Apple Music to Label AI-Generated Tracks, Report Says
▼ Summary
– Apple Music is introducing new metadata tags for labels and distributors to flag AI-generated or AI-assisted content in songs.
– The new tags will allow distributors to specify if AI was used in a track’s artwork, music, lyrics, or music video.
– This is an opt-in system, requiring labels and distributors to manually choose to disclose their use of AI.
– Other platforms like Spotify are taking a similar manual approach, while Deezer is attempting to use AI-detection tools.
– Creating accurate in-house AI-detection systems for music, as Deezer is trying, remains a significant technical challenge.
Apple Music is introducing a new system for identifying songs created with artificial intelligence, aiming to provide greater clarity for listeners. The platform is updating its process so that record labels and music distributors can now include specific metadata tags when uploading content. These tags are designed to signal when AI has been used in key components of a track, such as the artwork, the instrumental music, the lyrical composition, or an accompanying music video. This move toward transparency comes as listener curiosity about AI’s role in music production continues to grow, with online communities recently discussing the potential for such a feature.
The initiative was detailed in a newsletter sent to industry partners, outlining how the new metadata fields will function. Traditionally, metadata includes basic information like song title, artist, and genre. The new optional tags will allow distributors to manually disclose the involvement of AI, distinguishing between human-created and AI-assisted elements. This opt-in approach places the responsibility for disclosure squarely on the content providers, a strategy also being adopted by competitor Spotify.
While Apple and Spotify rely on voluntary labeling from distributors, other services are exploring different methods. Platforms like Deezer are reportedly developing their own in-house AI detection tools to automatically identify such content. However, building these automated systems presents significant technical hurdles, as achieving high levels of accuracy in detection remains a complex challenge. The industry-wide effort reflects a broader push to establish clear standards as AI becomes a more common tool in the creative process.
(Source: TechCrunch)
