Category Archives: Fair Use

China’s Controversial Court Rulings on AI Output—and How It May Affect People in the US

Posted April 3, 2025
these AI-generated images were found to be copyrightable by courts in China

The copyrightability of AI-generated works is a hotly debated issue. We recently blogged about the first US appellate court decision on the copyrightability of AI-generated works. In Part I of this blog post, we examine the five decisions handed down by Chinese courts so far on the copyrightability question over AI-generated works. 

We believe ours is the first attempt to examine these five cases together. These copyrightability cases, individually, are receiving lots of attention in Chinese media. The general public in China has very pro-copyright and pro-enforcement sentiment nowadays. This may explain why courts have issued decisions that largely sided with the creators of AI-generated works; according to some judges in China, their job is to issue rulings that fit with the expectations of the plaintiff, the defendant, and the public.

These AI copyrightability cases are barely ever discussed together as congruent jurisprudence, because, like with most legal questions, courts in China rarely need to pay attention to precedents. Only since 2010 are courts in China required to follow certain Supreme People’s Court’s decisions. None of the cases discussed below are precedential. 

These decisions, then, are just one-off incidents—barely impactful in terms of damages born by the defendants or precedential effects for future cases to be decided in China. The deadline for appeal has long passed for all five cases, and the decisions are final for the parties involved. But for people in the US, one big question is whether these Chinese courts’ non-precedential decisions could potentially be upheld and enforced by US courts. We consider this question in Part II, below.

Part I, Chinese Courts’ Copyrightability Holdings 

China’s judicial system seems to be moving really fast. While most countries are still slowly working toward articulating their stance on AI-generated works, courts in China have already released multiple opinions addressing AI, both in terms of training and copyrightability of AI output. Researching these cases is challenging, however, because there is no single unified database for court opinions in China. 

In Beijing Feilin Law v. Baidu, the Beijing IP Court issued an appellate decision in 2020 partially upholding and partially overturning the lower Beijing Internet Court’s 2019 decision. Many refer to this case as the first case in China dealing with computer-generated works, because part of the dispute was centered on whether some computer-generated charts were copyrightable. In reaching the decision that the computer-generated charts are not copyrightable, the appellate court reasoned:

Although there are differences in the graphics, shapes, and the data represented, these differences resulted from choices in data selection, software, or graphics. The graphics used are common shapes in data analysis like bar charts, pie charts, and line graphs, which do not reflect the originality of Feilin Law Firm’s expressions. While Feilin Law Firm claims to have manually enhanced the lines and colors of these graphics, no evidence has been provided to support this assertion.

The court still managed to award Feiling Law Firm damages based on the right of integrity, because when Baidu reposted Feilin’s article, Baidu deleted more than 20% of the article. The damages awarded was 1,000 rmb plus 560 rmb in reasonable fees (totaling about $216 USD—peanuts to Baidu, which is valued at $34.5 billion USD). Overall, because the court refused copyright to the computer-generated charts, we are tempted to infer that human authorship is necessary for a computer-generated work to be copyrightable in China, very similar to the rule in the US. 

At first glance, a second case, Tencent v. Shanghai Yingxun, confirms the assumption that human authorship is necessary for copyright protection for AI-generated works in China. However, the ruling is not entirely straightforward once we examine more closely the court’s reasoning on what constitutes the original human authorship needed for copyright protection:

The article was created through (1) data training, (2) prompting and article generation, (3) AI-enabled editing and (4) AI-enabled publication. In this process, the Plaintiff’s team members had to make selection and determination on the cleaning and inputting of data, prompt engineering, the selection of article template and language corpus, and the training of the editor function. The key difference between the creative process in this case and what we commonly see with other human creative processes is that the original human choices are made prior to when the article was written in terms of what data to use, what theme to focus on, and what style and tone to adopt.  This court holds that such asynchronicity is caused by the technology. … If we consider the two-minutes it took for the article to be generated to be the entire creative process, then no human authorship was involved; however, Plaintiff determined how the program was run, and the article was generated in a way that was determined by both how Plaintiff intended that program to work and how the program functions based on its technical characteristics. If we see the two-minutes it took to generate the article as the creative process, we are in effect taking the machine to be the author of the article, which does not match our understanding of reality or justice. … We do not need to investigate if the originality of the article stems from the contributions by the program’s developer, because the developer has already agreed in a contract that the Plaintiff holds copyright to anything created by the program.

This case resulted in 1,775 rmb (around $245 USD) fees and damages awarded against the Defendant; the impact is minimal on the parties directly involved. Even though the opinion affirmed the necessity of human authorship, the reasoning behind it is in direct opposition to the US Copyright Office’s position on the lack of copyrightability for AI-generated works. Whereas a consensus is forming in the US that AI outputs are beyond the controls of humans, that prompt engineering does not lead to foreseeable outputs, and that AI-generated works are categorically uncopyrightable, China seems to be leaning towards an unsustainable position that any human input at all during the prompting stage could lend copyright protection to an unpredictable AI output. 

In late 2023, for the first time ever in the world, a court got to determine whether a user owns copyright to an entirely AI-generated image in the case of Li Yunkai v. Liu Yuanchun. The Plaintiff in this case was a lawyer by profession; he also created visual art using text-to-image generative AI on the side. The Beijing Internet Court reasoned:

As to whether images generated using artificial intelligence reflect the author’s individualized expressions, it requires case-by-case determination. Generally speaking, when people use models like Stable Diffusion to generate images, the more their requests differ from other users and the more specific and clear the descriptions for the image and composition, the more the author’s individualized expressions will be reflected in the final image. In this case, the image exhibits identifiable differences from prior works. On the one hand, the plaintiff did not personally draw the lines or even fully instruct the Stable Diffusion model on how to draw particular lines and colors, it can be said that the lines and colors that form the images were essentially “drawn” by the Stable Diffusion model, which is quite different from how people traditionally use brushes or drawing software. However, the plaintiff designed the female character and its presentation via prompts, and set the layout and composition by changing image parameters, reflecting the plaintiff’s choices and arrangements. On the other hand, after obtaining the first image by initially inputting prompt words and setting related parameters, the plaintiff continued to add prompt words and modify parameters, continually adjusting and correcting the image until the final image was achieved. This adjustment and correction process reflected the plaintiff’s aesthetic choices and personal judgment.

Essentially, the court granted copyright to AI output based on prompt engineering alone. The Defendant was ordered to pay the Plaintiff 500 rmb (around $69 USD) for removing the copyright notice as well as distributing the infringing image online without permission. The Plaintiff accepted the court’s holding, but refused to take any money from the Defendant, saying money was not what he was seeking. The decision is criticized by some Chinese scholars for granting copyright to wholly AI-generated images, potentially leading to an oversaturation of AI-generated images, further marginalizing human authors. There remain strong proponents in China that advocate for a bright line rule—that AI-generated images are never copyrightable.

With the previous two cases in mind, it should not come as a surprise that, in 2024, the Plaintiff in Lin Chen v. Hangzhou Gaosi Membrane Technology was able to assert his copyright in an AI-generated image when he used both Midjourney and Photoshop to manipulate the image. The court examined the contract terms between Midjourney and Plaintiff, as well as looked at the prompt-author’s activity log and creative process, before reaching the conclusion that the AI output was copyrightable. The court reasoned that the work was copyrightable because the Plaintiff had creative control over the output and the output embodied the author’s intended original expressions, and socially-speaking, allowing prompt-authors to be copyright holders to their AI output would encourage more creative activities that utilized AI. The key facts related to the creative process are as follows:

The plaintiff began designing the image using Midjourney GAI. Initially, Plaintiff entered the following prompts: “On the Huangpu River” “at night” “there is a string of large and small hearts” “floating in the water” “lights” “advanced” “reflection” “details” “ realistic” “4k ” “no people” “High environment/Canon E0S 5Diii” and Midjourney generated four images with heart-shaped balloon.  The Plaintiff continued to engineer prompts, such as inputting “there are multiple red love balloons”“there is a huge red love balloon” “lying on the water” “half soaked in water” “rose petals composed of love” “only half of the surface of the water” to manipulate the size, number, shape, and position of the balloons. When the output was unsatisfactory, the Plaintiff took the image to Photoshop, changing the shape of the balloon, and reimported the resulting image back into Midjourney for further tweaking. After that, the Plaintiff took the image to Photoshop once again before finalizing the design on 2023/2/14 at 23:40.

In this case, beyond copyright infringement through unauthorized distribution, the removal of copyright notice was also found to be infringing on the Plaintiff’s right to integrity. The Defendant was ordered to pay 1,000 rmb in damages and 9,000rmb in reasonable fees (totalling around $1383 USD). Interestingly, the Defendant was only held liable for reposting the image, but not found infringing for creating a 3D submerged-heart statue based on the infringing 2D image. Some people—including the Plaintiff—argue that this result is only due to mistakes made in the copyright registration process, that the Plaintiff failed to register 3D rendition of his 2D design. Although, a more compelling reading of the opinion would be that copyright for a half-heart design is thin, and people are free to make different renditions based on the same half-submerged heart idea.

Similar to the reasoning provided in the Li Yunkai case, this February, the court in Wang v Wuhan Technology Company (The link takes you to the court’s official report; full opinion for this case could not be found as of 3/20/2025) determined that the Plaintiff’s AI-generated work was entitled to copyright protection because the Plaintiff could foresee and control the resulting image to a certain extent, and the prompts Plaintiff inputted into the AI system embodied his unique human expressions which directly correlated to the final AI-generated image. Defendant was ordered to pay 4,000 rmb (around $553 USD) for their infringement. 

As we mentioned at the beginning, these cases are not precedential in China, despite being final. If the general societal sentiment in China continues to lean towards AI-artists receiving copyright protection for their works, any new rulings would likely come out similarly—granting copyright to AI-generated works. Until inevitably, the Chinese courts must re-examine their flawed reasoning, when stockpiling happens, when AI companies stop assigning “copyright” to users of their AI models, when human authors start to lose jobs en masse, and when the judges can’t figure out if an AI-artist should be held liable for a copyright-infringing AI-generated image when all the artist has done was providing some simple text-prompts.

Part II, Will US Courts Grant Copyright Protection to Foreign AI Works?

