Patrick Gallaher at Public Knowledge recently posted an article about AI training with protected works, proposing to distinguish between piracy and fair use. Not to begin on a pedantic note, but the article is subtitled “Words Matter” because it claims that piracy is a provocative, non-legal term, so I have to respond by saying this is wrong. Although we think of “piracy” today as enterprises like The Pirate Bay, courts have often used the term “piracy” to mean “copyright infringement.” For instance, the seminal fair use case Folsom v. March (1841) uses the word thirteen times as in this quote:
“….it is as clear, that if he thus cites the most important parts of the work, with a view, not to criticise, but to supersede the use of the original work, and substitute the review for it, such a use will be deemed in law a piracy.”
So, Gallaher is making a semantic fuss over nothing. If a contemporary court holds that AI training with protected works is copyright infringement, then this conduct may both legally and colloquially be called piracy.
As to the substance of the post, Gallaher asserts that AI training is inherently fair use, which is too broad a claim. The fair use doctrine defies generalization, and the facts in one case involving a particular AI and one type of work may have limited influence on the result of a case involving a different AI and different type of work. Or to put that another way, the incomplete fair use inquiry conducted in Bartz v. Anthropic, involving a class of literary works, likely predicts almost nothing about the eventual outcome in UMG et al. v. Udio or Disney et al. v. Midjourney, involving sound recordings and visual works respectively.
Gallaher states that AI training is transformative under fair use factor one (the purpose of the use). Indeed many articles of this nature rely on the assumption that this finding should be obvious and should carry the weight of the fair use analysis. “Copying for training is transformative: it uses the works for a fundamentally different purpose from the original, much like indexing websites for search engines or scanning books for text analysis,” he writes. And that’s all he writes about one of the most vexing doctrines in fair use weighing the most challenging technology ever confronted by copyright law.
Of course, even in one sentence, Gallaher manages to hide (or expose) the distinction that the purpose of many GAI products is to produce works without authors. This fact is highly distinguishable from the two analogies he cites and, as the courts will surely recognize, presents a novel challenge to the constitutional intent of copyright law. This is a consistent fallacy with every article of this nature—claiming that AI is the most revolutionary tech in history, but despite this novelty, we have ample case law to conclude that training is fair use.
Perhaps the courts will not wholly agree with my view that a purpose which does not serve the goals of copyright cannot favor fair use, but in Kadrey v. Meta, Judge Chhabria stated, “Courts can’t stick their heads in the sand to an obvious way that a new technology might severely harm the incentive to create, just because the issue has not come up before.”
Although that sentence prefaces a consideration of market dilution under factor four, the words “harm the incentive to create” allude directly to copyright’s core purpose and, so, implicates the purpose of the GAI to “create” in lieu of authors. And that goes to the question of transformativeness. So, no, it is not enough to say that a use which serves a different purpose is per se transformative, especially when that different purpose is to do exactly what creators do and, in the process, moot the utility of copyright law.
Notably, Gallaher masks the substitutional purpose of GAI by referring to it in general as technology that serves a “public good” and which provides “broad benefits.” The plain fact, though, is that we do not know this to be true. Simply because a product is new, being widely adopted, and/or has investors chomping at the bit is not evidence that its purpose is categorically beneficial. Far from it. We are already flooded with AI products causing serious harm, triggering liability claims for negligence and wrongful death, and launching emotional Senate hearings.
In this regard, I have argued that the courts have no factual basis for even defining the purpose of AI training. Although we should not talk about AI as a monolith, the counterpoint to that principle is that it’s generally the same process ingesting the same creative works, whether the AI product is used for scientific research, military applications, medical diagnosis, CSAM, social engineering attacks, or addicting children to establish dangerous “friendships” with machines.
Even if the courts are unwilling to apply such a broad sweep of uncertainty in a copyright context, it is sufficient to say that we have little reason to assume that AI is generally beneficial in the world of creative and cultural production. And whether the folks at Public Knowledge know it, the courts are at liberty to look beyond the four factors in weighing fair use, especially when they are presented with considerations that have little or no precedent.
It is important to keep in mind that on fair use factor one, the often unwieldy transformative doctrine splits into two distinct branches of case law. The traditional purpose of fair use, dating back to English courts, is to allow new creative expression to flourish, particularly expression that comments upon the work being used. Fair use cases of this nature most often address one user of one work for one clear purpose.
The more contemporary branch of factor one considerations entails mass use of protected works for a technological purpose that can strain against the fair use doctrine. Simply put, fair use was not developed or codified into statute to provide raw materials for technological products, and as discussed in other posts, when the Second Circuit allowed scanning millions of books for Google Books, it stated that the case “tests the boundaries of fair use.” GAI products, whether used for good or ill, lie well outside those boundaries.
Articles like Gallaher’s are not really making a copyright argument but are instead drawing readers to conclude that copyright owners should be required to subsidize AI development whether they like it or not. Other than assuming that Public Knowledge is still a PR firm for Big Tech, I don’t know why an organization with that name takes such a position when countless parents, educators, artists, lawmakers, and medical experts are insisting upon guardrails and oversight for AI in recognition of social harm already being done. This same sober approach must apply to copyright rights and, at the very least, foster a licensing regime that avoids undermining foundational IP principles.
Image source: H9images
