Should novel output (such as music, artworks, poems, etc.) generated by artificial intelligence¹ (AI) be protected by copyright? While this question seems straightforward, the answer certainly isn’t. It brings together technical, legal, and philosophical questions regarding “creativity,” and whether machines can be considered “authors” that produce “original” works.

In search of an answer, we ran an admittedly unscientific Twitter poll over five days in June. Interestingly, almost 70% of a total of 338 respondents indicated that novel outputs from an AI system belong in the public domain, while 20% weren’t sure. For example, one commentator said that “since an AI will (given the same inputs and the same model) produce the same output every time, it’s hard to argue it’s unique and creative,” another succinctly argued: “system-generated activities = no creative input, therefore, no copyright,” while another respondent noted that it “depends on the nature of the AI, and the source materials used…I don’t think you could make a blanket rule for all AI.” This question was also debated at the World Intellectual Property Organization’s (WIPO) Conversation on Intellectual Property and Artificial Intelligence (Second Session) held from 7-9 July 2020. To share our general policy views on this topic from a global perspective, Creative Commons submitted a written statement and made two oral interventions (here and here). 

In this blog post, the first in a series on AI and creativity, we explore some of the fundamentals of copyright protection in an attempt to determine whether AI is capable of creating works eligible for copyright protection. In the second blog post, “Artificial Intelligence and Creativity: Can Machines Write Like Jane Austen?“ we walk you through two practical examples of an AI system generating arguably novel content and apply copyright eligibility criteria to them. By doing so, we hope to shed light on some of the copyright issues arising around the nascent field of AI technology.

What works can benefit from copyright protection? 

In order to determine what constitutes a creative work eligible for copyright protection, most national copyright regimes rely on the concepts of authorship and originality, among others. 

The concept of authorship

For a work to be protected by copyright, there needs to be creative involvement on the part of an “author.” At the international level, the Berne Convention stipulates that “protection shall operate for the benefit of the author” (art 2.6), but doesn’t define “author.” Likewise, in the European Union (EU) copyright law,² there is no definition of “author” but case-law has established that only human creations are protected.³ This premise is reflected in the national laws of countries of civil law tradition, such as France, Germany, and Spain, which state that works must bear the imprint of the author’s personality. As AI systems do not have a personality that they could imprint on what they produce, authorship is beyond limits for AI. 

In countries of common law tradition (Canada, UK, Australia, New Zealand, USA, etc.), copyright law follows the utilitarian theory, according to which incentives and rewards for the creation of works are provided in exchange for access by the public, as a matter of social welfare. Under this theory, personality is not as central to the notion of authorship, suggesting that a door might be left open for non-human authors. However, the 2016 Monkey selfie case in the US determined that there could be no copyright in pictures taken by a monkey, precisely because the pictures were taken without any human intervention. In that same vein, the US Copyright Office considers that works created by animals are not entitled to registration; thus, a work must be authored by a human to be registrable. Though touted by some as a way around the problem, the US work-for-hire doctrine also falls short of providing a solution, for it still requires a human to have been hired to create a work, whose copyright is owned by their employer.

As AI systems do not have a personality that they could imprint on what they produce, authorship is beyond limits for AI. 

Nevertheless, some countries (e.g. United Kingdom, Ireland, and New Zealand) do grant copyright-like protection to computer-generated works. The UK Copyright Designs and Patents Act 1988, for example, creates a legal fiction for computer-generated works where there is no human author. Section 9(3) states that “the author shall be taken to be the person by whom the arrangements necessary for the creation of the work are undertaken.” An important nuance is that this provision assumes some form of creative intervention by a human and not autonomous, human-less generation by a computer program alone.  

The originality requirement

Common law jurisdictions generally have a low threshold for originality, requiring only a minimal level of creativity or intellectual labor and independent creation for a work to be protectable. The word “originality” in that context refers to the author as being the “origin” of a work, rather than to any creativity standard.⁴ Some other countries, like Brazil, approach originality from the negative, and state that all works of the (human) mind that do not fall within the list of works that are expressly defined as “unprotected works” can be protected. 

