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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesOn October 22, 2024, more than 10,500 creators, creative-industry organizations and cultural institutions initially signed the Statement on AI training, objecting to the use of creative works without permission to train generative-AI systems. The coalition included actors, musicians, authors, photographers, publishers and rights groups. Its statement was a policy demand—not a court ruling—and did not establish that every form of AI training is illegal.
What happened on October 22, 2024?
The Statement on AI training launched with more than 10,500 signatories. News/Media Alliance reported the initial figure on the day of the announcement, while the International Federation of the Phonographic Industry (IFPI) identified October 22 as the publication date. The signatories were not all individual visual artists: organizations, publishers, trade associations and other cultural institutions joined alongside individual creators.
The statement’s live website later displayed 50,544 signatories. That is a cumulative figure shown after the launch and should not be confused with the more than 10,500 reported on October 22, 2024. The current list is available at aitrainingstatement.org/signatories.
| Figure | What it means |
|---|---|
| More than 10,500 | Initial creators and organizations reported at launch on October 22, 2024. |
| 50,544 | Later cumulative total displayed on the statement’s live signatory page at the time of reporting. |
What did the statement say?
The entire statement was deliberately short. It said:
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“The unlicensed use of creative works for training generative AI is a major, unjust threat to the livelihoods of the people behind those works, and must not be permitted.”
That sentence expresses a broad principle: generative-AI developers should obtain authorization or a license before using creative works as training material. It does not set out a technical definition of a dataset, distinguish web scraping from text-and-data mining, specify one licensing model or identify a particular defendant. Nor is it a lawsuit, statute or judicial finding.
The Authors Guild described the campaign’s policy objective as requiring AI companies to license the creative works on which they train. That more detailed licensing proposal came from supporting advocacy, rather than from additional clauses in the one-sentence statement itself (Authors Guild).
Who signed?
“Artists” is understandable headline shorthand, but the coalition was much broader. Reported and listed individual signatories included:
Actors and performers
- Julianne Moore
- Kevin Bacon
- Rosario Dawson
- F. Murray Abraham
- Kate McKinnon
- Sean Astin
Musicians and composers
- Thom Yorke
- Björn Ulvaeus
- Robert Smith
- Billy Bragg
- Max Richter
- Kate Bush
- Geoff Barrow
Authors
- Kazuo Ishiguro
- James Patterson
- Ian Rankin
- Malorie Blackman
- William Boyd
- Tracy Chevalier
Institutional supporters included IFPI, News/Media Alliance, publishers’ and authors’ organizations, the Association of American Publishers and Penguin Random House. The official statement website is the authoritative place to check the evolving list of names (Statement on AI training). The Washington Post also reported several prominent signatories.
Who organized and supported the campaign?
The statement was associated with Ed Newton-Rex, a former Stability AI executive who later founded the nonprofit Fairly Trained. Publishers’ Licensing Services said Newton-Rex resigned from Stability AI in 2023 over concerns about using copyright-protected works without permission (Publishers’ Licensing Services).
IFPI said it was among the initial signatories and described the effort as an industry-wide creator-rights initiative (IFPI). News/Media Alliance and publishing organizations likewise presented the statement as a collective response to unlicensed training rather than an objection limited to one artistic medium.
Why are creators objecting to AI training?
The signatories and their supporting organizations raise several connected concerns:
- Consent: A creator may not have agreed to have a book, photograph, recording, composition, performance or other work copied into training data.
- Compensation: Commercial AI systems can derive economic value from works that rights holders say were used without payment.
- Competition: Generated text, images, music, voices and performances may compete with human-made work or reduce demand for commissioned work.
- Attribution and control: Creators may not know whether a work was included in a dataset or how it influenced a model.
- Livelihoods and cultural production: The statement frames large-scale unlicensed use as a threat to the economic position of people whose work supports publishing, recording, journalism, film and other cultural industries.
These are the coalition’s concerns and policy arguments, not a finding that every AI system has produced the same economic effect or that every creator’s work was used in a particular model.
What does “unlicensed” mean?
Licensed training
A developer obtains permission or rights to use specified works, often through a contract, direct agreement or dataset license. The terms may address scope, payment, attribution, security and permitted uses.
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Unlicensed training
The developer uses material without obtaining permission from the relevant rights holder. The statement argues that commercial model developers should not treat online availability as blanket authorization.
Opt-out is different from permission
An opt-out system lets a creator request removal or exclusion after a service offers that mechanism. It is not the same as prior consent, a negotiated license or payment.
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware match“Unlicensed” also does not automatically mean “definitively illegal.” Whether copying for model training is permitted can depend on jurisdiction, the works involved, the purpose, the copying process and available exceptions such as fair use, fair dealing or text-and-data-mining rules. Public accessibility alone does not resolve those questions.
The legal and policy dispute
The letter appeared amid copyright lawsuits against AI developers and government debates about transparency, consent, licensing and creator protections. AI companies and their supporters have argued in some cases that training is transformative or otherwise covered by legal exceptions. Those arguments remain contested and fact-specific rather than a universal rule.
Training-data claims are also distinct from disputes about a model’s output. Whether a developer copied works during training is one question; whether a particular generated image, song, passage or voice infringes rights is another. Copyright ownership in a specific work is different again from attempts to imitate an artist’s general style, which is a more complicated and less clearly protected category.
The campaign’s broader purpose can be understood as shifting the debate from whether software can technically collect publicly accessible material to whether commercial developers should be required to obtain permission and pay for creative works used in training.
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What did publishers and other companies do?
Penguin Random House joined the coalition and said it opposed unauthorized use of copyrighted content to train generative-AI models. It also began adding a copyright-page notice stating that its books may not be used for AI training (Penguin Random House).
Such a notice records a publisher’s position and may support later contractual or legal arguments. It does not by itself prove that every AI system will comply, and it does not establish that every author’s individual contract contains identical language. Support from a trade group likewise does not prove that every member has the same policy.
Fairly Trained offers a separate certification model for AI companies that use licensed training data, according to its description at fairlytrained.org. That certification addresses the organization’s stated licensing criterion; it is not a general guarantee that a model is ethical, accurate or harmless.
How is this different from entertainment labor disputes?
SAG-AFTRA and other unions have negotiated protections involving AI-generated performances, digital replicas, consent and compensation. Those are employment and collective-bargaining issues. The open letter addressed training material across a much wider range of industries, including books, recordings, photographs, journalism and visual art.
The statement was therefore not a union strike action. A performer’s contract rights over a digital replica and a publisher’s objection to copying books into a training dataset may overlap politically, but they involve different legal relationships and remedies.
What did the letter change?
The statement had immediate political, reputational and coordinating force: it documented opposition from a large cross-section of the creative economy and gave regulators, publishers and AI companies a clear licensing demand. It did not ban AI training, order a company to remove data or resolve the underlying copyright disputes.
Its practical impact depends on what follows through contracts, licensing markets, dataset disclosure, legislation, litigation, certification and public pressure. Possible associated proposals include opt-in licensing, collective payment systems, enforceable opt-outs, training-data transparency, synthetic-content labeling and protections for voices and likenesses, but those were not all spelled out in the one-sentence statement.
The bottom line
The October 2024 letter showed broad creator and industry opposition to using creative works for generative-AI training without authorization. It made a strong policy claim—that such use should not be permitted—but it did not decide whether every instance is unlawful or force developers to change their practices. The unresolved questions are how permission, payment, transparency and liability should work in different countries and for different kinds of creative material.
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