Spotify uses fake artists to cut real artists' royalty costs

Occurred: 2017-

Spotify is accused of promoting fake "ghost artists" in order to minimise royalty payments to real musicians and boost its financial profitability, raising concerns about the company's leadership, values and integrity. 

What happened

Spotify has been systematically promoting non-existent or low-cost artists, referred to as "ghost artists," to fill certain playlists - notably in genres such as ambient, sleep, "focus" and lo-fi hip-hop -  with cheaper music, according to credible media sources.

The strategy is purportedly designed to unobtrusively manipulate users of the Spotify app into listening to low quality music produced by entities listed under fake or pseudonymous names - some of it reputedly AI-generated - and thereby reduce the percentage of royalties paid to actual artists.

Specifically, Spotify created an internal programme called Perfect Fit Content (PFC) in which employees listed music produced by specially commissioned production companies - including Epidemic Sound, Firefly Entertainment, Hush Hush LLC and others - on the app's curated playlists.

Why it happened

By flooding popular playlists with low cost generic music, Spotify allegedly algorithmically diminishes the overall share of streams that go to established artists, thereby lowering their royalty rates during negotiations with record labels. 

The practice is seen as part of a broader trend where streaming services seek to optimise costs in an oversaturated music streaming market.

What it means

The allegations raises questions about the fairness and transparency of Spotify in compensating artists. 

Many musicians have already expressed concerns about Spotify's Discovery Mode, which offers increased exposure at the cost of reduced royalties, further complicating the economic landscape and opportunities for independent creators.

System 🤖

Documents 📃

Operator: 
Developer: Spotify
Country: Global
Sector: Media/entertainment/sports/arts  
Purpose: Manipulate user behaviour
Technology: Machine learning
Issue: Ethics/values; Fairness; Transparency

Investigations, assessments, audits 👁️