Under EU law and case-law, a work is original if it reflects the “author’s own intellectual creation,”⁵ i.e. the expression of the author’s personal touch and the result of free and creative choices. In short, both EU and US law establish the need for the work to be the proximate (direct) causal result of human action. This implies that AI, as it is currently understood as intelligence completely implemented via computational means, cannot make free and creative choices on its own and that the concept of creativity is not applicable to machines. 

Economics of AI-generated outputs: incentives, markets, and monopolies of exploitation 

Leaving aside theories of copyright protection and the rather abstract concepts of authorship and originality (and the even more hypothetical issue of machines having a personality and owning intellectual property rights), the real question we should ask ourselves relates to the economic environment around AI-generated content. Is there any market for AI-generated content? Do people really want to listen to Nirvana-esque algorithm-produced music or Google’s Deep-mind AI piano prowess, get immersed in the writings of a literary robot, or hang a computer-generated Rembrandt, a nightmarish Van Gogh-reminiscent Starry Night or a blurry portrait of a fictional aristocrat in their living room, not to mention to have to pay for any of that? And if so, would AI-generated products truly compete with artistic and literary works produced by humans, as substitute goods? Would the billions of AI-generated outputs produced faster than any human could produce or even consume, need any exclusivity (which is artificially inseminated in the market by means of a copyright “monopoly” of exploitation) to avoid market failure? 

Of course, AI-technology developers might expect to be incentivized to invest in innovation, research, and development to help solve the world’s problems and to make AI as useful to society as possible. But copyright protection of the “artistic” outputs by an AI system is not the appropriate mechanism to stimulate this development. Unfair competition and patent law (and to a certain extent, existing copyright law protecting software as literary works) are far better suited to stimulate innovation and ensure a return on investment for the development of AI technology. 

AI needs to be properly explored and understood before copyright or any intellectual property issues can be seriously considered.

All said, as much as AI has advanced in the past few years, there exists no clarity, let alone consensus, over how to define the nascent and uncharted field of AI technology. Any attempt at regulation is premature, especially through an already over-taxed copyright system that has been commandeered for purposes that extend well beyond its original intended purposes. AI needs to be properly explored and understood before copyright or any intellectual property issues can be seriously considered. That’s why AI-generated outputs should be in the public domain, at least pending a clearer understanding of this evolving technology.

In the second part of this series, “Artificial Intelligence and Creativity: Can Machines Write Like Jane Austen?” we look at two practical examples of an AI system generating “novel” content and apply the copyright eligibility criteria explained above.

Notes

1. There is as yet no widely accepted definition of “artificial intelligence.” We thus discuss this matter in general terms, and consider, strictly for the sake of discussion, that artificial intelligence is intelligence, or a simulation of intelligence, which is implemented via an automated machine, such as a digital computer.
2. Information Society Directive, 2001/29/EC.
3. Case C-145/10, Eva-Maria Painer v Standard Verlags GmbH 1 December 2011, Court of Justice of the European Union (CJEU).
4. For US case law on the concept of originality, see Alfred Bell & co. v. Catalda Fine Arts, Inc. 191 F2nd, Baltimore Orioles Inc. v. Major League Baseball Players Association, 805 F2nd 663 (7th Cir. 1986) and Feist Publications, Inc. v. Rural Tel. Serv. Co., 499 US 340 (1991).
5. Council Directive 2009/24/EC, Art 1(3), protection of computer programs as “the author’s own intellectual creation”; Database Directive 96/9/EC, Art 3(1); Case C‐5/08, Infopaq, ECLI:EU:C:2009:465; Information Society Directive, 2001/29/EC.

: Featured image is “Love Art Science 95” by Kollage Kid, licensed CC BY-NC-SA 2.0.

