Biggest songs hide metadata problems
The world of music history is built on dazzling peaks of artistic genius and massive commercial success. Recordings by legends like Michael Jackson, Fleetwood Mac, and the Eagles have generated decades of revenue, backed by some of the world’s largest publishing houses. Yet, beneath this glittering surface, a surprising metadata mess is threatening to unravel the financial tapestry of the music industry.
A recent investigation reveals that even the most valuable music catalogues may contain fundamental problems, specifically recordings that are mistakenly connected to entirely different musical works. The study, titled Who’s Eating Your Lunch?, utilized an AI-powered research tool to examine publicly available data from the Mechanical Licensing Collective (The MLC).
Researchers dove into the data, examining 111 tracks across ten of the best-selling albums of all time, including iconic records like Thriller, Rumours, and Hotel California. While the data showed high registration rates, the deep dive revealed a significant discrepancy: 56 tracks (50.5%) were associated with multiple musical-work records, suggesting recordings linked to the wrong compositions.
This isn’t just about missing credits; it’s about misplaced royalties. The inconsistencies point to instances where a single recording might be tied to the wrong underlying song, potentially skewing how composition royalties are allocated. For example, investigations uncovered bizarre connections, such as Fleetwood Mac’s “Don’t Stop” being linked not only to Christine McVie’s composition but also to Queen’s “Don’t Stop Me Now” and Journey’s “Don’t Stop Believin’.”
Such errors highlight a crucial systemic issue: being matched to a song is not the same as being matched to the right song. As one researcher noted, “A registration can look complete and still point to somebody else’s song.”
The implications of these data inconsistencies extend far beyond superstar artists. For independent songwriters and self-releasing musicians, these gaps are particularly concerning, as they often lack the resources to manage complex publishing teams. The study emphasizes that while improving registration rates is important, it does not inherently solve the problem of misattribution.
The irony of the situation is that this very challenge offers a compelling opportunity for technological intervention. While AI remains a contentious topic for many creators, platforms like AIMi are demonstrating how artificial intelligence can act as a powerful tool to protect creators’ earnings. By analyzing tens of thousands of musical works, the technology can identify contradictions in rights metadata and prepare evidence for human review.
To make this transparency a reality, the research calls for broader action. The discoveries were made possible because the MLC made its data publicly accessible. AIMi is now urging other collection societies to adopt similar standards for independent scrutiny, setting the stage for a future where music rights administration is clearer, more equitable, and powered by smart technology. A free catalogue-auditing service is already scheduled to launch by the end of 2026.
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