Access to Law Wins at D.C. Circuit in ASTM International v. Public.Resource.Org – Public Knowledge

“Today, the U.S. Court of Appeals for the District of Columbia issued its opinion in the case ASTM International v. Public.Resource.Org. 

The Court was asked to consider whether online posting of building codes (and other standards) incorporated into the law by reference constitutes a fair use. Public Knowledge maintains that these standards, once incorporated into law, are no longer protectable by copyright, and filed an amicus brief with Library Futures, EveryLibrary, and Authors’ Alliance arguing this position. The Court of Appeals did not address whether or not these standards remained under copyright, but did hold that posting them online for nonprofit purposes constituted a fair use….”

Canadian Copyright, Fair Dealing and Education, Part Five: Open Textbooks Saving Students Millions of Dollars – Michael Geist

“Adjacent to open access publication of research is the growth of open educational resources and open textbooks, which has been actively encouraged and supported by governments who recognize the benefits of investing in textbooks that can be freely copied, adapted, and distributed with no further licensing costs. The model typically involves an upfront payment for the creation of the materials (often through grants) with the stipulation that the licence that accompanies the resulting works will fully permit free and open use. Copyright lobby groups rarely acknowledge the emergence of these materials, which involve significant public expenditures to create and result in a long-term cost savings for educational institutions and their students. 

For example, the Ontario Government has provided funding for post-secondary institutions to create virtual open access resources. eCampusOntario’s Virtual Learning Strategy (VLS) funding engaged Ontario’s post-secondary sector and resulted in the creation of hundreds new virtual educational resources. Other initiatives include Open Education Alberta (run by the University of Alberta), which offers 39 high-quality open educational resources through a partnership with five universities, three colleges, and four other educational institutions as well as BC Campus, which features hundreds of open textbooks. By August 2022, a total of 267,924 British Columbia students were using open textbooks. In 2020/21, 43 educational institutions across the province had replaced course materials with an open textbook – a practice known as adopting. Since 2019, there has been a 70% increase in the number of open textbook adoptions across B.C.

One of the clearest benefits are the cost savings for students. During 2020/21, around 9,000 students at the University of Saskatchewan used open textbooks instead of commercial texts, saving them about $800,000 collectively. Since the University launched its open textbook initiative in 2014, students have saved more than $2.5 million at that one university alone. Investments in the area continue as the University of British Columbia’s 2021/22 budget committed $2.5 million in future years to expand existing learning enhancements, technology tools, and open educational resources….”

Fair Use Week 2023 (10th Anniversary): Day Two With Guest Expert Prof. Pia Hunter | Copyright at Harvard Library

“One question that has emerged frequently these past three years, is how? How have libraries provided access to copyrighted materials for remote users? How were students able to access copyrighted materials at the height of the pandemic? When we think of a classroom, most of us consider a traditional space with walls and students together in one room. The logistics for students to access library materials from their homes seemed insurmountable to some because the copyright laws surrounding how students and teachers can gain remote access is complex. Section 110(1) sets a generous standard for how content may be used, but it only applies to face-to-face instruction. Section 110(2), the TEACH Act, allows the digital transmission of copyrighted materials, but only under limited circumstances and the requirements are difficult for many educational institutions to achieve. With these competing sections of the Copyright Act, what was the solution?…

Although the IA had announced their intention to end the emergency access by June 30, 2020, they ended the program two weeks early when publishers Hachette, Penguin Random House, Wiley, and HarperCollins announced that they would sue the IA for copyright infringement. On June 1, 2020, the publishers and several authors filed a complaint in the United States District Court for the Southern District of New York. But this case, Hachette v. Internet Archive, is not about the expanded access IA provided during the pandemic. It is a challenge to how we can use materials in a digital age and how fair use supports our right to do so….”