The post Artificial Intelligence and Creativity: Why We’re Against Copyright Protection for AI-Generated Output appeared first on Creative Commons.

This post was co-authored by CC’s Open Policy Manager Brigitte Vézina and Legal and Policy Intern Alexis Muscat.

Tomorrow is International Day of the World’s Indigenous Peoples, a day that seeks to raise awareness of and support Indigenous peoples’ rights and aspirations around the world. We at Creative Commons (CC) wish to highlight this important celebration and acknowledge that, internationally, measures need to be taken to protect Indigenous peoples’ rights and interests in their unique cultures. One measure, which intersects with our policy work at CC on Open GLAM, addresses the open, online sharing of Indigenous cultural heritage cared for within cultural heritage institutions. 

Creative Commons and the Open GLAM movement

Many galleries, libraries, archives, and museums (known collectively as “GLAMs”) work hard to make cultural heritage collections available to the public. For these institutions, providing access to knowledge and culture is a core aspect of their duty and public interest mission. Many institutions are digitizing and making cultural heritage collections available online in an effort to both preserve and openly share cultural heritage materials. The Open GLAM movement acknowledges this mission and actively promotes this premise, helping GLAMs make the most out of CC licenses and tools to communicate what users can do with digitized material. At CC, we strongly advocate for open access to public domain material held in GLAM collections for the benefit of all. CC firmly believes that digital reproductions of public domain material within these collections should remain in the public domain and be accessible online as openly as possible.

Indigenous cultural heritage and Open GLAM

Reuse freedoms associated with public domain materials, and fostered through digitization, can create tension when it comes to Indigenous cultural heritage. Existing copyright law, steeped in Western concepts and values, does not adequately protect Indigenous traditional cultural expressions, nor does it sufficiently reflect or account for Indigenous cultural values. By default, many forms of Indigenous heritage or “traditional cultural expressions” (which may include secret, sacred, or sensitive content) are inequitably deemed public domain under conventional copyright law.¹ One of the challenges is that the copyright system does not properly account for the ways in which traditional cultural expressions are created, collectively held, and transmitted through the generations. The copyright eligibility criteria, such as originality and authorship, are often at odds with Indigenous notions of creativity and custodianship over a community’s cultural heritage. As a result, it may seem that such heritage is freely available for use and reuse, when in truth this may not be the case. Permitting this level of access and use raises ethical concerns which must be fully considered.²

Existing copyright law, steeped in Western concepts and values, does not adequately protect Indigenous traditional cultural expressions, nor does it sufficiently reflect or account for Indigenous cultural values.

The notion of the “public domain” is relevant within the confines of the copyright system. So, while Indigenous cultural heritage may be regarded as public domain under copyright rules, and thus free to use, other rights and interests may still attach to it, stemming from various sources. These include other legal restrictions like privacy rights, other intellectual property rights (including sui generis rights to protect traditional cultural expressions), and personality rights, as well as Indigenous customary laws and protocols. In practice, this means that access to and use of Indigenous materials may be limited, and justified, on grounds found outside of the copyright system. Because these rights and interests are not protected under copyright law, they are not licensed under CC’s licenses and tools, which operate solely within the copyright system. This means that specific terms or conditions on access and use that are based on Indigenous rights, interests, or wishes are not fully addressed when applying CC licenses and tools only and that additional measures might be advisable to correctly reflect the conditions associated with access and use of traditional cultural expressions. Local Contexts, a labeling system inspired by Creative Commons, was designed to address this issue by alerting reusers to local protocols established by communities.

GLAMs are in a pivotal position to take active steps in support of Indigenous cultural interests and values. Through thoughtful, intentional, and respectful decision making, GLAMs can enable the ethical treatment of cultural heritage materials, going beyond the application of conventional copyright law and the determination of a work’s public domain status. GLAMs should take account of Indigenous peoples’ rights and interests, particularly regarding digitization, access, and reuse of Indigenous cultural heritage. 

