As I delve deeper into the realm of coding and generative AI capabilities, I’ve stumbled upon a unique intersection of data science and personal taste. This blend provides a window into one of my deepest inclinations: music. In collaboration with ChatGPT’s data analysis tool, I embarked on a quest to decode my musical preferences — a dataset from my “liked” playlist on Spotify.
This dataset is more than a collection of songs, artists, and albums; it’s a tapestry of my life’s soundtrack, tracing back to my early teens. Using advanced analytics, the AI didn’t just enumerate my favourite artists and albums but ventured further into a thematic odyssey, exploring underlying elements like “energy” and “danceability” that thread my tracks together.
Deep dives and surprises
- Artist preferences: TOOL, Max Richter, and Chicos de Nazca dominated my playlist in terms of the number of favourite tracks, pointing to an affinity for the alternative and experimental, transcending genre labels.
- Surprising absences: The lack of artists like Justin Timberlake or Wiz Khalifa, among my many guilty pleasures in pop music, highlighted the unpredictable nature of personal taste.
Temporal echoes and life chapters
2017 stands out as a significant year, resonating with my life’s rhythm at the time — juggling the early challenges of parenthood and a demanding career as a financial journalist at the time, back in Hong Kong.
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This connection between life events and musical preferences to me, underscores music’s role as a temporal anchor and emotional companion. We have all had that feeling, that ability of a song to recall and pinpoint so accurately specific moments in our memories. One of the many fascinating powers of music.
Themes and echoes
The AI’s linguistic analysis of song titles unravelled motifs like ‘sun’, ‘life’, and ‘dream’, echoing universal human experiences and offering glimpses into my subconscious landscape.
The symphony of metrics
- Balance in energy: My playlist’s moderate energy level mirrors life’s oscillations between calm and chaos — reflecting for me the inability of averages to tell us much about the underlying data.
- Danceability: A subtle lean towards danceable tracks reflects an underlying rhythm in my everyday life. Yes, I like drums. And all beats, really, EDM included!
- Melancholic undertones: The prevalence of introspective tunes speaks to a contemplative and reflective nature. Anyone who has met me will not be surprised.
Synthesis and revelation
This exploration transcends mere data analysis, hinting at the role AI could play in curating our musical journeys. It’s a fusion of technology and human narrative, potentially reshaping our cultural landscapes and personal discoveries.
Reflections and projections
This AI-assisted journey through my musical landscape has been enlightening, revealing the dynamic tapestry of my tastes. It’s a digital mirror reflecting my evolving identity, with algorithms as the new narrators of our personal stories.
This foray into the analytics of personal music taste exemplifies the synergy between technology and human curiosity. It’s a testament to how AI can serve as a lens, magnifying our preferences’ patterns and potentially uncovering aspects of our inner selves.
An appendix
Most prevalent words in my favourite songs’ titles (as explained by GPT-4):
- “man”: A window into personal identity and individual journeys.
- “sun”: Symbolic of life cycles, energy, and new beginnings.
- “life”: Captures the essence of existence and human experiences.
- “heaven”: Reflects aspirations, transcendence, or ethereal states.
- “heart”: Embodies the core of human emotions and connections.
- “dream”: Bridges the gap between aspirations and the subconscious.
- “feel”: A focus on the visceral and emotive aspects of music.
- “alive”: Celebrates vitality, life’s essence, and its myriad forms.
- “go”: Suggests movement, evolution, and the passage of life.
- “song”: A meta-layer, reflecting on the art of music itself.
- “silence”: Represents introspection and the spaces between sounds.
- “night”: Symbolises mystery, introspection, and solitude.
- “never”: Conveys notions of infinity and the unattainable.
- “lost”: Themes of search, longing, and existential journeys.
This article originally appeared on the newsletter Code Red for Writers.
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This article was first published on March 18, 2024
The post Dancing through data: What can AI-powered insights into my own music tastes reveal? appeared first on e27.