Fair Use Week 2023 (10th Anniversary): Day Two With Guest Expert Prof. Pia Hunter | Copyright at Harvard Library

“One question that has emerged frequently these past three years, is how? How have libraries provided access to copyrighted materials for remote users? How were students able to access copyrighted materials at the height of the pandemic? When we think of a classroom, most of us consider a traditional space with walls and students together in one room. The logistics for students to access library materials from their homes seemed insurmountable to some because the copyright laws surrounding how students and teachers can gain remote access is complex. Section 110(1) sets a generous standard for how content may be used, but it only applies to face-to-face instruction. Section 110(2), the TEACH Act, allows the digital transmission of copyrighted materials, but only under limited circumstances and the requirements are difficult for many educational institutions to achieve. With these competing sections of the Copyright Act, what was the solution?…

Although the IA had announced their intention to end the emergency access by June 30, 2020, they ended the program two weeks early when publishers Hachette, Penguin Random House, Wiley, and HarperCollins announced that they would sue the IA for copyright infringement. On June 1, 2020, the publishers and several authors filed a complaint in the United States District Court for the Southern District of New York. But this case, Hachette v. Internet Archive, is not about the expanded access IA provided during the pandemic. It is a challenge to how we can use materials in a digital age and how fair use supports our right to do so….”

Fair Use: Training Generative AI

Like the rest of the world, CC has been watching generative AI and trying to understand the many complex issues raised by these amazing new tools. We are especially focused on the intersection of copyright law and generative AI. How can CC’s strategy for better sharing support the development of this technology while also respecting the work of human creators? How can we ensure AI operates in a better internet for everyone? We are exploring these issues in a series of blog posts by the CC team and invited guests that look at concerns related to AI inputs (training data), AI outputs (works created by AI tools), and the ways that people use AI. Read our overview on generative AI or see all our posts on AI.

Generated by AI: An oil painting in the style of Pieter Jansz Saenredam of a robot learning to follow a recipe in a Dutch kitchen with a large collection of tiny artworks arranged haphazardly on shelves.“Robot Training” by Creative Commons was generated by the DALL-E 2 AI platform with the text prompt “an oil painting in the style of Pieter Jansz Saenredam of a robot learning to follow a recipe in a Dutch kitchen with a large collection of tiny artworks arranged haphazardly on shelves.” CC dedicates any rights it holds to the image to the public domain via CC0.

While generative AI as a tool for artistic expression isn’t truly new — AI has been used to create art since at least the 1970s and the art auction house Christie’s sold its first piece of AI artwork in 2018 — the past year launched this exciting and disruptive technology into public awareness.  With incredible speed, the development and widespread availability of amazing tools like Stable Diffusion and Midjourney have engendered excitement, debate, and indeed fear over what the future may hold and what role generative AI should have in the production of creative works.

Perhaps unsurprisingly to anyone who has been paying attention to the conversation around generative AI, the past year also saw the first lawsuits challenging the legality of these tools. First, in November, a group of programmers sued Github and OpenAI over the code generation tool, Github Copilot, alleging (among other things) that the tool improperly removes copyright management information from the code in its training data, in violation of the Digital Millennium Copyright Act, and reproduces code in its training data without following license agreement stipulations like attributing the code to its original author. Then, in January, a group of artists (represented by the same attorneys as in the Github lawsuit) sued Stability AI and Midjourney over their text-to-image art generation tools. In this second lawsuit, the artist-plaintiffs made several claims, all of which deserve discussion. In this blog post, I will address one of those claims: That using the plaintiffs’ copyrighted works (and as many as 5 billion other works) to train Stable Diffusion and Midjourney constitutes copyright infringement. As Creative Commons has argued elsewhere, and others agree, I believe that this type of use should be protected by copyright’s fair use doctrine. In this blog post I will discuss what fair use is, what purpose it serves, and why I believe that using copyrighted works to train generative AI models should be permitted under this law. I will address the other claims in both the Github and Stable Diffusion lawsuits in subsequent blog posts.

Copyright for public good

It is clear from both the history and origin of copyright law in the United States that copyright’s purpose is to serve the public good. We can see this in the Constitution itself. Article I, section 8, clause 8 of the U.S. Constitution gives Congress the power to create copyright law. This provision states that copyright law must “promote the Progress of Science and useful Arts” and that copyright protection can only last for “limited times.” As such, any copyright law that Congress passes must be designed to support the creation of new creation works and that copyrights must eventually expire so that the collection of works that are free for us all to use — the public domain — will grow and nurture further creative endeavors. However, even while the ultimate beneficiary of copyright may be the public, the law attempts to achieve these goals by giving rightsholders several specific ways to control their works, including the right to control the reproduction and distribution of copies of their works.

