Shuffle: Making Random Feel More Human
Spotify EngineeringNovember 13, 2025
Why It Matters
Understanding the gap between mathematical randomness and human perception is crucial for UX. This article demonstrates how applying signal processing concepts like dithering to data ordering can solve common user complaints about perceived bias in automated systems.
Key Takeaways
- •Spotify addresses the 'clustering' problem where true randomness leads to repetitive sequences of artists or genres.
- •The engineering team transitioned from standard Fisher-Yates shuffling to a 'balanced shuffle' algorithm.
- •The balanced approach is inspired by dithering techniques used in image processing to distribute points evenly.
- •The algorithm calculates ideal distances between tracks from the same artist to prevent back-to-back occurrences.
- •This method improves user satisfaction by aligning the shuffle logic with human psychological expectations of variety.
Keywords
Fisher-YatesBalanced ShuffleDitheringAlgorithm DesignUser PerceptionData Distribution
Content Preview
Shuffle has always been one of Spotify’s most-used features, and also one of the most misunderstood. For...
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