The rise of music science

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The document discusses the history and future of the music industry. It describes how music has evolved from physical goods and radio broadcasts to streaming and digital formats online. It also discusses how music services now analyze user listening data to optimize recommendations, detect copyrighted content, and understand how music tastes change over time. Finally, it suggests music in the future may involve more human-machine collaboration, with compositional feedback loops incorporating biometric data on listener preferences.

Technology

SOLVEfor
INTERESTING
OTHERWISE LIFE IS DULL.
MUSIC 
SCIENCE

Choice constraints
(program vs. on-demand)

The economics
of ﬁckleness
http://www.hypebot.com/hypebot/2014/05/music-adhd-users-love-the-skip-button-says-spotify-data-scientist.html

Part two: When you listen
to music, it listens back.

We know what you did. All of it.
http://i.imgur.com/pzfcYnh.jpg

We know you’re
getting old.
http://skynetandebert.com/2015/04/22/music-was-better-back-then-when-do-we-stop-keeping-up-with-popular-music/

We know
music’s
getting stupid.
http://consequenceofsound.net/2015/05/the-lyrics-of-recent-no-1-singles-average-at-a-third-grade-reading-level/

IWe know how
we got here.
https://medium.com/the-physics-arxiv-blog/genetic-data-tools-reveal-how-
pop-music-evolved-in-the-us-48ad60bf495b

Times a song in “heavy
rotation” is played daily
0
15
30
2007 2012
266

Part three: The Turing
Problems of Music Science

The tension between 
creativity and optimization

http://www.musicbusinessworldwide.com/the-inventor-of-google-maps-wants-to-change-the-way-you-listen-to-music/
From player to composer

Ultimately, digital isn’t about copying. 
It’s about feedback loops.

First, we will explore the power of a compounding insight machine (as opposed to an ad hoc insight machine): -Human time is focused on improving logic, rather than executing outcomes -Less dependent on human biases or frailty -Robust to and tested by a huge collection of scenarios Second, we will explore the anatomy of such a machine: -The roles you need to cast on your team and who to fill them with -The key processes required for generating and capturing insight and, more importantly, for building upon those insights -The technology required to enable this approach

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