With this design, copyright law attempts to strike a balance between the interests of both rightsholders and the public, and when that balance breaks down, copyright cannot achieve its goals. This is where fair use comes from. Shortly after the first copyright law, courts began to realize that it would frustrate copyright’s ability to benefit the public if rightsholders had an unlimited right to control the reproduction and distribution of their works. So, in 1841, Judge Joseph Story first articulated what would become eventually the modern test for fair use in Folsom v. Marsh. As part of that decision, he wrote that downstream uses of copyrighted works that do not “supersede the objects” of the original works should be permitted under the law.

Generated by AI: A chrome-skinned robot face with a blue glow behind its eyes and nose, looking out from the inside of a complex black and white machine.“Fair Use Training Generative AI” by Creative Commons was generated by the Stable Diffusion AI platform with the text prompt “Fair Use Training Generative AI.” CC dedicates any rights it holds to the image to the public domain via CC0.

What is fair use?

Today, fair use, codified at 17 USC 107, is unquestionably an essential part of copyright law in the United States. Courts, including the Supreme Court, have repeatedly emphasized the importance of fair use as a safeguard against the encroachment on the rights of people to use copyrighted works in ways that rightsholders might block. Unfortunately, however, fair use is a famously hard doctrine to apply. Courts repeatedly write that there are no bright lines in what is or is not fair use and each time we consider fair use we must conduct a case-by-case analysis. To that end, the law requires courts to consider four different factors, in light of the purpose and goal of copyright law. These factors are: 1. The purpose and character of the use, or what the user is doing with the original work; 2. The nature of the original work; 3. The amount and substantiality copied by the secondary use; and 4. Whether the secondary use harms the market for the original.

Even though there are no bright lines, there are some principles we can look to when weighing the four fair use factors that courts tend to consider for a finding of fair use and that are particularly relevant for how we may think about fair use and generative AI training data. First, and perhaps most importantly, is whether the secondary use “transforms” the original in some way, or if it “merely supersede[s]” the original. Since 1994, when the Supreme Court adopted “transformativeness” as part of the inquiry about the purpose and character of the secondary use in Campbell v. Acuff Rose Music, this question has grown increasingly important. Today, if someone can show that their secondary use transforms the original in some way, it is much more likely to be fair use then otherwise. Importantly, however, last October, the Supreme Court heard Andy Warhol Foundation v. Goldsmith, which may change how we approach transformativeness in fair use under U.S. law. Nevertheless, it still seems likely that highly transformative uses will weigh in favor of fair use, even after the decision in that case. Second, when considering the nature of the original work, we need to remember that copyright protects some works a bit more strongly than others. Works that are fiction or entirely the creative products of their authors are protected more strongly than nonfiction works because copyright does not protect facts or ideas. As such, uses of some works are less likely to be fair use than others. Third, we need to think about how much of the original work is copied in the context of the transformativeness inquiry, and whether the amount copied serves the transformative purpose. If the amount copied fits and supports the transformative purpose, then fair use can support copying entire works. Fourth, when we consider market harm, we need to think about whether the secondary use undermines the market for or acts as a market substitute for the original work. And finally, we need to consider whether permitting a secondary use as a fair use would serve the goals of copyright.

Is AI transformative?

Given all this background on fair use, how do we apply these principles to the use of copyrighted works as AI training data, such as in the Stable Diffusion/Midjourney case? To answer this question, we must first look at the facts of the case. Dr Andrés Guadamuz has a couple excellent blog posts that explain the technology involved in this case and that begin to explain why this should constitute fair use. Stability AI used a dataset called LAION to train Stable Diffusion, but this dataset does not actually contain images. Instead, it contains over 5 billion weblinks to image-text pairs. Diffusion models like Stable Diffusion and Midjourney take  these inputs, add “noise” to them, corrupting them, and then train neural networks to remove the corruption. The models then use another tool, called CLIP, to understand the relationship between the text and the associated images. Finally, they use what are called “latent spaces” to cluster together similar data. With these latent spaces, the models contain representations of what images are supposed to look like, based on the training data, and not copies of the images in their training data. Then, user focused applications collect text prompts from users to generate new images based on the training data, the language model, and the latent space.