Looking beyond China, the UK, Ireland, South Africa and Ukraine all have adopted laws that specifically grant copyright to computer-generated works. In this part, we discuss whether copyright granted in foreign jurisdictions will be upheld by US courts.

the 9th Circuit did not challenge the French court’s decision that the photo on the right had a copyright separate from the elements taken from Picasso’s original image on the left

There are two main questions US courts may need to consider regarding foreign AI-generated works: (1) whether to apply foreign law to determine the copyrightability of foreign AI-generated works, and (2) whether to enforce foreign judgments that upheld AI-generated work as copyrightable and unlicensed use infringing. 

First, will US courts defer to foreign law when determining whether AI-generated work created in a foreign jurisdiction is copyrightable? We think it unlikely.

The issue raises what is known as a “choice of law” question. The answer in the copyright context depends on how US law incorporates obligations under international treaties such as the Berne Convention, as well as common law principles that are more generally applicable. Itar-Tass Russian News Agency v. Russian Kurier, Inc. (2d Cir. 1998) is among the most cited cases to decide this issue under the current Copyright Act. In Itar-Tass, when deciding whether to apply US law or foreign law, the court distinguished between the question of copyright ownership and the question of copyright infringement. For copyright ownership of a foreign work, the Second Circuit applied foreign law. 

For infringement issues, Itar-Tass states that “the governing conflicts principle is usually lex loci delicti. . . . We have implicitly adopted that approach to infringement claims, applying United States copyright law to a work that was unprotected in its country of origin.” (citing to Hasbro Bradley, Inc. v. Sparkle Toys, Inc., (2d Cir.1985). The distinction between ownership and infringement is not arbitrary. The infringement question addresses the scope of copyright protection, whereas the ownership question addresses who gets to enjoy that protection. It is well established that the US does not grant additional protection to foreign works compared to US works: for example, in the US, a foreign copyright holder would not be able to point to foreign laws to request moral rights for his work (see Fahmy v. Jay-Z (9th Cir. 2018)).

Because the United States has joined the Berne Convention and implemented it in US Copyright Law, U.S. courts must give the same protection to foreign works as to US works, and this deference to foreign copyright includes a presumption of the foreign copyrights’ validity. However, the presumption of validity is different from a copyright being in fact valid under US copyright law: a defendant can always challenge a registered, presumptively valid, copyright. As discussed in Unicolors, Inc. v. H&M Hennes & Mauritz, L.P. (9th Cir. 2022), “[equal treatment] simply means that foreign copyright holders are subject to the same U.S. copyright law analysis as domestic copyright holders… [I]t does not mean we can change the rules of the game simply because foreign copyright law is implicated.” Whether an AI-generated work is copyrightable similarly would have to be equally subject to review under US copyright law, regardless of whether it was created in the US or a foreign jurisdiction.

Many cases have followed this principle that US law will be applied when determining questions of originality and copyrightability. In Molnarova v. Swamp Witches (S.D. OH 2023), a case brought by Slovakian artists, the district court explained “Although [Plaintiff] is correct in asserting that Slovakia law applies to the question whether she owns a copyright in the Tumblerone, the question of who owns a copyright is distinct from what protection that copyright provides. The latter is governed by United States law, more specifically the Copyright Act. In other words, even if Slovakia offers copyright protections to the Tumblerone as alleged by Plaintiff, she must still show that the Tumblerone is protectable under United States copyright law.” (citing to a series of other cases in agreement.) 

One notable outlier to this rule is TeamLab v. Museum of Dream Space (C.D. CA 2023), where the court applied Japanese law in deciding whether the works in question were copyrightable. The TeamLab court essentially only required valid copyrights in Japan for the works to automatically enjoy copyright protection in the US. Because the works were “creatively produced expressions” eligible for copyright in Japan, the court accepted the works as protected by valid copyrights in the US as well, without explicitly scrutinizing the works under US law. The Teamlab court’s confusion likely arose out of the court’s conviction that applying US law would have led it to the same conclusion (—e.g., with language like “in both Japanese and U.S. copyright law, a work need not be novel to be original” and “Under both Japanese and U.S. law, Plaintiff retains a copyright”). 

Even if a court were to follow Teamlab and apply foreign law on the question of copyrightability, a US court may still very likely interpret Chinese law to grant no copyright to AI-generated works. On paper at least, China only grants copyright to “fruits of intelligence” (Art. III, Copyright Act) which so far has been interpreted to mean human intelligence and human authorship. Especially when so many Chinese legal scholars do not believe AI-generated works contain enough “human intelligence” to warrant copyright, it is likely a US court will determine AI-generated works are uncopyrightable under Chinese copyright law. In any case, defendants in US courts would almost always want to challenge the validity of copyrights given to AI-generated works.

Let’s now move on to the second question: Will plaintiffs be able to enforce foreign copyright judgments in the US? We believe there’s a possibility that opinions issued by foreign courts granting AI-generated works copyright protection will be enforceable in the US, but jurisprudence seems unsettled in this area. 

We have written about one case addressing this issue before: when the Plaintiff in Sicre de Fontbrune v. Wofsy (9th Cir. 2016) sought to enforce a foreign judgment on copyright infringement, the Ninth Circuit did not second guess the French court’s decision on copyrightability, even though the work at issue was a faithful 2D scan of an existing work, lacking originality and thus uncopyrightable under US law. The defendant did not request the Ninth Circuit to reexamine the copyrightability issue. Had the defendant raised the argument that the photograph in question did not meet the originality requirement under French law—or under US law, maybe the Ninth Circuit would have done its own copyrightability analysis. We cannot be sure how the case would have played out had the question been raised.

In a similar case brought to the Second Circuit, SARL Louis Feraud Int’l v. Viewfinder (2nd Cir. 2007), the circuit court explained that courts rarely refuse to enforce foreign judgments unless they are “inherently vicious, wicked or immoral, and shocking to the prevailing moral sense.” The circuit court reasoned that “if the sole reason that Viewfinder’s conduct would be permitted under United States copyright law is that plaintiffs’ dress designs are not copyrightable in the United States, the French Judgment would not appear to be repugnant. However, without further development of the record, we cannot reach any conclusions as to whether Viewfinder’s conduct would fall within the protection of the fair use doctrine.” 

Essentially, the circuit court made the distinction between copyright protection (which is an economic right fabricated by Congress that does not implicate morality or public policy) and fair use, which is an embodiment of a First Amendment right that represents strong public policy concerns. When SARL was remanded to the district court, the French judgment was not enforced. In reaching its decision to not enforce the foreign judgment, the district court did not address the copyrightability issue (that fashion design is uncopyrightable in the US), but entirely based its decision on a fair use analysis rooted in US copyright law, in accordance with the circuit court’s instructions. 

Notably, the circuit court in SARL referred to the relevant state statute, N.Y. C.P.L.R. § 5304(b)(4) (and New York’s adoption of the Uniform Foreign-Country Money Judgments Recognition Act) as the basis for its decision. There is no federal law regulating the enforcement of foreign judgments, and the US is not a party to any international treaty that requires US courts to enforce foreign judgments. (Compare the situation to how the Berne Convention obligates US courts to provide copyright protection to foreign works.) Most states have similar laws about enforcement of foreign monetary judgements, though there are some important differences. Depending on the applicable state laws, US courts can sometimes substantively review foreign judgments, like when the SARL court relied on fair use under US law. A defendant should have a fair use defense ready if a US court is considering enforcing a foreign copyright infringement ruling.

Even if courts were to enforce the opinions issued by Chinese courts, the good news is that Chinese courts typically award limited damages to the plaintiffs (because AI works are cheap to generate). Also important to remember is that foreign courts only address infringing acts in their jurisdictions, so this is not an issue for parties without an overseas presence. US courts also take procedural due process into account when deciding whether to enforce a foreign judgment; it would be farfetched to worry that US courts will enforce foreign judgments entered against entirely unsuspecting US defendants.

Updates on AI Copyright Law and Policy: Section 1202 of the DMCA,  Doe v. Github, and the UK Copyright and AI Consultation 

Posted March 7, 2025
some district courts have applied DMCA 1202(b) to physical copies, including textile, which means if you cut off parts of a fabric that contain copyright information, you could be liable for up to $25,000 in damages

The US Copyright Act has never been praised for its clarity or its intuitive simplicity—at a whopping 460 pages long, it is filled with hotly debated ambiguities and overly complex provisions. The copyright laws of most other jurisdictions aren’t much better.

Because of this complexity of copyright law, the implications of changes to copyright law and policy are not always clear to most authors. As we’ve said in the past, many of these issues seem arcane, and largely escape public attention. Yet entities with a vested interest in maximalist copyright—often at odds with the public interest—are certainly paying attention, and often claim to speak for all authors when they in fact represent only a small subset.  As part of our efforts to advocate for a future where copyright law offers ample clarity, certainty, and real focus on values such as the advancement of knowledge and free expression, we would like to share with you two recent projects we undertook:

The 1202 Issue Brief and Amicus Brief in Doe v. Github

Authors Alliance has been closely monitoring the impact of Digital Millennium Copyright Act (DMCA) Section 1202. As we have explained in a previous post, Section 1202(b) creates liability for those who remove or alter copyright management information (CMI) or distribute works with removed CMI. This provision, originally intended to prevent wide-spread piracy, has been increasingly invoked in AI copyright lawsuits, raising significant concerns for lawful use of copyrighted materials beyond training AI. While on its face, penalties for removing CMI might seem somewhat reasonable, the scope of CMI (including a wide variety of information such as website terms of service, affiliate links, and other information) combined with the challenge of including it with all downstream distribution of incomplete copies (imagine if you had to replicate and distribute something like the Amazon Kindle terms of service every time you quoted text from an ebook) could be potentially very disruptive for many users. 

In order to address the confusion regarding the (somewhat inaptly named) “identicality requirement” by the courts in the 9th Circuit, we have released an issue brief, as well undertaken to file an amicus brief in the Doe v. Github case now pending in the 9th Circuit.

