{"id":38125,"date":"2025-07-14T16:03:57","date_gmt":"2025-07-14T16:03:57","guid":{"rendered":"https:\/\/publicknowledge.org\/?p=38125"},"modified":"2025-07-14T16:04:01","modified_gmt":"2025-07-14T16:04:01","slug":"the-fatal-failures-of-the-copyright-offices-report-on-ai","status":"publish","type":"post","link":"https:\/\/publicknowledge.org\/the-fatal-failures-of-the-copyright-offices-report-on-ai\/","title":{"rendered":"The Fatal Failures of the Copyright Office\u2019s Report on AI"},"content":{"rendered":"\n

Back in 2023, the U.S. Copyright Office was given the unenviable task of advising Congress on whether using copyrighted works to train artificial intelligence was a fair use. It took them nearly two years and a Librarian of Congress, but in May 2025, the Office released the long-awaited third installment of the report<\/a>. <\/p>\n\n\n\n

Its top-line conclusions were generally correct: Copyright law is extremely robust, with decades of relevant case law behind it, and is actually quite well-equipped to deal with the question of training on copyrighted works. Fair use is a case-by-case analysis, and the outcome will depend largely on the specific facts of each case. Congress should wait for the courts to suss out these questions, and see whether licensing markets develop organically in the meantime. If they don\u2019t develop, or take an anticompetitive turn, then Congress should consider a kind of mass licensing known as \u201cextended collective licensing<\/a>.\u201d The Report also contained an extremely useful (and accurate) description of the training process, including unique use cases such as \u201cretrieval-augmented generation\u201d (or RAG) models, which search for answers in real time to user queries. <\/p>\n\n\n\n

But the reasoning the Office used to arrive at those conclusions is largely a mess. Three missteps in particular undermine the Office\u2019s analysis: endorsing an unsupported theory of market dilution; making up a nonexistent right for rightsholders to control the manner in which their works are accessed; and sloppily applying the recent Warhol <\/em>decision to a general-purpose technology.<\/p>\n\n\n\n

Market Dilution Is Not A Thing<\/strong><\/h2>\n\n\n\n

Probably the most-discussed failure of the Report is the Copyright Office\u2019s decision to endorse a brand new, fringe theory of market harm: that the existence of too much creative work is bad. This stems from a recurring fear of rightsholders that AI-generated works will flood the market in a way that will disadvantage human-created works and drive down their value.<\/p>\n\n\n\n

This theory, known as \u201cmarket dilution,\u201d is based on a tortured reading of the fourth factor<\/a>. Although the Office \u201cacknowledge[s] this is uncharted territory,\u201d it nevertheless argues that \u201cany<\/em> effect upon the potential market\u201d for a copyrighted work \u2013 up to and including the introduction of competing works \u2013 can weigh against fair use. This becomes doubly tortured when applied to situations where the work being \u201cdisadvantaged\u201d was used solely to train the person or tool being used to assist in the creation of a new, competing work. Under \u201cmarket dilution\u201d theory, copyright stops being about copies and starts being about competition, because humans learn from existing works before creating their own. Assigning novels to a college creative writing class? If any of those student works ends up getting published, that\u2019s a new work competing against the books the students read in class; that\u2019s market dilution. DSLR or digital single-lens reflex cameras, which allow everyday users to take professional-looking photos that they can license to news organizations? Market dilution. Recording your own music with GarageBand and releasing it online? Market dilution, and you can expect a call from the RIAA (once they\u2019re done suing your internet service provider<\/a>). <\/p>\n\n\n\n

Copyright law doesn\u2019t protect creators from the threat of too much<\/em> competition, machine-made or otherwise. If there\u2019s a thru-line at all in the history of copyright policy, it\u2019s that technology allows for more works, by more people, with less friction. Everything from word processing to Photoshop has led to explosions in the number of works being created \u2013 and licensed. Copyright law does not protect a right to be free of competitive market pressure; it simply protects the right to control (some) uses of your specific work. As Professor Edward Lee puts it<\/a>, market dilution theory \u201cturns copyright from a limited monopoly to a general monopoly against competition posed by noninfringing works.\u201d And, if that\u2019s not enough to convince you, the U.S Supreme Court also had a few things to say<\/a>, namely that \u201cCreative works can compete with other creative works for the same market, even if their appeal is overlapping,\u201d and \u201cNo presumption or inference of market harm \u2026 is applicable to a case involving something beyond mere duplication for commercial purposes.\u201d <\/p>\n\n\n\n

