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There is no chapter about generative AI in my book about music streaming. In part this is because while I was writing it, things were changing in AI so quickly that almost anything future-looking I tried to say would have been abjectly obsolete by the time the book was printed. But mostly it's because music's most pressing problems are cultural and economic, and do not require incomprehensibly complicated technical solutions. Spotify did a lot of machine learning for music recommendation purposes, and my rueful experience was that I could almost always do better, at least in the explainable human terms that I personally cared about, with SQL queries and math. I like math, but I hate SQL and once spent 4 years of my life trying to design a better query-language and data-model than that. I didn't pick tools because I liked them, I picked them because I cared about the results, and those were the tools that allowed me to produce results with human and cultural implications I could understand and attempt to improve.  

All my jobs, I realize with the forced perspective of spending the last few months explaining my life to strangers over and over, have involved negotiating with machines on behalf of humanity. Algorithms and computer programs are tools for accomplishing human purposes. SQL JOINs and LLMs are ultimately both imperfect techniques for collecting collective knowledge, and like all tools should be held to the standard of allowing humans to be more human, more intentional, more curious, more joyful.  

The music book is also a book about technology and algorithms and cultural mediation. In its first draft it had a very long and detailed chapter about the very many ways this technology can go wrong, which my editor cheerfully volunteered to preserve by moving it to an appendix. On reflection, I realized it actually belonged in a different book.  

That book is provisionally called The Robots Will Not Win. The robots, at the moment, are not acting entirely convinced of this. My music streaming book is split about equally between new fears and new joys. As I started outlining the next one, it quickly became clear to me that I know more about the fears of AI than the joys. I don't want AI that pretends to be people. I don't want an internet clogged with mechanical recapitulations of word-correlations that humans have already established. I don't want luminous fictitious tiny houses in which you would have to climb over the sofa to get to a kitchen where the faucet pours water directly onto the countertop and the oven has no door. I don't want AI that turns human agency into vaguely prompted parades of anonymous golems.  

And yet, I love people and I love computers. I love tools. Good tools imbue us with superpowers. We deserve good tools. Or, put the other way around, the more powerful our tools, the more urgent our obligations to make sure they are specifically built to empower humans, individually and collectively.  

I didn't write this book intending it to be the end of a life-chapter, but when the interesting timing of my Spotify layoff presented the opportunity, it was surprisingly easy to change a few tenses and understand it as a cross between a progress report and an exit interview. There are plenty of things still to be done in music, but I'm going to try to help them with human advocacy and technological guidance for a while, instead of SQL queries embedded deeply in existing corporate constraints.  

Meanwhile, it's not time to write the book I want to write about AI yet, because I don't know how it ends, or even necessarily how it goes next. But I know how it has to develop, because the tools change but we are still ourselves. I know what it feels like when good questions lead you to better questions instead of easier answers. I know that when we understand the fears better than the joys, the only thing to do is to make the joys we are missing.  

Back to work.
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