Independent music publishing organizations IMPEL and IMPF have issued a licensing framework for generative AI based on several key principles that will ensure song copyrights are properly valued now and in the future. The framework is based on a number of key licensing considerations, including revenue allocations between master and publishing rights; payments for past use, training outputs, and future exploitations; and mechanisms to establish trust and transparency.
IMPF and IMPEL are now calling on CMOs and other licensors to support the principles to create a fair and sustainable future for the music industry.
“The principles we have established here have been designed to protect songs and songwriters and ensure they are properly valued. With the music business at a new inflection point, it is crucial that we take a strong stance that will set the right precedent for the industry going forward,” said IMPEL CEO Sarah Williams.
“IMPF exists to give independent publishers and the songwriters we represent a collective voice, a mission that has never mattered more, as our industry navigates disruptive change and new rules are being written. The song needs protecting as the keystone of it all,” added IMPF President Annette Barrett.
One principle, they stress, is non-negotiable: the song must be properly valued, and absent other salient factors, at least equally with the recording. Transparency must be embedded throughout the licensing process to reflect the distinct and essential contribution of songwriters and publishers. To that end, technology can play an important role in building trust, supporting clear licensing terms, robust reporting obligations, and rightsholder oversight.
Revenue allocations between master and publishing rights should fairly value the song at least equally with the recording, particularly for generative AI training and exploitation. Payments for past use, training, outputs, and future exploitation must be clearly distinguished and fairly treated. Any deductions, costs, or revenue calculations must be transparent, justified, and applied fairly.
Mechanisms to establish trust and transparency in the attribution and valuation of original works used in AI training and output must be agreed with rightsholders. Downstream uses of AI-generated music must yield appropriate royalties for the songs on which AI models are trained.
IMPEL and IMPF urge all parties on both sides of the aisle to work with independent publishers and songwriters to build a licensing framework that recognizes the true value of the song and creates a fair, sustainable market for the future.