Turning back to fair use, this method of using image-text combinations to train the AI model has an inherently transformative purpose from the original images and should support a finding of fair use. While these images were originally created for their aesthetic value, their purpose for the AI model is only as data. For the AI, these image-text pairs are only representations of how text and images relate. What the images are does not matter for the model — they are only data to teach the model about statistical relationships between elements of the images and not pieces of art.

This is similar to how Google used digital copies of print books to create Google Books, a practice that was challenged in Author’s Guild v. Google (Google Books). In this case, the Second Circuit Court of Appeals found that Google’s act of digitizing and storing copies of thousands of print books to create a text searchable database was fair use. The court wrote that Google’s purpose was different from the purpose of the original authors because Google was not using the books for their content. Indeed, the content did not really matter to Google; rather the books were like pieces of data that were necessary to build Google’s book database. Instead of using the books for their content, Google’s purpose was to create a digital tool that permitted new ways of using print books that would be impossible in the analog world. So, the books as part of Google’s database served a very different purpose from their original purpose, which supported the finding of fair use in this case.

Moreover, it is also similar to how search engine operator Arriba Soft used copies of images in its search engine, which was litigated in Kelly v. Arriba Soft. In this case, a photographer, Leslie Kelly, sued the operator of a search engine, Arriba Soft, for copying and displaying copies of her photographs as thumbnails to users. The court, however, disagreed that this constituted copyright infringement. Instead, the court held that this use served a different and transformative purpose from the original purpose because Arriba Soft only copied Kelly’s photographs to enable its search engine to function and not because of their aesthetic value. Like Google Books, and like AI training data, the images here served a function as data for the tool, not as works of art to be enjoyed as such.

On the nature of works as AI inputs

Turning to factor two, the nature of the original works, even though we do not know what specific images are in the LAION dataset used to train Stable Diffusion and Midjourney, it is likely that these images involve a wide range of creativity. While this could weigh against a finding of fair use for Stable Diffusion and Midjourney, given the presumably creative nature of the input works, this factor is rarely determinative. In fact, in Google Books, the court was skeptical that this factor would weigh against fair use even if the books in the database were fiction. This is because using the digitized books as part of the database provided information about the books and did not use them for their creative content.  Similarly in the litigation against Stable Diffusion and Midjourney, these generative AI tools use the works in their dataset as data. In this, anything they extract from their training data might only be unprotectable elements of the works in the training data, such as facts and ideas about how various concepts are visualized.  As such, because this factor is rarely a major factor in fair use decisions, it seems unlikely that this factor should weigh heavily against fair use in this case.

Is AI making copies?

Third, because of how the generative AI models work, they use no more of the original works than is necessary when used for training to enable the transformative purpose. The models do not store copies of the works in their datasets and they do not create collages from the images in its training data. Instead, they use the images only as long as they must for training. These are merely transitory copies that serve a transformative purpose as training data. Again, Google Books is helpful to understand this. In that decision, the Court wrote that Google needed to both copy and retain copies of entire books for its database to function. But this was permissible because of Google’s transformative purpose. Furthermore, Google did not permit users to access full copies of the books in the database, but instead, it only revealed “snippets” to the users. On this point, the court wrote that the better question to answer was not how much of the works Google copied, but instead how much was available to users. Similarly, Stability AI and Midjourney would not work unless they used the entire images in their training datasets. Moreover, they do not store images, they do not reproduce images in their data sets, and they do not piece together new images from bits of images from their training data. Instead, they learn what images represent and create new images based on what they learn about the associations of text and images.

AI in the marketplace

Fourth, the issue of whether Stable Diffusion and Midjourney harm the market for the works in their training data is difficult, in part because the way that courts think of this question can be a bit inconsistent. In one way, the answer must be yes, this use at least has the potential to harm the market for the original. That is, after all, one likely reason the plaintiffs filed this lawsuit in the first place — they are afraid that AI generated content will cut into their ability to profit off of their art. Indeed, any art has the potential of competing with other art, not necessarily because it fills the same niche, but because attention is limited, and AI generated content has the advantage of being able to be made in a quick, automated fashion. However, this may not be the best way to think about market harm in the context of using images as training data. As mentioned above, we need to think about this question in the context of the transformative purpose. In Campbell v. Acuff Rose, the Supreme Court wrote that the more transformative the purpose, the less likely it is that it will be a market substitute for the original. Given this, perhaps it is better to ask whether this use as training data, not as pieces of art, harms the market for the original. This use by Stability AI and Midjourney exists in an entirely different market from the original works. It does not usurp the market of the original and it does not operate as a market substitute because the original works were not in the data market. Moreover, this use as training data does not “supersede the objects” of the originals and does not compete in the aesthetic market with the originals.

