YouTube Music launches new labels as AI-generated music floods streaming platforms

YouTube Music announced Wednesday the rollout of a new labeling system aimed at improving transparency around songs created with the help of generative AI. Now listeners will be able to easily identify tracks created using AI, including those involved in composition and vocals.

The label will appear on the player page. Clicking on this label provides additional information about the specific role of AI in the track’s creation.

Notably, these labels will also extend to the main YouTube app. 

YouTube said it collaborated with various music partners and deployed its own detection tools to identify AI-generated music. According to its help page, partners using YouTube can declare their work’s use of generative AI through one of three designations: Fully Gen AI, Partly Gen AI, or No Gen AI. 

“Fully Gen AI” applies to tracks that are entirely generated by AI, while “Partly Gen AI” refers to works where artists may have incorporated AI-generated components but added their own live elements. Tracks edited using pitch-correction tools such as Auto-Tune fall under the “No Gen AI” category.

The move comes as AI-generated music rapidly expands across streaming services, and many platforms are adopting their own approaches. For instance, Apple Music has plans to introduce “Made With AI” labels as part of its AI Transparency Tags later this year. Spotify also has AI labels, as well as a music spam filter.

Deezer has taken one of the stricter stances, reporting in July that it was receiving nearly 90,000 fully AI-generated tracks daily. The platform labels detected AI-generated music and excludes it from algorithmic recommendations and editorial playlists, while also withholding royalties from fraudulent streams. The company is also working on an option to let users filter out AI-generated music.

TIDAL also labels recordings it identifies as entirely AI-generated, allows listeners to disable them, and excludes these recordings from royalty attribution. 

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