A study of GLAM policies on Indigenous cultural heritage

In an effort to better understand how GLAMs are tackling this tension, we undertook desk-based research aimed at surveying and analyzing GLAM policies and practices dealing with the treatment of Indigenous cultural materials.³ After collecting a diverse range of resources from various GLAMs located in different world regions, we studied them to find common trends, best practices, strategies and rationales. ⁴

We found that some institutions attempt to strike a balance between their aim to share collections openly and the need to prioritize Indigenous peoples’ interests in their cultural heritage. The policies in place at Auckland War Memorial Museum (discussed here with Open GLAM on Medium), Museum of New Zealand Te Papa Tongarewa, and Museum of Applied Arts and Sciences are great examples of institutions working to strike this balance. 

Additionally, we were able to identify three key themes in the surveyed policies: 

1. Acknowledgment—GLAMs should recognize and affirm the interests Indigenous peoples have in their cultural and intellectual property, existing both inside and outside conventional copyright law.
2. Consultation—GLAMs should form authentic and meaningful relationships with source communities, understanding customary law and protocols, and determining community needs and wishes with regard to their cultural heritage. 
3. Guardianship—GLAMs should actively respect community decisions regarding digitization, access, and use, giving Indigenous communities full agency over how their cultural material is treated.

While this research provides us with initial insight, it is only the first step in understanding the important but complex interrelations between the goals of the Open GLAM movement and the celebration of the public domain on the one hand, and the ethical, and at times legal, obligation to respect Indigenous cultural heritage. Looking at institutional policies probes a narrow aspect of a much larger conversation. More work needs to be done, and CC will continue to explore ways to bring attention to this issue. In the meantime, we remain convinced that as far as Indigenous cultural heritage is concerned, GLAMs should acknowledge that access and reuse restrictions might be justified in certain situations. With continued efforts, we hope to better inform the Open GLAM movement of best practices when digitizing and making material available online, accounting for more than just the “public domain” status of Indigenous cultural heritage. 

We remain convinced that as far as Indigenous cultural heritage is concerned, GLAMs should acknowledge that access and reuse restrictions might be justified in certain situations.

Moving forward, we at Creative Commons intend to explore paths to find ways to resolve this tension in the GLAM space and beyond. Ideally, we would like to conduct further research to develop informed policy options, hold open conversations and consultations with relevant stakeholders on these important issues based on the principles of collaboration, inclusivity, and transparency, and continue to clarify how CC licenses and tools work and develop ways to better reflect and account for Indigenous rights and interests in their cultural heritage.

Notes

1. Some countries have sui generis (tailor-made) systems of protection in place designed specifically to protect traditional cultural expressions from misappropriation and misuse. For further information, see WIPO’s “Compilation of Information on National and Regional Sui Generis regimes for the Intellectual Property Protection of Traditional Knowledge and Traditional Cultural Expressions.” However, no such regime exists at the international level. The Intergovernmental Committee of the World Intellectual Property Organization is the forum in which negotiations take place to develop a sui generis international legal instrument for the protection of traditional cultural expressions.
2. In the case of museums, the International Council of Museums (ICOM) Code of Ethics provides one basis for recognizing Indigenous cultural interests as an ethical consideration.
3. For the sake of compatibility, we modeled our approach on the Open GLAM survey.
4. Note that the sample of policies reviewed was relatively small next to the large number of GLAMs. As such, the results are not comprehensive nor are they necessarily representative of GLAM practices more broadly.

The post Sharing Indigenous Cultural Heritage Online: An Overview of GLAM Policies appeared first on Creative Commons.

The Alliance for Excellent Education (All4Ed) just released the second edition of their openly licensed digital image collection, “American Education: Images of Teachers and Students in Action.” This edition features nearly 500 high-quality images of teachers and students licensed Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0).

Captured by Allison Shelly (photojournalist and co-founder of Women Photojournalists of Washington) and funded by the William and Flora Hewlett Foundation, these images portray “deep learning” both before and during the COVID-19 pandemic at the UCLA Community School in Los Angeles and Sutton Middle School in Atlanta. 