Training AI as fair use

Finally, as discussed above, since the purpose of copyright law is to encourage the new creative works, to promote learning, and to benefit the public interest, fair use should permit using copyrighted works as training data for generative AI models like Stable Diffusion and Midjourney. The law should support and foster the development of new technologies that can provide benefits to the public, and fair use provides a safeguard against the cudgel of copyright being used to impede these technologies. As Mark Lemley and Bryan Casey write in a recent paper arguing that this type of use should constitute fair use:  “A central problem with allowing copyright suits against ML [machine learning] is that the value and benefit of the system’s use is generally unrelated to the purpose of copyright.” In fact, the Supreme Court has recognized fair use’s importance in the development of new technologies, first in 1984, in Universal City Studios v. Sony and most recently in 2021 in Google v. Oracle. In Sony, the Court held that the Betamax videocassette recorder should not be sued out of existence even if it could potentially help people violate copyright law. Instead, because it held “substantial, non infringing uses”, the Court believed copyright law should not be used to stop it. Then in Google, the Court held that Google’s use of Google’s 11,500 lines of Java code was fair use, writing that the courts must consider fair use in the context of technological development.

Altogether, I believe that this type of use for learning purposes, even at scale by AI, constitutes fair use, and that there are ways outside of litigation that can offer authors other ways to control the use of their works in datasets. We can already see an example of this, to a degree, when Stability AI announced that it would permit artists to opt out of having their works used for training Stable Diffusion. While this certainly isn’t a perfect solution, and opt-out is just one possible way to approach these issues, it is at least a start, and it highlights that there are ways to address these problems other than through copyright-based solutions. Perhaps by looking at norms and best practices and by engaging people in collaboration and dialogue we can better address the concerns raised by AI training data, instead of falling back on lawsuits that force the different sides of this issue into opposition and that can create unpredictable and potentially dangerous new precedent for future technologies.

The post Fair Use: Training Generative AI appeared first on Creative Commons.

Our Digital History Is at Risk – Internet Archive Blogs

“Publishers and platforms continue to play an important role in bringing the work of creators to market, and sometimes assist in the preservation task. But companies close, and change hands, and their commercial interests can cut against preservation and other important public benefits. 

Traditionally, libraries and archives filled this gap. But in the digital world, law and technology make their job increasingly difficult. For example, while a library could always simply buy a physical book on the open market in order to preserve it on their shelves, many publishers and platforms try to stop libraries from preserving information digitally. They may even use technical and legal measures to prevent libraries from doing so. While we strongly believe that fair use law enables libraries to perform traditional functions like preservation and lending in the digital environment, many publishers disagree, going so far as to sue libraries to stop them from doing so. 

We should not accept this state of affairs. Free societies need access to history, unaltered by changing corporate or political interests. This is the role that libraries have played and need to keep playing. This brings us back to Twitter….”

Fair Use Creep Is A Feature, Not a Bug

“Fair use is essential to internet for at least two reasons. First, the vast majority of what we do online, from email to texting to viewing images and making TikToks, involves creating, replicating, and/or repurposing copyrighted works. Since copyright is a limited but lengthy monopoly over those works, in theory, using or even viewing them might require a license; now, and for many decades in the future.

Second, technological innovation rarely means starting from scratch. Instead, developers build on existing technologies, hopefully improving them. But if the technology in question involves code, it is likely copyrightable. If so, that add-on innovation might require a license from the rightsholder, giving them a veto right on technological development.

As digital technologies dramatically (and sometime controversially) expand the reach of copyright, fair use helps ensure that the rights of the public expand as well….

In Hachette v. Internet Archive, four of the biggest publishers in the world, are trying to shut down Controlled Digital Lending, which allows people to check out digital copies of books for two weeks or less and only permits patrons to check out as many copies as the Archive and its partner libraries physically own. That means that if the Archive and its partner libraries have only one copy of a book, then only one patron can borrow it at a time….