Here are the key reasons why we care—and why you should care—about this seemingly obscure issue:

  • The Precedential Nature of Doe v. Github: The upcoming 9th Circuit case, Doe v. GitHub, will address whether Section 1202(b) should only apply when copies made or distributed are identical (or nearly identical) to the original. Lower courts have upheld this identicality requirement to prevent overbroad applications of the law, and the appellate ruling may set a crucial precedent for AI and fair use.
  • Potential Impact on Otherwise Legal Uses: It is not entirely certain if fair use is a defense to 1202(b) claims. If the identicality requirement is removed, Section 1202(b) could create liability for transformative fair uses, snippet reuse, text and data mining, and other lawful applications. This would introduce uncertainty for authors, researchers, and educators who rely on copyrighted materials in limited, legal ways. We advocate for maintaining the identicality requirement and clarifying that fair use applies as a defense to Section 1202 claims. 
  • Possibility of Frivolous Litigation: Section 1202(b) claims have surged in recent years, particularly in AI-related lawsuits. The statute’s vague language and broad applicability have raised fears that opportunistic litigants could use it to chill innovation, scholarship, and creative expression.

To find out more about what’s at stake, please take a look at our 1202(b) Issue Brief. You are also invited to share your stories with us, on how you have navigated this strange statute. 

Reply to the UK Open Consultation on Copyright and AI

We have members in the UK, and many of our US-based members publish in the UK. We have been watching the development in UK copyright law closely, and have recently filed a comment to the UK Open Consultation on Copyright and AI. In our comment, we emphasized the importance of ensuring that copyright policy serves the public interest. Our response’s key points include:

  • Competition Concerns: We alerted the policy-makers that their top objective must include preventing monopolies forming in the AI space. If licensing for AI training becomes the norm, we foresee power consolidating in a handful of tech companies and their unbridled monopoly permeating all aspects of our lives within a few decades—if not sooner. 
  • Fair Use as a Guiding Principle: We strongly believe that the use of works in the training and development of AI models constitutes fair use under US law. While this issue is currently being tested in courts, case law suggests that fair use will prevail, ensuring that AI training on copyrighted works remains permissible. The UK does not have an identical fair use statute, but has recognized that some of its functions—such as flexibility to permit new technological uses—are valuable. We argue that the wise approach is for the UK to update its laws to ensure its creative and tech sectors can meaningfully participate in the global arena. Our comment called for a broad AI and TDM exception allowing temporary copies of copyrighted works for AI training. We emphasized that when AI models extract uncopyrightable elements, such as facts and ideas, this should remain lawful and protected. 
  • Noncommercial Research Should Be Protected: We strongly advocated for the protection of noncommercial AI research, arguing that academic institutions and their researchers should not face legal barriers when using copyrighted works to train AI models for research purposes. Imposing additional licensing requirements would place undue burdens on academic institutions, which already pay significant fees to access research materials.

Thomson Reuters v. Ross: The First AI Fair Use Ruling Fails to Persuade

Posted February 13, 2025
A confused judge, generated by Gemini AI

Facts of the Case

On February 11, Third Circuit Judge Stephanos Bibas (sitting by designation for the U.S.  District Court of Delaware) issued a new summary judgment ruling in Thomson Reuters v. ROSS Intelligence. He overruled his previous decision from 2023 which held that a jury must decide the fair use question. The decision was one of the first to address fair use in the context of AI, though the facts of this case differ significantly from the many other pending AI copyright suits. 

This ruling focuses on copyright infringement claims brought by Thomson Reuters (TR), the owner of Westlaw, a major legal research platform, against ROSS Intelligence. TR alleged that ROSS improperly used Westlaw’s headnotes and the Key Number System to train its AI system to better match legal questions with relevant case law. 

Westlaw’s headnotes summarize legal principles extracted from judicial opinions. (Note: Judicial opinions are not copyrightable in the US.) The Key Number System is a numerical taxonomy categorizing legal topics and cases. Clicking on a headnote takes users to the corresponding passage in the judicial text. Clicking on the key number associated with a headnote takes users to a list of cases that make the same legal point. 

Importantly, ROSS did not directly ingest the headnotes and the Key Number System to train its model. Instead, ROSS hired LegalEase, a company that provides legal research and writing services, to create training data based on the headnotes and the Key Number System. LegalEase created Bulk Memos—a collection of legal questions paired with four to six possible answers. LegalEase instructed lawyers to use Westlaw headnotes as a reference to formulate the questions in Bulk Memos. LegalEase instructed the lawyers not to copy the headnotes directly. 

ROSS attempted to license the necessary content directly from TR, but TR refused to grant a license because it thought the AI tool contemplated by ROSS would compete with Westlaw.

The financial burden of defending this lawsuit has caused ROSS to shut down its operations. ROSS has countered TR’s copyright infringement claims with antitrust claims but the claims were dismissed by the same Judge. 

The New Ruling

The court found that ROSS copied 2,243 headnotes from Westlaw. The court ruled that these headnotes and the Key Number System met the low legal threshold for originality and were copyrightable. The court rejected the merger and scenes à faire defense by ROSS, because, according to the court, the headnotes and the Key Number System were not dictated by necessity. The court also rejected ROSS’s fair use defense on the grounds that the 1st and 4th factors weighed in favor of TR. At this point, the only remaining issue for trial is whether some headnotes’ copyrights had expired or were untimely registered.

The new ruling has drawn mixed reactions—some saying it undermines potential fair use defenses in other AI cases, while others dismiss its significance since its facts are unique. In our view, the opinion is poorly reasoned and disregards well-established case law. Future AI cases must demonstrate why the ROSS Court’s approach is unpersuasive. Here are three key flaws we see in the ruling.   

Problems with the Opinion

  1. Near-Verbatim Summaries are “Original”?

“A block of raw marble, like a judicial opinion, is not copyrightable. Yet a sculptor creates a sculpture by choosing what to cut away and what to leave in place. … A headnote is a short, key point of law chiseled out of a lengthy judicial opinion.” 

— the ROSS court

(↑example of a headnote and the uncopyrightable judicial text the headnote was based on↑)

The court claims that the Westlaw headnotes are original both individually and as a compilation, and the Key Number System is original and protected as a compilation. 

“Original” has a special meaning in US copyright law: It means that a work has a modicum of human creativity that our society would want to protect and encourage. Based on the evidence that survived redaction, it is near impossible to find creativity in any individual headnotes. The headnotes consist of verbatim copying of uncopyrightable judicial texts, along with some basic paraphrasing of facts. 

As we know, facts are not copyrightable, but expressions of facts often are. One important safeguard for protecting our freedom to reference facts is the merger doctrine. US law has long recognized that when there are only limited ways to express a fact or an idea, those expressions are not considered “original.” The expressions “merge” with the underlying unprotectable fact, and become unprotectable themselves. 

Judge Bibas gets merger wrong—he claims merger does not apply here because “there are many ways to express points of law from judicial opinions.” This view misunderstands the merger doctrine. It is the nature of human language to be capable of conveying the same thing in many different ways, as long as you are willing to do some verbal acrobatics. But when there are only a limited number of reasonable, natural ways to express a fact or idea—especially when textual precision and terms of art are used to convey complex ideas—merger applies. 

There are many good reasons for this to be the law. For one, this is how we avoid giving copyright protection to concise expression of ideas. Fundamentally, we do not need to use copyright to incentivize the simple restatement of facts. As the Constitution intended, copyright law is designed to encourage creativity, not to grant exclusive rights to basic expressions of facts. We want people to state facts accurately and concisely. If we allowed the first person to describe a judicial text in a natural, succinct way to claim exclusive rights over that expression, it would hinder, rather than facilitate, meaningful discussion of said text, and stifle blog posts like this one. 

As to the selection and arrangement of the Key Number System, the court claims that originality exists here, too, because “there are many possible, logical ways to organize legal topics by level of granularity,” and TR exercised some judgment in choosing the particular “level” with its Key Number System. However, the cases are tagged with Key Number System by an automated computer system, and the topics closely mirror what law schools teach their first-year students. 

The court does not say much about why the compilation of the headnotes should receive separate copyright protection, other than that it qualifies as original “factual compilations.” This claim is dubious because the compilation is of uncopyrightable materials, as discussed, and the selection is driven by the necessity to represent facts and law, not by creativity. Even if the compilation of headnotes is indeed copyrightable, using portions of it that are uncopyrightable is decidedly not an infringement, because the US does not protect sui generis database rights.

  1. Can’t Claim Fair Use When Nobody Saw a Copy?

 “[The intermediate-copying cases] are all about copying computer code. This case is not.” 

— the ROSS court conveniently ignoring Bellsouth Advertising & Publishing Corp. v. Donnelley Information Publishing, Inc., 933 F.2d 952 (11th Cir. 1991) and Sundeman v. Seajay Society, Inc., 142 F. 3d 194 (4th Cir. 1998).

In deciding whether ROSS’s use of Westlaw’s headnotes and the Key Number System is transformative under the 1st factor, the court took a moment to consider whether the available intermediate copying case law is in favor of ROSS, and quickly decided against it. 

Even though no consumer ever saw the headnotes or the Key Number System in the AI products offered by ROSS, the court claims that the copying of these constitutes copyright infringement because there existed an intermediate copy that contained copyright-restricted materials authored by Westlaw. And, according to the court, intermediate copying can only weigh in favor of fair use for computer codes.

Before turning to the actual case law the court is overlooking here, we wonder if Judge Bibas is in fact unpersuaded by his own argument: under the 3rd fair use factor, he admits that only the content made accessible to the public should be taken into consideration when deciding what amount is taken from a copyrighted work compared to the copyrighted work as a whole, which is contrary to what he argues under the 1st factor—that we must examine non-public intermediate copies. 

Intermediate copying is the process of producing a preliminary, non-public work as an interim step in the creation of a new public-facing work. It is well established under US jurisprudence that any type of copying, whether private or public, satisfies a prima facie copyright infringement claim, but, the fact that a work was never shared publicly—nor intended to be shared publicly—strongly favors fair use. For example, in Bellsouth Advertising & Publishing Corp. v. Donnelley Information Publishing, Inc., the 11th Circuit Court decided that directly copying a competitor’s yellow pages business directory in order to produce a competing yellow pages was fair use when the resulting publicly accessible yellow pages the defendant created did not directly incorporate the plaintiff’s work. Similarly, in Sundeman v. Seajay Society, Inc., the Fourth Circuit concluded that it was fair use when the Seajay Society made an intermediary, entire copy of plaintiffs’ unpublished manuscript for a scholar to study and write about it. The scholar wrote several articles about it mostly summarizing important facts and ideas (while also using short quotations).  

