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.” Childers 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.