Fortunately for the public, fair use has likewise grown to protect the original purpose of copyright: to encourage forward progress. And no matter what Hollywood or John Deere tells you, that’s a feature, not a bug.”

Internet Archive Files Final Reply Brief in Lawsuit Defending Controlled Digital Lending – Internet Archive Blogs

“On Friday, October 7, the Internet Archive filed a reply brief against the four publishers that sued Internet Archive in June 2020: Hachette Book Group, HarperCollins Publishers, John Wiley & Sons, and Penguin Random House. This is the final brief in support of our motion for summary judgment (our previous motions can be found here and here) where we have asked the Court to dismiss the lawsuit because our lending program is a fair use….”

The GLAM Fam! Transformative Use and Creativity in Galleries, Libraries, Archives, and Museums

“Did you enjoy our Fandoms, Fan Fiction, and Fair Use: Transformative Use For Creators session on August 17th? Join Library Futures to learn more about creativity and transformative use from a team of GLAM experts!

Galleries, Libraries, Archives, and Museums curate, preserve, and display creative works that serve to inform and inspire continued innovation. Without transformative use, both GLAM institutions’ ability to provide these services and their patrons’ ability to create are endangered.
Join Library Futures Fellow Emily Finch in the second session of a two part series on transformative and fair use. Moderated by University of Illinois College of Law’s Associate Director for Research and Instruction Pia M. Hunter, the session will feature Brigitte Vèzina, Creative Commons’ Director of Policy, Open Culture, and GLAM, George Oates, Founder and Executive Director of the Flickr Foundation, and Douglas McCarthy Collections Engagement Manager, Europeana Foundation and Co-Founder and Editor of the Open GLAM Survey. Learn more Learn more about the role fair use, and especially transformative use, plays in GLAM institutions, in platforms and the sharing of creative content, and where the Warhol v. Goldsmith case stands to affect GLAM institutions and their users. Featuring a presentation by Policy Fellow Juliya Ziskina.”

How Smart is the SMART Copyright Act? – Diff

“During March 2022, United States Senators Patrick Leahy and Thom Tillis introduced the Strengthening Measures to Advance Rights Technologies Copyright Act of 2022 (SMART Copyright Act). The bill is deceptively simple. It would require the Library of Congress to mandate that online platforms use certain “technical measures” (i.e., automated systems) to identify infringing content. Its simplicity masks its dangers, however. For that reason, though the Wikimedia Foundation agrees that technical measures to identify potentially infringing works can be useful in some circumstances, we sent a letter (reproduced below) on 19th April 2022 to the bill’s sponsors letting them know that we oppose it. 

Under the SMART Copyright Act, the Foundation and Wikimedia communities could be forced to accommodate and implement technical tools to identify and manage copyrighted content that may not be right for Wikimedia projects. This requirement could force the Foundation to change its existing copyright review process, even though the current process is working very well. …

While we fully agree that tools can be a helpful aid in identifying infringement, they should not be considered as a fix for all enforcement problems. There are two main reasons for this:

Technical tools are not good at determining when a work was “fairly used” or when a work has entered the public domain. This flaw leads to inappropriate censorship. Even YouTube’s Content ID identifies numerous false positives for infringement, and fails to catch a significant amount of problematic content. We worry that such tools would do far worse than the Wikipedia non-free content policy enforced by users.
Technical tools are often developed and owned by one company, and are not open source or freely available. If specific tools are mandated by the copyright office, this would make it difficult for smaller companies and nonprofits to use them without becoming overly reliant on those companies….”

Authors Alliance Opposes the SMART Copyright Act of 2022 | Authors Alliance

“Last week, Senators Thom Tillis and Patrick Leahy introduced new legislation regarding technical protection measures used to protect copyrighted works online, entitled the Strengthening Measures to Advance Rights Technologies (SMART) Copyright Act of 2022. This new legislative proposal represents the latest in a multi-pronged effort to fortify protections for copyrighted works online (coming on the heels of the Copyright Office’s recent notice of inquiry about the development of technical protection measures, about which Authors Alliance submitted a comment). If passed, the SMART Copyright Act of 2022 would establish a procedure for the Librarian of Congress to designate standardized protection measures (“STMs”) to be adopted by online service providers. 