There are many good reasons for allowing intermediate copying. Clearly, we do not want ALL unlicensed copies to be subject to copyright infringement lawsuits, particularly when intermediate copies are made in order to extract unprotectable facts or ideas. More generally, intermediate copying is important to protect because it helps authors and artists create new copyrighted works (e.g., sketching a famous painting to learn a new style, translating a passage to practice your language skills, copying the photo of a politician to create a parody print t-shirt). 

  1. Suddenly, We Have an AI Training Market?

“[I]t does not matter whether Thomson Reuters has used [the headnotes and the Key Number System] to train its own legal search tools; the effect on a potential market for AI training data is enough.”

 — the ROSS court

The 4th fair use factor is very much susceptible to circular reasoning: if a user is making a derivative use of my work, surely that proves a market already exists or will likely develop for that derivative use, and, if a market exists for such a derivative use, then, as the copyright holder, I should have absolute control over such a market.

The ROSS court runs full tilt into this circular trap. In the eyes of the court, ROSS, by virtue of using Westlaw’s data in the context of AI training, has created a legitimate AI training data market that should be rightfully controlled by TR.

Only that our case law suggests the 4th factor “market substitution” considers only markets which are traditional, reasonable or likely to be developed. As we have already pointed out in a previous blog post, copyright holders must offer concrete evidence to prove the existence, or likelihood of developing, licensing market, before they can argue a secondary use serves as “market substitute.” If we allowed a copyright holder’s protected market to include everything that he’s willing to receive licensing fees for, it will all but wipe out fair use in the service of stifling competition. 

Conclusion

The impact of this case is currently limited, both because it is a district court ruling and because it concerns non-generative AI. However, it is important to remain vigilant, as the reasoning put forth by the ROSS court could influence other judges, policymakers, and even the broader public, if left unchallenged.

This ruling combines several problematic arguments that, if accepted more widely, could have significant consequences. First, it blurs the line between fact and expression, suggesting that factual information can become copyrightable simply by being written down by someone in a minimally creative way. Second, it expands copyright enforcement to intermediate copies, meaning that even temporary, non-public use of copyrighted material could be subject to infringement claims. Third, it conjures up a new market for AI training data, regardless of whether such a licensing market is legitimate or even likely to exist.

If these arguments gain traction, they could further entrench the dominance of a few large AI companies. Only major players like Microsoft and Meta will be able to afford AI training licenses, consolidating control over the industry. The AI training licensing terms will be determined solely between big AI companies and big content aggregators, without representation of individual authors or public interest.  The large content aggregators will get to dictate the terms under which creators must surrender rights to their works for AI training, and the AI companies will dictate how their AI models can be used by the general public. 

Without meaningful pushback and policy intervention, smaller organizations and individual creators cannot participate fairly. Let’s not rewrite our copyright laws to entrench this power imbalance even further.

AUTHORS ALLIANCE SUBMITS AMICUS BRIEF IN SEDLIK v. DRACHENBERG

Posted December 23, 2024
Kat Von D tracing the image of Miles Davis
in preparation for inking the tattoo

Although tattoos have existed for as long as human’s written history, legal disputes involving tattoos are a relatively new phenomenon. The case Sedlik v. Drachenberg, currently pending before the 9th Circuit, is particularly notable, as it marks the first instance of a court ruling on an artist’s use of copyrighted imagery in her tattoo art. 

More importantly, the case presents the 9th Circuit a first opportunity to interpret the fair use right in the wake of the Supreme Court’s 2023 Warhol decision. Authors Alliance has been closely monitoring circuit courts’ rulings on fair use and advocating for a proper interpretation of Warhol—including challenging the problematic fair use ruling issued by the 10th Circuit earlier this year, a decision that was later vacated in response to strong pushback from fair use advocates.

At the heart of the Sedlik v. Drachenberg legal debate are two creative professionals with very different backgrounds: 

The plaintiff in this case is Jeffery Sedlik. Sedlik is a successful professional photographer. He took a photo of the Jazz legend Miles Davis in 1989—an image that is at the focal point of the pending dispute. 

The defendant, Kat Von Drachenberg (“KVD”), is a celebrity tattoo artist. In recent years, she has shifted away from for-profit tattooing, opting instead to ink clients for free. In 2017, she freehand-tattooed Miles Davis on a client’s arm, largely drawing from the 1989 photograph captured by Sedlik.

Interestingly, neither party is new to the world of litigation. Sedlik has established a reputation for aggressive copyright enforcement—even filing a case with the Copyright Claims Board on its first day of operation. KVD, on the other hand, was sued by a former employee in 2022. 

Sedlik’s claims were straightforward—he alleges that KVD’s tattoo, as well as her social media posts documenting the process of her creating the tattoo, infringe his copyright in the Miles Davis photo.

For Sedlik to state a prima facie case of copyright infringement, he must prove that KVD had access to the Miles Davis photo (which is easy to prove in this case), and that the allegedly infringing tattoo and social media posts are substantially similar to the plaintiff’s photo. In this case, the district court left the question of substantial similarity and fair use to the jury, after refusing the motions for summary judgement on copyright infringement issues in May 2022. 

The jury returned a verdict in January 2024 that the tattoo inked by KVD and some of her social media posts are not substantially similar to Sedlik’s photo. The jury also determined that the rest of KVD’s social media posts, documenting her process of creating the tattoo in question, were fair use. In short, the jury concluded there was no copyright infringement.

On May 3rd, 2024, the district court judge denied Sedlik’s motions for judgment as a matter of law and for a new trial. Faced with the jury’s adverse decision, Sedlik argued, among other things, that the jury erred in finding no substantial similarity. The judge, however, upheld the jury’s finding that KVD’s works had a different concept and feel from Sedlik’s photo and that KVD only copied the unprotected elements of the photo. Sedlik tried to argue that the legal question of fair use should not have been left to the jury. However, the court was unpersuaded, highlighting that Sedlik had remained silent on this procedural issue until after receiving an unfavorable verdict.  

Following the ruling on his motions, Sedlik appealed, and the case is now in front of the 9th Circuit. Anticipating the far-reaching consequences for artists and authors depending on how the 9th Circuit will interpret Warhol, Authors Alliance filed an amicus brief in support of KVD.

Both Sedlik and KVD in this case argued that Warhol supported their side. Sedlik proposed a unique test, that a fair use must either target the original copyrighted work, or otherwise have a compelling justification for the use. In our amicus brief, we illustrated how that is not the correct reading of Warhol. Under Warhol, a distinct purpose is required for the first factor to tilt in favor of fair use. The Warhol Court only analyzed “targeting” and “compelling justification” because Warhol’s secondary use of the Goldsmith photo shared the exact same purpose as the photo, both for the purpose of appearing on the cover of a magazine. This is not the case with KVD’s freehand tattoo and Sedlik’s photo: they serve substantially distinct purposes.   

Authors routinely borrow from other’s copyrighted works for reporting, research, teaching, as well as to memorialize, preserve, or provide historical context. These uses by authors have historically been considered fair use, and often have purposes distinct from the copyrighted works used; but they do not necessarily “target” the works being used, nor do they have “compelling justifications” beyond the broad justification that authors are promoting the goal of copyright—”to promote the progress of science and the arts.”

In our brief, we also stressed how a successful commercial entity can nevertheless make noncommercial uses, as already demonstrated in the case of Google Books and Hachette. We also argued that social media posts are not commercial by default, just by virtue of drawing attention to the original poster. Many successful authors maintain active social media presence. The fact that authors invariably write to capture and build an audience through these sites does not automatically render their uses “commercial.” “Commerciality” under the fair use analysis has always been limited to the act of merchandising in the market, such as selling stamps, t-shirts, or mugs.

Finally, we explained to the court why copyright holders must offer concrete evidence to prove the existence, or likelihood of developing, licensing market, before they can argue a secondary use serves as “market substitute.” If we accepted Sedlik’s argument that his protected market includes everything that he’s willing to receive licensing fees for, it will all but wipe out fair use. We want authors and other creatives to continue to engage in fair use, including to document their creative processes—as KVD has done in this case in her social media posts, without being told they have to pay for each instance of use as soon as demanded by a rightsholder.  

Restricting Innovation: How Publisher Contracts Undermine Scholarly AI Research

Posted December 6, 2024
Photo by Josh Appel on Unsplash

This post is by Rachael Samberg, Director, Scholarly Communication & Information Policy, UC Berkeley Library and Dave Hansen, Executive Director, Authors Alliance

This post is about the research and the advancement of science and knowledge made impossible when publishers use contracts to limit researchers’ ability to use AI tools with scholarly works. 

Within the scholarly publishing community, mixed messages pervade about who gets to say when and how AI tools can be used for research reliant on scholarly works like journal articles or books. Some scholars voiced concern (explained more here) when major scholarly publishers like Wiley or Taylor & Francis entered lucrative contracts with big technology companies to allow for AI training without first seeking permission from authors. We suspect that these publishers have the legal right to do so since most publishers demand that authors hand over extensive rights in exchange for publishing their work. And with the backdrop of dozens of pending AI copyright lawsuits, who can blame the AI companies for paying for licenses, if for no other reason than avoiding the pain of litigation? While it stings to see the same large commercial, academic publishers profit yet again off of the work academic authors submit to them for free, we continue to think there are good ways for authors to retain a say in the matter. 

 Big tech companies are one thing, but what about scholarly research? What about the large and growing number of scholars who are themselves using scholarly copyrighted content with AI tools to conduct their research? We currently face a situation in which publishers are attempting to dictate how and when researchers can do that work, even when authors’ fair use rights to use and derive new understandings from scholarship clearly allow for such uses. 

How vendor contracts disadvantage US researchers

We have written elsewhere (in an explainer and public comment to the Copyright Office) why training AI tools, particularly in the scholarly and research context, constitutes a fair use under U.S. Copyright law. Critical for the advancement of knowledge, training AI is based on a statutory right already held by all scholarly authors engaging in computational research and one that lawmakers should preserve. 

