In this episode of the Arts Management and Technology Lab, Samantha Childers explores why so many songs recommended by streaming platforms like Spotify, Apple Music, Amazon Music, and YouTube Music sound strikingly similar. She breaks down the inner workings of music streaming algorithms—how metadata, collaborative filtering, content-based filtering, and continuous feedback loops collectively shape the "perfect playlist." Samantha also examines Spotify features such as Discover Weekly and Discovery Mode, uncovering how these tools influence music discovery, artist visibility, and even compositional trends as musicians increasingly write with algorithms in mind. Alongside these technical insights, she raises critical ethical questions about data privacy, algorithmic bias, pay-to-play practices, and the shrinking role of human curation. Ultimately, the episode invites listeners to rethink how algorithm-driven platforms shape not only what we hear but also how we discover, value, and experience music.

SHOW NOTES

Samantha Childers

A Critical Research of Spotify's Business Model—The Case of Discover Weekly

We Tested Popular Music Streaming Services — These Are the Top 6 You Should Check Out In 2025

About Spotify- Newsroom

The Role Of Music Streaming Algorithms In The Industry

Algorithmic Symphonies: How Spotify Strikes the Right Chord

Algorithms in Music: Blessing or Curse?

Understanding recommendations on Spotify

How to Break Free of Spotify's Algorithm

Pay-to-Playlist: The Commerce of Music Streaming

Impacts of AI on Music Consumption and Fairness