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World Congress 2026 Europe - Virtual Stage • Jul 2, 2026 • Session details

The 100 Days of Colour: Unearthing Algorithmic Bias in Music Streaming

Emily Wright

When Emily Wright realized 95% of her Spotify recommendations featured white artists, she launched a 100-day experiment. Discover how she exposed the hidden algorithmic bias controlling your playlists.

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#1 about 4 min

Identifying recommendation loops and algorithmic bias in music

Analyzing personal listening history reveals a subconscious preference amplified by streaming recommendation engines.

#2 about 4 min

Establishing principles for testing algorithmic responsiveness to new data

Flooding the recommendation engine with new inputs without using search functions ensures unbiased algorithmic reactions.

#3 about 3 min

Tracking demographic shifts across core algorithmic recommendation playlists

Monitoring various auto-generated playlists over time measures how quickly recommendation algorithms adapt to changed input.

#4 about 3 min

The persistent influence of historical data on automated recommendations

Clearing historical preferences reveals how algorithms double-weight legacy interactions over recent behavior shifts.

#5 about 4 min

Visualizing playlist accessibility and the convenience hierarchy concept

Grouping recommendation access points demonstrates how algorithmic conveniences reflect and reinforce dominant collective priorities.

#6 about 6 min

Human curation frameworks and algortorial filtering in streaming platforms

Examining how base recommendations established by human curators constrain subsequent machine learning personalization options.

#7 about 5 min

Identifying the curator trap in algorithmic training models

Comparing internal company demographics to baseline human-curated recommendations highlights systemic limits in machine learning systems.

#8 about 6 min

Recognizing and mitigating digitized subconscious bias in everyday technology

Acknowledging the human elements within automated systems helps navigate convenience hierarchies and minimize algorithmic manipulation.

Matching moments

2:18 min

Addressing implicit human biases embedded within algorithmic datasets

Cassie Kozyrkov · World Congress 2022

4:41 min

Identifying systemic biases in algorithms and artificial intelligence tools

Emily Wright Emily Wright · Europe 2026 Virtual

2:07 min

The hidden dangers of automated algorithms

Torsten Stiller Torsten Stiller · World Congress 2025

1:24 min

Navigating spurious correlations and ethical concerns in data analysis

Johanna Pirker Johanna Pirker · World Congress 2021

3:48 min

Driving corporate AI accountability through public pressure

Björn Bringmann Björn Bringmann +3 · World Congress 2024

2:12 min

Algorithmic polarization and the confirmation bias rabbit hole

Jeff Watkins Jeff Watkins · World Congress 2025

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