The problem U.S. scholarly authors presently face with AI training is that publishers restrict their access to these statutory rights through contracts that override them: In the United States, publishers can use private contracts to take away statutory fair use rights that researchers would otherwise hold under Federal law. In this case, the private contracts at issue are the electronic resource (e-resource) license agreements that academic research libraries sign to secure campus access to electronic journal, e-book, data, and other content that scholars need for their computational research.

Contractual override of fair use is a problem that disparately disadvantages U.S. researchers. As we have described elsewhere, more than forty countries, including the European Union, expressly reserve text mining and AI training rights for scientific research by research institutions. Not only do scholars in these countries not have to worry whether their computational research with AI is permitted, but also: They do not risk having those reserved rights overridden by contract. The European Union’s Copyright Digital Single Market Directive and recent AI Act nullify any attempt to circumscribe the text and data mining and AI training rights reserved for scientific research within research organizations. U.S. scholars are not as fortunate. 

In the U.S., most institutional e-resource licenses are negotiated and managed by research libraries, so it is imperative that scholars work closely with their libraries and advocate to preserve their computational research and AI training rights within the e-resource license agreements that universities sign. To that end, we have developed adaptable licensing language to support institutions in doing that nationwide. But while this language is helpful, the onus of advocacy and negotiation for those rights in the contracting process remains. Personally, we have found it helpful to explain to publishers that they must consent to these terms in the European Union, and can do so in the U.S. as well. That, combined with strong faculty and administrative support (such as at the University of California), makes for a strong stance against curtailment of these rights.

But we think there are additional practical ways for libraries to illustrate—both to publishers and scholarly authors—exactly what would happen to the advancement of knowledge if publishers’ licensing efforts to curtail AI training were successful. One way to do that is by “unpacking” or decoding a publisher’s proposed licensing restriction, and then demonstrating the impact that provision would have on research projects that were never objectionable to publishers before, and should not be now. We’ll take that approach below.

Decoding a publisher restriction

A commercial publisher recently proposed the following clause in an e-resource agreement:

Customer [the university] and its Authorized Users [the scholars] may not:

  1. directly or indirectly develop, train, program, improve, and/or enrich any artificial intelligence tool (“AI Tool”) accessible to anyone other than Customer and its Authorized Users, whether developed internally or provided by a third party; or
  2. reproduce or redistribute the Content to any third-party AI Tool, except to the extent limited portions of the Content are used solely for research and academic purposes (including to train an algorithm) and where the third-party AI Tool (a) is used locally in a self-hosted environment or closed hosted environment solely for use by Customer or Authorized Users; (b) is not trained or fine-tuned using the Content or any part thereof; and (c) does not share the Content or any part thereof with a third party.  

What does this mean?

  • The first paragraph forbids the training or improving of any AI tool if it’s accessible or released to third parties. And, it further forbids the use of any computational outputs or analysis that are derived from the licensed content from being used to train any tool available to third parties. 
  • The second paragraph is perhaps even more concerning. It provides that when using third party AI tools of any kind, a scholar can use only limited portions of the licensed content with the tools, and are prohibited from doing any training at all of third party tools even if it’s a non-generative AI tool and the scholar is performing the work in a completely closed and highly secure research environment.

What would the impact of such a restrictive licensing provision be on research? 

It would mean that every single one of the trained tools in the following projects could never be disseminated. In addition, for the projects below that used third-party AI tools, the research would have been prohibited full-stop because the third-party tools in those projects required training which the publisher above is attempting to prevent:

Tools that could not be disseminated

  1. In 2017, chemists created and trained a generative AI tool on 12,000 published research papers regarding synthesis conditions for metal oxides, so that the tool could identify anticipated chemical outputs and reactions for any given set of synthesis conditions entered into the tool. The generative tool they created is not capable of reproducing or redistributing any licensed content from the papers; it has merely learned conditions and outcomes and can predict chemical reactions based on those conditions and outcomes. And this beneficial tool would be prohibited from dissemination under the publisher’s terms identified above.
  2. In 2018, researchers trained an AI tool (that they had originally created in 2014) to understand whether a character is “masculine” or “feminine” by looking at the tacit assumptions expressed in words associated with that character. That tool can then look at other texts and identify masculine or feminine characters based on what it knows from having been trained before. The implications are that scholars can therefore use texts from different time periods with the tool to study representations of masculinity and femininity over time. No licensed content, no licensed or copyrighted books from a publisher can ever be released to the world by sharing the trained tool; the trained tool is merely capable of topic modeling—but the publisher’s above language would prohibit its dissemination nevertheless. 

Tools that could neither be trained nor disseminated 

  1. In 2019, authors used text from millions of books published over 100 years to analyze cultural meaning. They did this by training third-party non-generative AI word-embedding models called Word2Vec and GLoVE on multiple textual archives. The tools cannot reproduce content: when shown new text, they merely represent words as numbers, or vectors, to evaluate or predict how similar words in a given space are semantically or linguistically. The similarity of words can reveal cultural shifts in understanding of socioeconomic factors like class over time. But the publisher’s above licensing terms would prohibit the training of the tools to begin with, much less the sharing of them to support further or different inquiry. 
  2. In 2023, scholars trained a third-party-created open-source natural language processing (NLP) tool called Chemical Data Extractor (CDE). Among other things, CDE can be used to extract chemical information and properties identified in scholarly papers. In this case, the scholars wanted to teach CDE to parse a specific type of chemical information: metal-organic frameworks, or MoFs. Generally speaking, the CDE tool works by breaking sentences into “tokens” like parts of speech and referenced chemicals. By correlating tokens, one can determine that a particular chemical compound has certain synthetic properties, topologies, reactions with solvents, etc. The scholars trained CDE specifically to parse MoF names, synthesis methods, inorganic precursors, and more—and then exported the results into an open source database that identifies the MoF properties for each compound. Anyone can now use both the trained CDE tool and the database of MoF properties to ask different chemical property questions or identify additional MoF production pathways—thereby improving materials science for all. Neither the CDE tool nor the MoF database reproduces or contains the underlying scholarly papers that the tool learned from. Yet, neither the training of this third-party CDE tool nor its dissemination would be permitted under the publisher’s restrictive licensing language cited above.

Indeed, there are hundreds of AI tools that scholars have trained and disseminated—tools that do not reproduce licensed content—and that scholars have created or fine-tuned to extract chemical information, recognize faces, decode conversations, infer character types, and so much more. Restrictive licensing language like that shown above suppresses research inquiries and societal benefits that these tools make possible. It may also disproportionately affect the advancement of knowledge in or about developing countries, which may lack the resources to secure licenses or be forced to rely on open-source or poorly-coded public data—hindering journalism, language translation, and language preservation.

Protecting access to facts

Why are some publishers doing this? Perhaps to reserve the opportunity to develop and license their own scholarship-trained AI tools, which they could then license at additional cost back to research institutions. We could speculate about motivations, but the upshot is that publishers have been pushing hard to foreclose scholars from training and dissemination AI tools that now “know” something based on the licensed content. That is, such publishers wish to prevent tools from learning facts about the licensed content. 

However, this is precisely the purpose of licensing content. When institutions license content for their scholars to read, they are doing so for the scholars to learn information from the content. When scholars write about it or teach about the content, they are not regenerating the actual expression from the content—the part that is protected by copyright; rather the scholars are conveying the lessons learned from the content—facts not protected by copyright. Prohibiting the training of AI tools and the dissemination of those tools is functionally equivalent to prohibiting scholars from learning anything about the content that institutions are licensing for that very purpose, and that scholars have written to begin with! Publishers should not be able to monopolize the dissemination of information learned from scholarly content, and especially when that information is used non-commercially.

For these reasons, when we negotiate to preserve AI usage and training rights, we generally try to achieve the following outcomes which would promote—rather than prohibit—all of the research projects described above:

The sample language we’ve disseminated empowers others to negotiate for these outcomes. We hope that, when coupled with the advocacy tools we’ve provided above, scholars and libraries can protect their AI usage and training rights, while also being equipped to consider how they want their own works to be used.

Hachette v. Internet Archive Update: Second Circuit Court of Appeals Rules Against Internet Archive

Posted September 5, 2024

We got a disappointing decision yesterday from the Second Circuit Court of Appeals in the long-running Hachette v. Internet Archive (IA) copyright lawsuit about IA’s digitization and lending of books. The Court affirmed the district court’s decision that IA cannot circulate digital copies of books they have legitimately acquired in physical copies, even when only the same number of copies as legitimately acquired are circulated to a single user at a time—just as a physical book would be loaned.

The Court, focusing on IA’s lending of digitized books that were available for license as ebooks from the publishers, concluded that IA’s fair use defense fails. We think this decision will result in a meaningful reduction in access to knowledge. This is sad news for many authors who have relied on IA’s Open Library for research and discovery, and  for readers who have used Open Library to find authors works. However, we also view it as a decision limited to its facts—that is, IA’s particular implementation of controlled digital lending (CDL), and more specifically, its lending of books that are already available in licensed digital formats. 

We plan to do a more in-depth analysis of the Court’s decision later, but for now, we offer some initial thoughts. First, there are a couple of bright spots in the opinion: 

1) The Court rejected the district court’s conclusion that IA was engaged in commercial use when looking at the first factor of fair use. The publishers argued IA’s lending of digitized books was commercial in nature because IA received a few thousand dollars from a for-profit used-bookseller and also solicited donations on its website. The Court rightly pointed out that if that was the standard, virtually every nonprofit that solicits donations would by default only be able to engage in commercial use. This was an issue we and others strongly urged the Court to address, and we’re glad it did. 

2)  For the most part, the Court focused its analysis on the facts of the case, which was really about IA lending digitized copies of books that were already available in ebook form and licensable from the publishers. The legal analysis in several places turned on this fact, which we think leaves room to make fair use arguments regarding programs to digitize and make available other books, such as print books for which there is no licensed ebook available, out-of-print books, or orphan works. CDL will remain an important framework, especially considering the lack of an existing digital first-sale doctrine.  

We are also disappointed by several key points in the decision: 

One was the Court’s assessment of the first fair use factor, “purpose and character of the use.” The Court’s analysis of this factor was in some ways unsurprising but nevertheless disappointing. The Court did little more than conclude that the use was not transformative and, therefore, not fair use. Though we think there are strong arguments that CDL is transformative, whether CDL is “transformative” is just one of the supporting rationales for the argument that CDL is fair use. The other justifications—that CDL supports teaching, scholarship, and research, along with complementing the first sale doctrine and supporting the public-interest mission of libraries—are at the heart of CDL. The Court didn’t engage with those other arguments at all and also ignored meaningful discussion of cases where non-transformative copying supported a fair use finding because of the public benefits.

