Beyond 4/4: How Culture Shapes AI's Musical Brain

AI music models are powerful creative tools, but what are they actually learning? We often assume technology is neutral, but AI inherits the biases of the data it's trained on. In music, this means our algorithms have a distinct cultural point of view, one that is overwhelmingly shaped by Western musical traditions. This episode dives into how cultural signatures get encoded—or erased—in AI training data. We explore why most AI-generated tracks sound the way they do and the risks of creating a digital monoculture. We look at the technical limitations of formats like MIDI and how they fail to capture the richness of global music, and we celebrate the people working to build a more inclusive and interesting future for AI music. Imagine trying to preserve the unique, spiritual music of the Manchu people, a tradition at risk of fading away. But the AI tools you want to use only understand Western scales and rhythms. How do you capture the soul of a culture in a dataset when the technology itself is biased? We spotlight the researchers tackling this exact problem, creating a new dataset from the ground up to teach AI a new musical language and preserve a priceless cultural signature. In This Episode, We Ask: 1. Why do most AI music generators sound so... Western? 2. Is the MIDI format unintentionally erasing musical diversity? 3. How can a dataset be used to preserve the music of an entire culture? 4. What is a "musical signature" and how can AI learn to recognize it? 5. Are we creating a global 'AI monoculture' in music? 6. Can AI become a tool for decolonizing music creation? 7. What does it take to build a truly global and inclusive AI music model? 8. How do you teach an AI about musical traditions that don't use Western scales and rhythms? Follow my YouTube: https://www.youtube.com/@chenran818 or listen to my music on Apple music, Spotify or other platforms: https://ffm.bio/chenran818