In short, if you want to address the market threat to creative labor, copyright law isn\u2019t the avenue to do it.<\/p>\n\n\n\n

Publishers Do Not Have an Absolute Right To Control the Means of Access<\/strong><\/h2>\n\n\n\n

Another nonsense assertion in the report is the idea that whether or not a source work was initially accessed<\/em> with the copyright owner\u2019s permission has a bearing on whether or not the use is fair. For one thing, this is self-defeating logic; if you had obtained the rightsholder\u2019s permission, you wouldn\u2019t have to be in court arguing that your use was fair. Rightsholders take this argument a step further, saying that any training data obtained via \u201cunlawful access\u201d poisons the entire model. <\/p>\n\n\n\n

It\u2019s a nonsense argument, but it\u2019s worth unpacking what that means in the context of digital media. Training sets are digital; any material included in the set needs to either be converted from analog to digital (say by scanning), or obtained in a native digital format. While methods vary \u2013 Anthropic used a combination of book-scanning and scraped digital sources<\/a> \u2013 most developers are naturally going to want things in a digital-first format. <\/p>\n\n\n\n

Accessing these works, however, requires users to agree to a minefield of contracts. These contracts frequently contain clauses that (purport to) bar users from making legally allowable fair uses of the works they\u2019re accessing. And even if there\u2019s no contract, there\u2019s likely to be a digital access lock, which starkly limits what you can do with the file \u2013 even if all you want to do is make a fair use. Under the rightsholder view of the world, there is no \u201clawful access\u201d of a digital work that isn\u2019t entirely on their terms. <\/p>\n\n\n\n

Luckily, that\u2019s not how the law works. The \u201cDigital Millennium Copyright Act\u201d or DMCA explicitly allows for unlawful access <\/em>by circumventing digital locks<\/a> if the purpose is to make an approved fair use. \u201cLawful access\u201d as a factor in fair use is not backed up by statute or the case law, and judges have thrown it out both times it was argued in recent AI copyright cases; in both Kadrey v. Meta<\/em> and Bartz v. Anthropic<\/em>,<\/a> the court held that even using pirated material that was infringing to save or redistribute on its own did not necessarily make the training itself inherently unfair. <\/p>\n\n\n\n

Warhol (Derogatory)<\/strong><\/h2>\n\n\n\n

All of this is further complicated by a longstanding problem in fair use: What, exactly, is the \u201cuse\u201d the courts are supposed to be evaluating? <\/p>\n\n\n\n

Let\u2019s use a hypothetical. Say you\u2019re a collage artist; you cut out images from magazines and incorporate them into your work. The resulting piece is a large, 3\u2019 x 5\u2019 poster, which you license to your favorite band as album cover art. What is the relevant \u201cuse\u201d in this case? Is it the act of incorporating that picture into the resulting collage? Is it the act of licensing the collage as cover art? Or is \u201cfair use\u201d a status held by the work itself, that then travels with it regardless of what the artist does later down the line?  <\/p>\n\n\n\n

In its recent Warhol v. Goldsmith <\/em>decision, the Supreme Court faced a version of this problem \u2013 what is the relevant \u201cuse,\u201d and once that\u2019s defined, how do we assess its fairness? In 1981, photographer Lynn Goldsmith photographed singer-songwriter Prince, then an up-and-coming artist. In 1984, Vanity Fair licensed that photograph and commissioned Andy Warhol to turn it into a silk screen print. Warhol made the one print allowed by the license, but he liked the photograph so much that, over the remaining three years of his life (1984-87), he made another fifteen for his personal collection. He died in 1987, and his estate displayed the Prince Series <\/em>in galleries around the world. In 2016 \u2013 nearly four decades after his death \u2013 his estate then licensed one of the unlicensed prints back to Vanity Fair as a cover image for a special retrospective issue. Goldsmith, who had for nearly four decades been unaware of the existence of the other 15 prints, sued. <\/p>\n\n\n\n