“These are some of the final images we have of classroom-based instruction prior to the coronavirus sending students and teachers home for months of online instruction,” said Deborah Delisle, All4Ed president and CEO. “The idea of deeper learning is evolving as schools across the country rethink how they deliver instruction, and we are excited to see what that shift produces in thoughtful, innovative ways of engaging students.”

Browse the free collection!

Here at Creative Commons, we’re especially excited to use these images in relation to our work in Open Education. As we continue advocating for and supporting the development of OER policies globally, the images we use should accurately illustrate the messages we send. That’s why openly licensed stock photography collections (like this one!) that are inclusive and representative is imperative.

Congratulations to the Alliance for Excellent Education on a great collection! 

The post Nearly 500 CC-licensed Education Images are Now Available! appeared first on Creative Commons.

Have you ever wondered who looks for openly licensed images? Or how those images are used? Before we launched CC Search in April 2019, we assumed that the search engine would serve three broad groups of creators:

• Those making designs, imagery, and art
• Those illustrating text, such as bloggers, journalists, or educators
• Those creating videos

It’s been over a year since CC Search moved out of beta (we just celebrated its first birthday!), and we now have a better idea of who we serve and their needs thanks to user feedback and insights derived from anonymized data. We’re excited to share with you what we’ve learned!

Who are our users?

Thanks to extensive feedback and user interviews, we have a better sense of the broad groupings our core users fall into, including 1) educators, 2) students, 3) creators, 4) illustrators, or 5) professionals. By collecting examples indicating how CC-licensed content is used, we also have a clearer picture as to how these groups use the content they find and what they need from us to ensure an even better experience. 

• The Educator is someone who teaches, trains, or coaches at any level of schooling, from early childhood through adult education. They use CC Search to create or illustrate educational materials, such as presentations, handouts, worksheets, and videos. The Educator can be a creator, or an illustrator, but identifies as an educator first, and so the purpose and impact of their work is explicitly defined as for education. Approximately 30% of our users identify as educators. The size and impact of this group is deeply compelling as we structure our ongoing efforts.
• The Student is most commonly someone who is instructed to use CC Search as part of a defined curriculum (such as Code.org) or as part of a class assignment. They are directed to CC Search when learning about copyright or creating something to turn in to their teacher. Teachers using CC Search tell us it is their first choice because they see it as the safest, most comprehensive collection of openly licensed images. Approximately 30% of our users identify as students. One user, a Digital Creativity Advisor at a university in the United Kingdom told us, “I use the Creative Commons search engine with students to help them find great resources for use in their digital artworks but also to help explain the tricky concepts behind Creative Commons licensing. I’m so glad it’s there to make both so much easier.”
• The Creator is a musician getting cover art for their album or a filmmaker adding images to videos or a designer getting inspiration or material for adaptation. They’re not mainstream creators with large budgets, but rather artists pursuing passion projects. This group makes up about 10% of our users. We see this group as distinct from those with an explicit education focus.
• The Illustrator is an author, writer, journalist, blogger, or editor who is looking for a visual accompaniment to a written work. They’re looking for something they can freely use for personal and professional projects alike, some of which may be commercial. About 10% of our users fall into this group.
• The Professional is someone who is using CC Search for business purposes, most commonly for marketing materials, website assets, or merchandise creation. They need content that can be freely used for commercial purposes. The filter mechanisms on CC Search and clear explanations of license restrictions allow this group to reuse with great confidence. About 10% of our users fall into this group.

The remaining 10% or so of our users self-report as other types, often planning to use the work they’ve found for personal reasons, like social media backgrounds, internal decorations, or birthday cards.