A second key issue is about whether IA’s digital lending negatively impacts the market for the original works. This issue probably deserves a whole blog post to itself, but in short the analysis came down to who shoulders the burden of proving or disproving market harm, and what default assumptions the court has about market harm.  The following quotes from the decision will give you a sense of how the Court analyzed the issue: 

[a]lthough they do not provide empirical data of their own, Publishers assert that they (1) have suffered market harm due to lost eBook licensing fees and (2) will suffer market harm in the future if IA’s practices were to become widespread.  IA argues that Publishers cannot rely on the “common-sense inference” of market harm without data to back that up, citing American Society for Testing & Materials v. Public.Resource.Org, Inc. [citations omitted]. . . . We agree with Publishers’ assessment of market harm. 

Despite IA’s experts having offered meaningful data and analysis indicating a lack of market harm on sales of publishers’ books, the Court went on to say: 

We are likewise convinced that “unrestricted and widespread conduct of the sort engaged in by [IA] would result in a substantially adverse impact on the potential market for [the Works in Suit]. . . . Though Publishers have not provided empirical data to support this observation, we routinely rely on such logical inferences where appropriate in assessing the fourth fair use factor. . . . Thus, we conclude it is “self-evident” that if IA’s use were to become widespread, it would adversely affect Publishers’ markets for the Works in Suit.

We are also disappointed by how the Court portrayed the overall public benefit of IA’s lending and its long-term effect: “while IA claims that prohibiting its practices would harm consumers and researchers, allowing its practices would―and does―harm authors.” We think this is a gross generalization and mischaracterization of how IA’s digital lending affects most authors. Authors are researchers. Authors are readers. IA’s digital library helps authors create new works and supports their interests in having their works read. This ruling may benefit the largest publishers and most prominent authors, but for most, it will end up harming more than it will help. 

Fair Use Week 2023: Looking Back at Google Books Eight Years Later

Posted February 24, 2023
Photo by Patrick Tomasso on Unsplash

This post is authored by Authors Alliance Senior Staff Attorney, Rachel Brooke. 

More recent members and readers may not be aware that Authors Alliance was founded in the wake of Authors Guild v. Google,  a class action fair use case in the Second Circuit that was litigated for nearly a decade, and finally resolved in favor of Google in 2015. The case concerned the Google Books project—an initiative launched by Google whereby the company partnered with university libraries to scan books in their collections. These scans would ultimately be made available as a full-text searchable database for the public to search through for particular terms, with short “snippets” displayed accompanying the search results. Users could not, however, view or read the scanned books in their entirety. The Authors Guild, along with several authors, filed a lawsuit against Google alleging that scanning the books and displaying these snippets constituted copyright infringement.

In addition to Authors Guild representing its members in the litigation, its associated plaintiffs brought the case as a class action, claiming to bring the case on behalf of a broad group of authors:  “[a]ll persons residing in the United States who hold a United States copyright interest in one or more Books reproduced by Google as part of its Library Project” who were either authors or the authors’ heirs.

But many of these authors did not agree with the Authors Guild’s stance in the case, and felt that the Google Books project served their interests in sharing knowledge, seeing their creations be preserved, and reaching readers interested in their work. A group of authors and scholars came together to share their views with the district court, many of whom would soon become founding members of Authors Alliance. Many of those same authors signed on to amicus briefs before both the district court and Second Circuit explaining why they opposed the litigation and supported Google’s fair use defense. Then, in 2014, Authors Alliance submitted its first amicus brief to the Second Circuit, supporting Google’s ultimately successful fair use defense. The plaintiffs later appealed the Second Circuit’s ruling, asking the Supreme Court to weigh in, but the Court ultimately declined to hear the case, leaving the Second Circuit’s ruling intact. 

Nearly a decade later, the effects of Google Books can still be seen in fair use decisions and copyright policy developments involving the challenges of adapting copyright to the digital world. In today’s post, I’ll reflect on how Google Books can be contextualized within today’s fair use landscape and share my thoughts on what the case can tell us about copyright in the digital world. 

Google Books and Transformativeness

A major question in Authors Guild v. Google was whether Google’s use of the copyrighted works was “transformative,” a key component of the fair use inquiry. When a use is found to be transformative, this in practice weighs heavily in favor of a finding of fair use. In the case, the court found that Google’s scanning, as well as the search and snippet display functions, were transformative because the service “augments public knowledge by making available information about [the] books without providing the public with a substantial substitute for . . . the original works.” This was because Google Books provided information about the books—such as the author and publisher information—without creating substitutes of the original works. In other words, readers could learn about the books they searched through, but could not read the books in full—to do this, those readers would have to purchase or borrow copies through the normal channels. 

Since the doctrine of transformativeness was established in the 1994 landmark Supreme Court case, Campbell v. Acuff-Rose Music, there have been myriad questions about the precise contours of what it means for a use to be transformative. Campbell established that a use is transformative when it endows the secondary work with a “new meaning or message,” but it can be difficult to apply this test in practice, particularly in the context of new or nascent technologies. Google Books tells us that scanning works in order to create a full-text searchable database with limited snippet displays is a transformative use based on its new and different purpose from the purpose of the works themselves. Furthermore, it reinforces the notion that a use is particularly likely to be considered transformative when it serves the underlying purpose of copyright law: incentivizing new creation for the benefit of the public and “enriching public knowledge.” By highlighting that Google contributed to public knowledge about books through its scanning activities and the Google Books search function, the court helped bring fair use for scholarship and research—two key prototypical uses established in the 1976 Copyright Act—into the digital age, setting an important precedent for later cases. 

Google Books and Derivative Works

One of the plaintiffs’ arguments in Google Books was that Google’s full-text searchable database constituted a derivative work. One of a copyright holder’s exclusive rights is the right to prepare derivative works—such as adaptations, abridgements, or translations of the original work—and the plaintiffs alleged that this right had been infringed. The court disagreed, finding that Google’s use had a transformative purpose, whereas derivative works tend to involve a transformation in form, such as the adaptation of a novel into a movie or an audiobook. Furthermore, the court explained that derivative works are “those that re-present the protected aspects of the original work, i.e., its expressive content, converted into an altered form[.]” In contrast, the Google Books project provided information about the books and offered a limited “snippet” view, but did not re-present the expressive content: the full text of the books themselves.

The distinction the court drew between transformative fair uses and derivative works in Google Books is an important one, as it can often be a close question whether a work involves a transformative purpose or merely represents the same work in a new form, without enough added to tip the scales towards fair use. And it is a question that continues to arise in fair use cases today: just last year, the Supreme Court agreed to hear Warhol Foundation v. Goldsmith, a case about whether Andy Warhol’s creation of a series of screenprints of the late musical artist Prince which drew from a photograph taken by photographer Lynn Goldsmith qualified as a fair use. We’ve covered this case extensively on our blog over the past few years, and submitted an amicus brief in the case. Our brief argues (among other things) that Warhol’s screen prints involve much more than a transformation in form: they are stylistically and visually distinct from Goldsmith’s photograph, and endow the photograph with a new meaning or message, making the use highly transformative. 

As in Google Books, the parties and amici in Goldsmith grapple with the line between transformative uses and the creation of derivative works, an often complicated and fact-sensitive determination. In this context, Google Books serves as a reminder that fair use is not a one-size-fits-all determination. Yet it also provides support for arguments advanced by Authors Alliance and others that simply because a transformation in form exists—in the Google Books case, the transformation from a print book to a scanned copy, and in Goldsmith, the transformation of a black and white photo to a series of colorful screenprints—does not mean that a secondary use cannot be a fair one. Warhol’s use did not merely “re-present the protected aspects of the original work[‘s] . . . expressive content,” but was transformative in the different “purpose, character, expression, meaning, and message” it conveyed.

Google Books and Controlled Digital Lending

The practice of controlled digital lending (“CDL”)—and the arguments in favor of it constituting a fair use—can be traced back in part to the fair use principles established and reinforced in Google Books. As I argue in our amicus brief in Hachette Books v. Internet Archive, a case about—among other things—whether CDL constitutes a fair use, Google Books shows that copying the entirety of a work in the process of making a transformative use of it can be fully consistent with fair use. 

Another important suggestion in the Google Books case, made at the district court level, was that the Google Books search function could actually drive book sales: the search results were accompanied by links to purchase the book, and research suggested that this could enhance sales of those books. This is analogous to the effects of library lending: library readers often purchase books by authors they first discovered at the library, an effect which can apply with equal force when the library patron borrows a CDL scan. Indeed, several other amici in Hachette Books argue that the finding that the Google Books search was a fair use lent substantial support for the argument that CDL is a fair use, based on both the factual similarities between the two initiatives and their shared objective of “enriching public knowledge.” 

As in Google Books, CDL also helps authors reach readers who could not otherwise access their books, and achieves this through scanning books on library shelves. And also like Google Books, CDL helps solve the problem of 20th century works “disappearing”: the commercial life of a book tends to be much shorter than the term of copyright, so when books under copyright go out of print, they can disappear into obscurity. Scanning these books to preserve them ensures that the knowledge they advance will not be lost. 

Google Books and Text Data Mining

Text data mining—the process of using automated techniques aimed at quantitatively analyzing text and other data—is also widely considered to be a fair use, and this determination is similarly built in part on the building blocks established in Google Books. As was the case in Google Books, the results of text data mining research provide information about the works being studied, and cannot in any way serve as substitutes for the content of the works. In fact, one important aspect of the new exemption to DMCA liability for text data mining, which Authors Alliance successfully petitioned for in 2021, is that researchers are not able to use the works in the text data mining corpus for consumptive purposes. And also like Google Books, researchers are able to view the content in a limited manner to verify their findings, analogous to Google Books’s snippet view. The new TDM exemption was a huge win for Authors Alliance members, and something to celebrate for all scholars engaged in this important research. Importantly, the precedent established by Google Books strongly supported its adoption and the Register of Copyright’s suggestion that text data mining was likely to be a fair use. 