Authors Alliance strongly opposes the SMART Copyright Act of 2022. By requiring that digital platforms and service providers implement technical protection measures which could monitor content uploaded by users, the SMART Copyright Act of 2022 could lead to content “filtering mandate[s]” interfering with authors’ and other creators’ abilities to speak freely online. Authors and creators are the parties that copyright law is designed to protect, making the proposal one that is inconsistent with the very purposes of copyright. 

The SMART Copyright Act of 2022 would enable the Librarian of Congress to designate STMs to be implemented across industries, supposedly based on input from a diverse group of stakeholders. While the bill’s sponsors claim that the legislation “ensures that any designation of existing measures requires input from all stakeholders and assessment of public interest considerations,” it is telling that groups representing the content industry have praised the proposed legislation, while proponents of fair use and the free exchange of knowledge have opposed it. Even if the Copyright Office were to develop STMs that reflect a broad consensus across a diverse group of stakeholders, this would leave out the stakeholders who do not favor the widespread implementation of STMs in the first place (like Authors Alliance). Mandating that service providers use content moderating technology would impede the free flow of information and would not serve the interests of authors and creators who prioritize seeing their works reach wide audiences. …”

Little mermaid, long copyright, big absurdity – Walled Culture

“The reason the heirs were able to bring the case is because Eriksen died in 1959, and so under Danish law his work remains covered by copyright until 2029. The statue was unveiled in 1913, which means that the sculptor’s heirs are still claiming payments well over a hundred years after it was made. Copyright is supposed to be an incentive to create, but it’s absurd to claim that artists are motivated by the thought of earning money for decades after they have died….”

Harvard Library Celebrates Ninth Annual Fair Use Week | Harvard Library

“February 21–25, 2022 is the ninth annual International Fair Use Week — celebrated at libraries, archives, museums and other institutions around the world in recognition of an element of copyright law critical to research, education and scholarship.

Without fair use, scholars would be unable to quote from sources; journalism would be unable to produce articles; thesis and dissertation writers would be unable to offer criticism or analysis of other works; professors would be unable to use music or film in classrooms; libraries would be unable to digitize their print materials — the list of necessary actions that would be affected goes on and on….

Harvard Library’s Office for Scholarly Communication (OSC) founded the first week-long celebration of fair use in 2014. As it was my first year as Copyright Advisor, in a new position, I was looking for something big to accomplish. The idea for a celebration was posted on the Fair Use Allies listserv by Prof. Pia Hunter, now Teaching Associate Professor at University of Illinois College of Law. That very year, Prof. Hunter bought the website fairuseweek.org ahead of the annual celebration. In the second year of Fair Use Week the site went live, and, now run by the Association of Research Libraries (ARL), it continues to serve as the central spot for covering all things Fair Use Week….”

Updating the UCI IPAT Fair Use Jurisprudence Project for Fair Use Week 2022

“Last year, in celebration of Fair Use Week, the IPAT clinic took a deep dive into fair use. We looked at every written judicial opinion that discussed fair use from the beginning of 2019 through February 2021, and made them available in a searchable, sortable database with abstracts and commentary and links to copies of every single case. We learned a lot, and the resources we made available were used by many scholars, students, and attorneys across the country….

For Fair Use Week 2022, we’ve returned to the Fair Use Jurisprudence Project to analyze and present another year’s worth of fair use cases. Our first observation is that the rate of fair use activity has continued to increase. We logged 64 opinions discussing fair use in 2021, increasing from 45 in 2020 and 22 in 2019. Go here for the abstracts.  Photographs continue to be the most common type of work at issue in these disputes, with 67 of the 132 total cases from 2019 to 2022 relating to their use. Of course, not all photograph cases come out the same way. Online news sites, web storefronts, bloggers and artists have all claimed fair use as a defense against photograph infringement claims, with varying results….”

 

Singapore starts making its copyright law fit for the digital world; others need to follow its example – Walled Culture

“Singapore’s previous copyright law provided a broad “fair dealing” right that allowed a range of general uses.  The title of this exception has now been changed from “fair dealing” to “fair use.” That might seem a trivial change, but it’s significant.  Fair dealing rights are, in general, more limited than fair use ones.  The adoption of the latter term is further confirmation that Singapore’s new Copyright Law is moving in the right direction, and aims to provide greater freedoms for the general public, rather than fewer, as has so often been the case in this sector.”