
Why New Music is SO BAD 😔
8 chapters
- The 2012 Research Study on Music QualityStudy OverviewA 2012 article measured the evolution of contemporary Western popular music using the Million Song Dataset, containing metadata and audio analysis for a million songs.Measured Parameters• Pitch variation • Timbre variation • Dynamic rangeResearch SourceData came from the Econest, a musical intelligence platform that analyzes songs.Initial ConclusionThe study claimed pop music is getting worse, supporting the narrative that modern music quality has declined.
- Problems with Dynamic Range as a Quality MeasureThe Flawed MetricDynamic range has little or nothing to do with song quality and is a problematic measure to use.Listener PreferenceAn experiment with drum loops showed that most people preferred tracks with less dynamic range, contradicting the assumption that more dynamic range equals better quality.Why It FailsEnjoyment of music with different dynamic ranges varies by listener preference, making dynamic range unsuitable as an objective quality metric.ConclusionThis parameter should be dismissed from the quality analysis entirely.
- Timbre Analysis LimitationsMeasurement MethodThe timbre parameter measures the frequency response of each discrete segment, creating frequency response curves for each track section.Insufficient MeasurementA single parameter alone is too limited to accurately define the timbre of a song, as identical-looking frequency responses can sound completely different.Modern Music AdvantageModern songs are actually richer in timbre because producers have access to endless instrument libraries and can add a million different sounds, impossible 40 years ago.Research AssessmentThis part of the research is misleading and should be dismissed from the analysis.
- Pitch and Harmony Complexity DebateResearch ValidityThe model for pitch and harmony is more solid compared to the other parameters and aligns with the observation that harmonic content has become simpler.Quality IndependenceSong quality is not determined by its level of complexity. Both minimalism and maximalism are valid artistic approaches that fluctuate throughout music history.Artistic ValueCraftsmanship can be achieved by any means regardless of harmonic complexity, making simplicity in harmony not inherently worse.ConclusionArguing that simpler harmony makes a song worse is ignorant and dismisses this metric from the analysis.
- Why People Think Old Music Was BetterResearch MotivationAfter reading research papers and considering extensive data, three scientific reasons explain why people believe music was better in the past.Aging Effect on Perception• Research on neural representation of musical harmony shows that older people have lower ability to identify dissonant chords • As you get older, more things start to sound similar to you • This explains why older people complain that everything sounds the sameScientific FindingStudies comparing groups older and younger than 40 years old found that older listeners rated dissonant chords as less unpleasant than younger listeners.Biological ExplanationThe aging process affects how the brain processes musical harmony, making it harder to distinguish between different harmonic structures.
- Democratization of Music Production1980s Music Industry• Few recording artists due to high cost of recording studios and gear • Gatekeepers (record labels) filtered tracks to identify best songs and artists • Radio and TV provided additional filtering, ensuring only quality music reached listenersHidden Gems ProblemDespite gatekeeping ensuring quality, many good tracks were left behind and never reached listeners because they didn't pass through all industry filters.Modern Music Landscape• Millions of songs ready for release due to easier recording without expensive gear • Gatekeepers are mostly gone, allowing most tracks to be released • Social media and algorithms replaced radio and TV as the main distribution driverMixed ConsequencesWhile more music is accessible, listeners are exposed to both high-quality and low-quality tracks, and many focus only on algorithm-promoted content.
- Open-Mindedness and Musical ExplorationOpenness DefinitionOpenness to Experience is an academic term describing a person's willingness to explore new music, genres, and artistic styles.Age-Related Differences• Young people have higher openness, going out of their way to explore new songs and genres • Older people have lower openness and find it harder to seek out new music and genres • Exploring new music requires more effort as people ageFriendship AnalogyMaking new friends becomes harder with age, requiring more effort, and new friendships are less strong than those made when younger. The same principle applies to musical exploration.Connection StrengthConnections made when listening to music for the first time are much stronger. Repeating these same connections and feelings is harder as people age, making past music feel more meaningful.
- The Econest Algorithm and Spotify IntegrationEconest BackgroundThe 2012 article used data from the Econest, a music analysis platform. By 2016, Econest had over 30 million songs tagged with advanced algorithms.Spotify AcquisitionIn 2014, Spotify acquired Econest for 50 million euros, making it a key component of Spotify's recommendation systems.Algorithm Applications• Personalized playlists listeners encounter are driven by Econest algorithms • Discovery Weekly is created using Econest technology • Trufflepig, an internal Spotify tool, uses Econest to create playlists by mood or occasionPlaylist CurationEditor-created playlists like Coffeehouse and Tenga Friday are also available thanks to Econest and Trufflepig technologies.