Looking Forward: Google Books and Artificial Intelligence

In recent years, scholars and researchers have grappled with the implications of copyright protection on AI-generated content and AI models more generally. The holding in Google Books provides some support for companies’ and researchers’ ability to engage in these activities: one important factor in the case was that Google Books did not harm the market for the books at issue in the case, since the books in the database could not serve as substitutes for the books themselves. Similarly, when copyrighted works are used to train AI, the output cannot serve as a substitute for the copyrighted works, and the market for those works is not harmed, even if—like the plaintiffs in Google Books—the copyright holders might prefer that their works not be used in this way. Google Books establishes that simply because copyrighted works are used as “input” in a given model, this does not mean that the outputs constitute infringement. It is also worth noting that the court found Google’s use to be fair despite the fact that it was a use by a commercial, profit-seeking entity. While a commercial use can sometimes tip the scales in favor of finding a use to not be fair, this can be overcome by a socially beneficial, transformative purpose. This could arguably apply with equal force to AI models trained on copyrighted works which contribute to our understanding of the world, despite the fact that commercial entities are often the ones deploying these technologies. 

Eight years after it was decided, the legacy of Google Books endures in policy debates and copyright lawsuits that capture the public’s attention. Policymakers and judges would be wise to heed the lessons it teaches about the value of advancing public knowledge through digitization and the use of copyrighted works for new and socially beneficial purposes. As we await policy developments regarding text data mining and wait for decisions in Goldsmith and Hachette Books, it is my hope that this legacy will live on, reminding us all of the vast capabilities of information technology to enrich our understanding of the world and advance the progress of knowledge, which, after all, is what copyright law is all about. 

Fair Use Week 2023: How to Evade Fair Use in Two Easy Steps

Posted February 23, 2023

This post is by Dave Hansen and also posted to the Fair Use Week blog here.

Fair use is an essential part of the Copyright Act’s careful balance—on the one hand protecting rightsholders’ interests, while on the other “[permitting and requiring] courts to avoid rigid application of the copyright statute when, on occasion, it would stifle the very creativity which that law is designed to foster.” The Supreme Court has explained that fair use is a core part of what makes the Copyright Act compatible with the First Amendment guarantee of free expression. “First Amendment protections are ‘embodied . . . ’ in the ‘latitude for scholarship and comment’ safeguarded by the fair use defense.”

Fair use is what has allowed biographers to quote critically from originals when writing their own works, even when the copyrights are owned by the rich and powerful, as in cases involving L. Ron Hubbard and Howard Hughes. It’s what allows researchers to write and quote from unpublished manuscripts for literary criticism, as in this case about scholarly use of an unpublished work by Marjorie Kinnan Rawlings Baskin. It’s also what has allowed libraries to provide copies of books to blind readers, conduct research across texts, and make preservation copies. It allows reuse of images in support of news and political commentary, supports researchers who use tools like Google Image Search, and allows artists to use source materials to create transformative new works, such as parody.

Two easy steps to evade fair use

Given its importance, it may surprise you to learn that fair use is remarkably easy to evade. Savvy copyright owners do it all the time.  It takes just two easy steps.

First, you need to write a contract, specifically a “license” for the use of your work. In it, you dictate the terms on which you provide access to your work. You can impose almost any restrictions you like. Sometimes, contracts will restrict certain classes of uses: “you cannot reproduce this content for commercial use” or “you may download one copy of this work for personal consultation; you cannot reproduce or share any part of this work in whole or in part in any form, or share in any form with the public.”

Other contractual terms guard against specific threats. For example, Disney once won a lawsuit over use of its movie trailers, which Disney would license to websites only if they agreed that the website “may not be derogatory to or critical of the entertainment industry or of [Disney] (and its officers, directors, agents, employees, affiliates, divisions and subsidiaries) or of any motion picture produced or distributed by [Disney].”

The key here is that you can essentially rewrite the rules, and forbid those aspects of fair use that you disapprove of. Want to make sure critics can’t use your words against you? Just say they can’t. Want to make sure libraries don’t make preservation copies without paying you first? Want to make sure that instructors of college classes can only use excerpts of your book—even very small excerpts—if they pay every single time? It’s your prerogative.

Second, you need to make sure that everyone who gains access to your work is bound by your license. This sounds hard, but with online distribution, it’s actually pretty easy.

In the world of print copies, this was difficult because copies had a way of traveling beyond the control of the original purchaser. The “first sale” doctrine meant that buyers of copies could freely transfer those copies to third-party buyers (e.g., someone who buys a book at a used book store, or who borrows a book from a library) or give them away. So, even if you got the original buyer to agree to your terms, those downstream users didn’t have to. But there is no widespread acceptance of a buyer’s “digital first sale.” So, buyers can’t just transfer the copies they purchase to downstream users. Everyone who wants access to the digital copy must agree to the license. All you have to do is make sure that your materials are distributed exclusively on digital platforms that are subject to your terms, and you’re all set.

That’s it. Two easy steps and you’ve practically eliminated fair use. For any use you haven’t already authorized, you can just say no, require them to pay whatever you want, or just refuse to grant access. And if they don’t comply, at a minimum you’ve got at a slam-dunk breach of contract claim. 

Is it Seriously That Easy?

Unfortunately, this two-step approach–sometimes known as “contractual override”–reflects the prevailing wisdom and practice of many copyright owners. It is widely used online, by parties ranging from massive corporations such as Amazon or Netflix to small publishers and news outlets. And though the precedent for it isn’t airtight, when it has come up in court, the licensors have mostly prevailed. Because U.S. law so venerates “freedom of contract,” it has been difficult for policymakers or the courts to address the problem of rightsholders forbidding lawful fair uses under the terms of their licenses.

How did we get to this point? This is not a new or unexpected problem. You can look back to 1993, when law professor Jane Ginsburg  foresaw this state of affairs just as the possibilities of the internet were coming into view:

“In the digital environment posited here, contract protection may not be the fragile creature presumed in prior intellectual property preemption decisions. If access to works could be obtained only through the information provider (directly or through an authorized online distributor), and if copying could be electronically tracked or prevented, no ‘third parties’ to the contract would exist. When ‘we’re all connected,’ no functional difference may exist between a contract and a property right. At that point, it becomes necessary to consider whether limitations incorporated in the copyright law should be imported to its contractual substitute.”

Numerous others in the legal community soon made similar observations, such as Julie Cohen, Niva Elkin-Koren, and Andrew Shapiro, among others, who also wrote about aspects of this then-new challenge.

How to Protect Fair Use from Contractual Override 

A handful of efforts to address this problem have been mounted in Congress. In 2003 and 2005, representative Zoe Lofgren introduced a bill appropriately called the BALANCE Act (“Benefit Authors without Limiting Advancement or Net Consumer Expectations”), which addressed both the unavailability of “first sale” in the digital environment and contractual override of fair use. The proposed legislation provided that “[w]hen a digital work is distributed to the public subject to nonnegotiable license terms, such terms shall not be enforceable under the common laws or statutes of any State to the extent that they restrict or limit any of the limitations on exclusive rights under this title.” The BALANCE Act never passed however, and hasn’t been revisited in Congress since 2005.

Recent actions in other jurisdictions may provide renewed legislative interest and guidance on possible models to adopt. For example, in 2014, the UK passed legislation that limits contractual override of user rights—providing that “to the extent that a term of a contract purports to prevent or restrict the doing of any act which, by virtue of this section, would not infringe copyright, that term is unenforceable.” This language has been applied in the UK to exceptions that allow for making copies for persons with print and other disabilities, research and teaching, and text and data-mining. Similarly, the EU’s recent Copyright in the Digital Single Market Directive contains similar protections for copyright exceptions, as does Singapore’s recent copyright bill. So far, though, there has been no indication of real interest from Congress in the United States.

It’s also possible that states could craft legislation. There has recently been a surge of interest in bills in a number of states aimed at protecting libraries’ ability to license books on reasonable terms (bills that Authors Alliance generally supports). These bills also go beyond what fair use protects—seeking to, for example, ensure that libraries have broad access to ebooks on “reasonable terms,” and addressing problems of major publishers simply refusing to license books to libraries. Maryland was the first state to actually pass such a law, but it was struck down as preempted by federal copyright law in AAP v. Frosh. The court concluded that because federal copyright law dictates the scope of rights governing public distribution of works, it was impermissible for the state of Maryland to interject its own rules about the scope of the publishers’ distribution rights.

It’s possible that state legislation that is more narrowly tailored—e.g., a state law that focused solely on protecting fair use—would not suffer the same fate as the Maryland law. In fact, the reasoning of the Maryland e-lending case would seem to support such a state law, since a state law protecting fair use would be maintaining, rather than altering, the balance of rights as defined by federal law.

Legal Strategies in Court

It’s also possible that the courts could intervene, though so far they have mostly declined to do so. It seems to me there are two or three viable ways for judicial intervention to be effective:

First, Courts could conclude that contracts (created under and governed by state law) are preempted by federal copyright law, which is what defines the scope of copyright’s exclusive rights.  The Constitution provides that federal law supersedes conflicting state law, and Congress has provided specific instructions on how such preemption should apply, stating that “all legal or equitable rights that are equivalent to any of the exclusive rights within the general scope of copyright as specified by section 106 . . .  are governed exclusively” by federal copyright law. Those exclusive rights of copyright owners are explicitly defined as being “subject to” the limitations including fair use, so it would make some sense for courts to view state law expansions of those rights as being in conflict with and therefore preempted by federal copyright law.

However, there are several negative precedents indicating that this approach may not work. Take Bowers v. Baystate, for example, a Federal Circuit case involving two competing computer aided design (CAD) software companies. Bowers contended that Baystate violated the terms of use on its software by reverse-engineering its product in violation of a clause explicitly prohibiting such use. Baystate contended that such reverse engineering was protected by fair use and that contract terms to the contrary should be preempted as inconsistent with federal law. The Federal Circuit, observing that as a general matter “most courts to examine this issue have found that the Copyright Act does not preempt contractual constraints on copyrighted articles,” concluded that “private parties are free to contractually forego the limited ability to reverse engineer a software product under the exemptions of the Copyright Act. . . . [A] state can permit parties to contract away a fair use defense or to agree not to engage in uses of copyrighted material that are permitted by the copyright law, if the contract is freely negotiated.”

