Spotify is going full 'Minority Report' with its new personality patent

A new patent approved for the streaming giant will "identify a personality trait of a user... and the context in which they consume the content.” Wonderful.

As first reported by Music Business Worldwide, earlier this week Spotify received approval for a patent filed back in 2018 described as, "Methods and systems for personalizing user experience based on [user] personality traits.” How would Spotify determine a user's "personality traits?" By tracking and categorizing every minute of their time on the app, obviously.

According to the patent, Spotify would be able to assign various characteristics to music tracks, genres, and usage patterns based on a machine-learning algorithm, then correspond these to "personality traits" like "openness, agreeableness, extroversion, neuroticism, and conscientiousness" to create user profiles. Actions like users' frequency skipping a track or employing the "shuffle" feature will also aid in assigning them to a number of predetermined classifications. These subsequent profiles, of course, could then be exploited to provide more "personalized" ad experiences and future content suggestions.

Personalized to the point of creepiness — It's not necessarily news that companies are developing new and improved ways to reduce individuals into data points for better profit margins and algorithm-directed behavioral predictions.

The leaked patent, however, does provide a detailed look into just how data harvesting giants like Spotify go about structuring these methods, and how advanced these capabilities are becoming. For example, Spotify's patent explains that these personality trait divisions could manifest for users in changing "a tone of voice for messages for presentation" in advertisements, promote additional content "associated with the... personality trait." More "extroverted" users might experience more upbeat-tone ads or party-oriented playlist suggestions, while "introverted" listeners could come across reserved commercial breaks and music.

Algorithms of oppressive audio — The implications are far more wide-reaching than simply how annoying and/or relevant ads and tunes will become on an app like Spotify. Machine-learning algorithms come from somewhere (i.e. human developers) after all, and therein lies the potential for various unintended biases and shortcomings to only reinforce themselves over time.

Siloing users this way could easily lead to reinforced cultural echo chambers (no pun intended), and with Spotify aggressively moving towards expanding its media influential dominance beyond music and into increased podcast offerings, it's hard to see how this couldn't be socially detrimental. This is, after all, the company whose CEO recently backed Joe Rogan's anti-trans podcast content, so the idea of a Spotify R&D team delving into human psychology isn't the most thrilling of prospects. Maybe they should just stick to letting us search those random earworms stuck in our head via lyric snippets? That's actually a big damn help.