the park entrance — it turns out this is ‘just down the road’ in Montana.

We were driving back from another big hike at the park when our conversation moved onto music at some point and we traded DJ duties by connecting our iPods or iPhones to the car stereo.

My brothers and nephew have completely different tastes than me — but, we all share a similar obsession with quality. Or so we think.

All you could hear, each time a song started playing, was a rapid fire of questions about the artist and responses laced with memories of where the song originated in their life and how much they enjoyed it.

After about 30 minutes of this random sharing of music, it became apparent that we were never going to be able to recommend all the stuff we wanted to share.

We needed a way for each of us to look over the other guys shoulder and pick and choose what suited us. Screw recommendations, we could just use our curiosity — the source was already trusted.

But how?

Spotify attempts to do this by allowing you to see some of what others are playing or following. But, the entire process still seems a bit narrow. You can see what someone is listening to at the moment or the last thing they listened to if they’re off line.

I don’t think you can see what they are truly into. The list.

Apple Music comes at it from another angle — they use algorithms to suggest music you might like. These are ok — but, they still miss a step, because algorithms.

If I look at Good Reads, it gets a bit closer with the ability to view reading lists.

The problem with all of these approaches, in my mind, is that they all try to recommend stuff to me. And like you mention, Paul Cantor, the lists are massive. I couldn’t possible know where to begin because my curiosity is actually being bludgeoned.

I don’t want recommendations.

Seriously, I don’t want recommendations. I want to peek over a few of my trusted friends shoulders to see what they are listening to, reading or watching. This is not the same as looking at the most read book of everyone I follow — that is about averages. I want unique, distinct, eclectic, and definitely interesting.

I want to fire up my curiosity — to imagine I’m 5 years old and everywhere I look is a potential adventure. Not an avalanche of information, just discrete adventures.

I agree with you Paul — recommendations are difficult. So I’m going to pretty much stop myself from giving them. This is going to be hard — I am a recommendation machine. But…

…the lightbulb has just gone on — my recommendation machine is killing the vibe.

I’m going to invite people into my world, let them look around — discover what I’m vibe-ing on. Ok, I might raise my hand and say over here…but, I’m going to detox on the explicit recommendations.

It’ll be fun to see what happens. Thanks for the heads up.


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