Other courts addressing state contract law and other state law limitations on fair use (e.g,. this California right of publicity case) have largely followed the same approach. One notable exception to is Vault Corp. v. Quaid Software, Ltd., in which the Fifth Circuit invalidated a Louisiana law that permitted contracts to prohibit reverse engineering, even though federal law provides a specific exception (Section 117) that allows for such reverse engineering. Although not directly addressing fair use, the court’s holding could apply equally to state law contractual restrictions on fair use. The issue has not directly reached the Supreme Court, though there is a case, Genius v. Google, currently pending on a Petition for Certiorari that asks the Court to weigh in on the broader question of when federal law preempts contracts under state law.

Second, courts could conclude that the state common law (the body of law made up of legal principles established by courts over the years) on contracts does not permit contractual restrictions on fair use. This could come in a few different forms. One option might be for courts to consider more seriously the question of whether a valid contract is actually created in the first place, particularly in situations where users have no meaningful opportunity to negotiate terms and little ability to even understand what restrictions they are agreeing to. For years, following the lead of the Seventh Circuit Court of Appeals in ProCD v. Zeidenberg, courts have been willing to accept that a valid agreement is formed even in situations with “shrinkwrap” or “browsewrap” licenses. But, despite ongoing criticism of this approach by many, the approach has prevailed. Courts might also take more seriously the public policy implications of fair use evasion more directly, by invoking traditional rules for contract interpretation that hold terms unenforceable when they violate public policy—e.g., agreements to commit a crime, or a tort, or restraint of trade. To date, however, I’m unaware of any such cases directly applying these principles to contracts that restrict fair use, though there is a large body of case law and this may merit more research.

Third, the courts could apply existing or new equitable doctrines, such as “copyright misuse” or a yet-to-be-defined right of “fair breach” to protect users from overenforcement of contracts that limit fair use. Professor Jane Ginsburg outlines the potential need for courts to develop their own remedy of “fair breach.” She observes that, as with the current licensing environment online, at some point “it becomes necessary to consider whether limitations incorporated in the copyright law should be imported to its contractual substitute. With respect to libraries and their users, one should inquire whether some kind of fair use exception is appropriate. This might take the form of a judge-made right of ‘fair breach,’ or legislatively imposed mandatory library-user rights.”

This idea of “fair breach” has drawn little attention since Ginsburg first identified its need and coined the term, but it merits further attention. “Fair breach” may have some similarity to the existing doctrine of copyright misuse, which could have some application to contracts that restrict fair use. A judge-made doctrine borrowed from the patent law doctrine of patent misuse, copyright misuse has been mostly applied to situations where copyright owners have attempted to exercise their rights to unfairly stifle competition. The primary question with copyright misuse is “whether the copyright is being used in a manner violative of the public policy embodied in the grant of a copyright.” If copyright misuse is found, the copyright isn’t invalidated, but courts have held that the owners’ copyright cannot be enforced to exclude the harmed party’s use. The Supreme Court has yet to acknowledge the existence of this doctrine, but numerous appellate courts have recognized it over the last thirty years.

A handful of cases suggest that extension of copyright misuse to fair-use limiting contracts could be effective. For example, in Assessment Technologies of Wi, LLC v. Wiredata, the Seventh Circuit Court of Appeals held that Assessment Technologies’ attempt to restrict access to data that was not copyrighted fell within the copyright misuse doctrine’s core focus: “preventing copyright holders from leveraging their limited monopoly to allow them control of areas outside the monopoly.”

 Video Pipeline, Inc. v Buena Vista Home Entertainment, Inc., also gives some encouragement. In that case, Video Pipeline brought a declaratory judgment action seeking a judgment that its use of video trailers from Disney and others was not copyright infringement. Among the defenses it cited was copyright misuse on the part of Disney. To support its copyright misuse argument, Video Pipeline pointed to the license term I mentioned at the beginning of this blog post, which conditioned the license on an agreement to not disparage Disney or the entertainment industry. The court ultimately declined to find that those terms constituted copyright misuse, because the contract had a narrow focus and limited application: “we nonetheless cannot conclude on this record that the agreements are likely to interfere with creative expression to such a degree that they affect in any significant way the policy interest in increasing the public store of creative activity. The licensing agreements do not, for instance, interfere with the licensee’s opportunity to express such criticism on other web sites or elsewhere.” However, the court suggested that the outcome could have been different if the restrictions were more far reaching.   

Conclusion

Contractual override of fair use poses a real threat to free expression, especially given the increasing limits on distribution of copyrighted works online. Almost all online platforms that distribute copyrighted works impose restrictions that inhibit fair use to some degree. It takes just two easy steps. Thankfully, there are some plausible routes forward for improving the law to protect authors and others who rely on fair use to create new works and share knowledge with the world. There is also some reason for optimism due to renewed interest in the issue among scholars and organizations such as the Association of Research Libraries, which issued a report on contractual override for libraries, and is co-hosting a symposium with Washington College of Law at American University on the subject with perspectives from around the world.

Fair Use Week 2023: Resource Roundup

Posted February 21, 2023
Photo by Adi Goldstein on Unsplash

Authors who want to incorporate source materials into their writings with confidence may find themselves faced with more questions than answers. What exactly does fair use mean? What factors do courts consider when evaluating claims of fair use? How does fair use support authors’ research, writing, and publishing goals? Fortunately, help is at hand! This Fair Use/Fair Dealing Week, we’re featuring a selection of resources, briefs, and blog posts to help authors understand and apply fair use.

Fair Use 101

Cover of the Fair Use Guide for Nonfiction Authors

Authors Alliance Guide to Fair Use for Nonfiction Authors: Our guidebook, Fair Use for Nonfiction Authors, covers the basics of fair use, addresses common situations faced by nonfiction authors where fair use may apply, and debunks some common misconceptions about fair use. Download a PDF today.

Authors Alliance Fair Use FAQs: Our Fair Use FAQs cover questions such as:

  • Can I still claim fair use if I am using copyrighted material that is highly creative?
  • What if I want to use copyrighted material for commercial purposes?
  • Does fair use apply to copyrighted material that is unpublished?

Codes of Best Practices in Fair Use: The Center for Media and Social Impact at American University has compiled this collection of Codes of Best Practices in Fair Use for various creative communities, from journalists to librarians to filmmakers.

Fair Use Evaluator Tool: This tool, created by the American Library Association, helps users support and document their assertions of fair use.

Dig Deeper

U.S. Copyright Office Fair Use Index: The U.S. Copyright Office maintains this searchable database of legal opinions and fair use test cases.

Fair Use Amicus Briefs: Authors Alliance submitted several friend of the court briefs on issues related to fair use over the past year. Check out our brief in Hachette Books v. Internet Archive, where we expand on our longtime defense of Controlled Digital Lending as a fair use; our brief in Goldsmith v. Warhol Foundation, where we advocate for a broad yet sensible conception of “transformativeness”; and our brief in Sicre de Fontbrune v. Wofsy, where we explain why fair use is a crucial aspect of U.S. policy and why it should shield authors from the enforcement of foreign copyright judgments where fair use would have protected the use had it occurred in the U.S.

Fair Use and Text Data Mining: Learn about Authors Alliance’s new project, “Text and Data Mining: Defending Fair Use,” intended to support researchers engaging in text and data mining under the recent DMCA exemption for Text Data Mining, generously supported by the Mellon Foundation.

Fair Use and Public Policy: Learn about why we voiced opposition to the SMART Copyright Act of 2022 and the Journalism Competition and Preservation Act—proposed legislation that, if passed, could erode our fair use rights.

Announcing the “Text and Data Mining: Demonstrating Fair Use” Project

Posted December 22, 2022

We’re very pleased to announce a new project for 2023, “Text and Data Mining: Demonstrating Fair Use,” which is generously supported by the Mellon Foundation. The project will focus on lowering and overcoming legal barriers for researchers who seek to exercise their fair use rights, specifically within the context of text data mining (“TDM”) research under current regulatory exemptions.

Fair use is one of the primary legal doctrines that allow researchers to copy, transform, and analyze modern creative works—almost all of which are protected by copyright—for research, educational, and scholarly purposes. Unfortunately, in practice, not everyone is able to use this powerful right. Researchers today face the challenge that fair use is often overridden by a complex web of copyright-adjacent laws. One major culprit is Section 1201 of the Digital Millennium Copyright Act (“DMCA”), which imposes significant liability for users of copyrighted works who circumvent technical protection measures (e.g., content scramble for DVDs), unless those users comply with a series of specific exemptions to Section 1201. These exemptions are lengthy and complex, as is the process to petition for their adoption or renewal, which recurs every three years.

Text data mining is a prime example of work that demonstrates the power of fair use, as it allows researchers to discover and share new insights about how modern language and culture reflect on important issues ranging from our understanding of science to how we think about gender, race, and national identity. Authors Alliance has worked extensively on supporting TDM work in the past, including by successfully petitioning the Copyright Office for a DMCA exemption to allow researchers to break digital locks on films and literary works distributed electronically for TDM research purposes, and this project builds on those previous efforts.

The Text Data Mining: Demonstrating Fair Use project has two goals in 2023:

 1) To help a broader and more diverse group of researchers understand their fair use rights and their rights under the existing TDM exemption through one-on-one consultations, creating educational materials, and hosting workshops and other trainings; and

2) To collect and document examples of how researchers are using the current TDM exemption, with the aim of illustrating how the TDM exemption can be applied and highlighting its limitations so that policymakers can improve it in the future.

We’ll be working closely with TDM researchers across the United States, as well organizations such as the Association for Computers and the Humanities, and will be actively exploring opportunities to work with others. If you have an interest in this project, we would love to hear from you! 

About The Andrew W. Mellon Foundation

The Andrew W. Mellon Foundation is the nation’s largest supporter of the arts and humanities. Since 1969, the Foundation has been guided by its core belief that the humanities and arts are essential to human understanding. The Foundation believes that the arts and humanities are where we express our complex humanity, and that everyone deserves the beauty, transcendence, and freedom that can be found there. Through our grants, we seek to build just communities enriched by meaning and empowered by critical thinking, where ideas and imagination can thrive. Learn more at mellon.org.