The Court ultimately decided that commercial use of the work (by a separate party, four decades after its creation!) retroactively<\/em> rendered the prints themselves less transformative. The Court, through this miracle of judicial time travel, created a \u201cSchr\u00f6edinger\u2019s cat\u201d of fairness; whether or not a work itself is transformative may depend wholly on what the artist (or someone else!) chooses to do with it commercially at a later, unknown date. This is like saying that my cat is now a fish because I gave him a bath<\/em>. <\/p>\n\n\n\n

The only way this line of argument \u2013 commerciality can change how inherently transformative a use is \u2013 makes any logical sense is if you assume that the creator, when she sat down to make the secondary work, had commercial intent. <\/em>Something made for the purpose <\/em>of commercial use is less transformative; something made for the purpose <\/em>of educational use may be more transformative. If the work is commercialized by its artist later, that speaks to the artist\u2019s intent at the time of creation. <\/p>\n\n\n\n

The idea that the actions of Warhol\u2019s estate evidenced that Warhol himself had \u201ccommercial intent\u201d only works thanks to the legal fiction that an estate acts, for all intents and purposes, as the deceased individual himself. Andy Warhol made the unauthorized prints, and \u201cAndy Warhol\u201d licensed them to Vanity Fair in 2016. But this principle starts breaking down rapidly when you try to apply it to something with as many intervening actors as AI. <\/p>\n\n\n\n

How Does This Affect AI?<\/strong><\/h2>\n\n\n\n

AI is a general-purpose technology. It can be used (and marketed) for any number of ends that are fundamentally beyond the decision power of the original developer. The initial training, fine tuning, and end use can, and often is, done by entirely different people and organizations. The whole point<\/em> of most AI models is to be able to re-implement and repurpose what\u2019s been trained for new, custom ends. Meta\u2019s Llama model is a great example: it\u2019s an open-source large language model that has been fine-tuned and reshaped for everything from identifying biomarkers in cancerous tumors<\/a> to helping conservators analyze centuries-old artworks and strategize how to best preserve them.<\/a><\/p>\n\n\n\n

The Copyright Office report largely discarded this fact, and instead attempted to apply Warhol<\/em>\u2019s reasoning as if the entire process, from training to output prompting, was under conscious control of the same entity. There are cases where this might make sense: systems developed entirely for in-house use, or agentic systems explicitly marketed as digital replacements for human workers. But when that decision-making chain breaks, so does the Report\u2019s logic. A model or its components may pass through control of multiple entities. Does the fact that an end user decides to use a re-implemented model in a way that competes with something in the training set retroactively render that training not <\/em>a fair use? If the training itself was not fair, then is it unfair as applied to all <\/em>subsequent implementations? Does the cancer biomarker detector model now violate copyright law? <\/p>\n\n\n\n

The Copyright Office\u2019s sloppy assumption of singular decision-making results in a vision of fair use where training exists inside that Schr\u00f6edinger\u2019s box, both fair and unfair, depending on whether someone out there in the universe decides to point the model toward an unauthorized end. <\/p>\n\n\n\n

Practical Impacts<\/strong><\/h2>\n\n\n\n

So far, the Report has had little to no impact on the political (or legal) trajectory of AI disputes. First, because the Report was rushed out the door when it became clear President Trump was preparing to fire the Register of Copyrights<\/a>, it is only available in a \u201cpre-publication version.\u201d Given that the Office still lacks an acting Register \u2013 and the administration appears to have turned its attention elsewhere \u2013 it will likely be a while before we see a formal, finalized version\u2026 or the rest of the reports that the Office is scheduled to release in its AI and Copyright series.<\/p>\n\n\n\n