While we’ve been able to broadly group our users, which helps us understand their needs and motivations, we’ve also learned that the use cases of openly licensed images are wider than we can possibly imagine or represent through these groupings. We find it particularly heartwarming when a grandparent reports that they are making a picture card for their grandchild and inspiring when a teacher shares a link to a slide deck being used for a history lesson. We’re sincerely grateful to the users who share with us how they’re using the images they find.

Where are they based?

Our goal is to serve a global audience, and we’re actively working to make CC Search more usable in languages besides English. Despite our current limitations, we’re thrilled to see that CC Search is crossing borders. Here are the top 10 countries that users access CC Search from:

1. United States (40%)
2. Israel (6%)
3. United Kingdom (4%)
4. Canada (4%)
5. Spain (3%)
6. Australia (3%)
7. Germany (3%)
8. Brazil (2%)
9. France (2%)
10. India (2%)

In total, we’ve had visitors from 200+ countries and territories. Over 65% of our users were searching in English, with Spanish, Portuguese, French, German, and Russian making up over 20% combined. Over the next few months, we’ll be working to internationalize CC Search so that we can more effectively serve the growing number of users from non-English speaking countries. 

What have they taught us?

There are several ways we keep in touch with the users of CC Search. Some folks send us emails or submit feedback forms, while others chat with us on Twitter or through our Community Slack. Which we welcome you to join! We also have a standing invitation for user interviews to help improve the usability of CC Search and other products we’re building. Our favorite conversations are with users, as we work to understand their pain points and collect candid feedback. These conversations inform what features we focus our efforts on.

In recent months, we’ve had the chance to dig into the myriad of ways that openly licensed images are used, what other types of content would be useful to our current users, and what users miss most about the old search portal for CC-licensed content. We’re happy to report that we’re working on meeting the needs of those who want other sources of content and other types of content.

We’ll soon be rolling out a meta-search feature, both for additional image sources as well as audio and video. This will look familiar to those users who’ve used the old search portal to confidently put the necessary filters in place before searching for CC-licensed content on the broader web. This new feature will allow for a quick jump to results from the likes of Google Images, SoundCloud, YouTube, and more directly from the CC Search interface. We’re also working hard to prepare for the indexing and discovery of CC-licensed audio, which we expect we’ll be able to support by the end of 2020—stay tuned! 

To stay up-to-date on the technical updates that we’ll be making to CC Search throughout 2020, be sure to follow Creative Commons Open Source on Twitter, join #cc-usability in the Creative Commons Slack, or keep an eye on the Active Sprint and Backlog in GitHub! If you want to share your thoughts on CC Search with us directly, fill out this feedback form or schedule a user interview with one of our team members. We’d be thrilled to hear from you!

: Featured image has icons by Valerie Lamm from the “Person” collection licensed CC BY via Noun Project.

The post From Educators to Illustrators: Meet the Users of CC Search appeared first on Creative Commons.

Creative Commons is excited to announce the publication of the Romanian language translations of version 4.0 of the CC License Suite and of the CC0 public domain dedication. These translations will enable approximately 30 million people to understand our licenses in their first or second language! 

We could not be more pleased to see this effort reach a successful conclusion after one year of collaboration among experts from the European Commission. The translations were provided by official translators of the European Commission, coordinated by Pedro Malaquias (Legal Officer – Intellectual Property). The translations were reviewed by George Hari Popescu, our Translation Assistant.

The translations followed the guidelines set in the 3.0 version and kept the same translations for most of the legal words and phrases. The most important change in the 4.0 version is for the word “Share.” The 4.0 suite is an exact translation of the English original version, without adaptations to national laws. Since “Distribuire” is a word used in the Romanian copyright law, the word “Partajare” was chosen for the 4.0 version.

You can find the translations below:

• CC BY 4.0
• CC BY-SA 4.0
• CC BY-NC-SA 4.0
• CC BY-NC 4.0
• CC BY-NC-ND 4.0
• CC BY-ND 4.0
• CC0

Congratulations to everyone who worked on these translations! For more details and links, check out the dedicated Wiki page.

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