Second, the court decisions that have happened since the Report\u2019s release have completely ignored it. A report from the Copyright Office doesn\u2019t have any binding legal weight; in lawyer speak, it\u2019s considered persuasive, but not entitled to any special deference. (It\u2019s unclear what impact, if any, the Report\u2019s \u201cpre-publication\u201d status has on its persuasiveness.) <\/p>\n\n\n\n

Finally, the Report was almost immediately superseded by the American Law Institute\u2019s issuance of the long-awaited Restatement of Copyrights<\/a>. ALI Restatements are summaries of complex areas of law, designed to bring unfamiliar judges up to speed in areas with which they have no experience. The Restatement was a monumental effort, and its (much more even-handed) treatment of fair use is going to be much closer to hand and more readily consulted by judges than the Copyright Office\u2019s pre-publication report. <\/p>\n\n\n\n

Conclusion<\/strong><\/h2>\n\n\n\n

The Copyright Office\u2019s report was an ambitious but flawed attempt to provide categorical answers to fact-specific questions. In doing so, the Office dangled some crazy bait  \u2013 but mercifully, the courts don\u2019t seem to be biting.<\/p>\n","protected":false},"excerpt":{"rendered":"

At long last, the Copyright Office released its third report on fair use and AI \u2014 but their analysis contained serious missteps.<\/p>\n","protected":false},"author":117,"featured_media":37377,"parent":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[5],"tags":[12,29],"class_list":["post-38125","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-insights","tag-copyright-reform","tag-trustworthy-ai"],"acf":[],"yoast_head":"\nThe Fatal Failures of the Copyright Office\u2019s Report on AI - Public Knowledge<\/title>\n<meta name=\"description\" content=\"At long last, the Copyright Office released its third report on fair use and AI \u2014 but their analysis contained serious missteps.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/publicknowledge.org\/the-fatal-failures-of-the-copyright-offices-report-on-ai\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The Fatal Failures of the Copyright Office\u2019s Report on AI\" \/>\n<meta property=\"og:description\" content=\"At long last, the Copyright Office released its third report on fair use and AI \u2014 but their analysis contained serious missteps.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/publicknowledge.org\/the-fatal-failures-of-the-copyright-offices-report-on-ai\/\" \/>\n<meta property=\"og:site_name\" content=\"Public Knowledge\" \/>\n<meta property=\"article:published_time\" content=\"2025-07-14T16:03:57+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-07-14T16:04:01+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/publicknowledge.org\/wp-content\/uploads\/2024\/10\/Copyright-1440x720.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1440\" \/>\n\t<meta property=\"og:image:height\" content=\"720\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Meredith Filak Rose\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Meredith Filak Rose\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"10 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/publicknowledge.org\/the-fatal-failures-of-the-copyright-offices-report-on-ai\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/publicknowledge.org\/the-fatal-failures-of-the-copyright-offices-report-on-ai\/\"},\"author\":{\"name\":\"Meredith Filak Rose\",\"@id\":\"https:\/\/publicknowledge.org\/#\/schema\/person\/cb2c92f558c63e83a5ef351b4a5855b0\"},\"headline\":\"The Fatal Failures of the Copyright Office\u2019s Report on AI\",\"datePublished\":\"2025-07-14T16:03:57+00:00\",\"dateModified\":\"2025-07-14T16:04:01+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/publicknowledge.org\/the-fatal-failures-of-the-copyright-offices-report-on-ai\/\"},\"wordCount\":2225,\"publisher\":{\"@id\":\"https:\/\/publicknowledge.org\/#organization\"},\"image\":{\"@id\":\"https:\/\/publicknowledge.org\/the-fatal-failures-of-the-copyright-offices-report-on-ai\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/publicknowledge.org\/wp-content\/uploads\/2024\/10\/Copyright.png\",\"keywords\":[\"Copyright Reform\",\"Trustworthy AI\"],\"articleSection\":[\"Insights\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/publicknowledge.org\/the-fatal-failures-of-the-copyright-offices-report-on-ai\/\",\"url\":\"https:\/\/publicknowledge.org\/the-fatal-failures-of-the-copyright-offices-report-on-ai\/\",\"name\":\"The Fatal Failures of the Copyright Office\u2019s Report on AI - 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