In 2022, two working groups (WGs) of the Creative Commons Copyright Platform collaborated on policy papers tackling issues related to copyright and access to knowledge. In this blog post, we highlight their insightful contributions to the CC copyright reform community.
Working Group on Digital Sharing Spaces
Led by Emine Yildirim, the WG on Digital Sharing Spaces was based on the idea that recent and upcoming legislative and policy instruments are likely to affect freedom to share. In 2022, the WG focused on how data sharing policies concerning publicly available data impact academic research and journalism in the public interest. While the group found that there are some safeguards in place, there are also several barriers for utilizing publicly available data by researchers and journalists. The main output of the WG was a position paper, encompassing two jurisdictions, the European Union and the United States. With this position paper, the group sought to provide some preliminary recommendations and to call for action and engagement to those who may be facing challenges and barriers in their respective jurisdictions. Watch the group’s January 2023 webinar recording. The WG hopes to use this position paper as a conversation starter for a bigger and more geographically inclusive debate.
Led by André Houang, the WG on User Rights was based on the idea that these rights are an integral part of the copyright system. As such, the WG focused on exchanging thoughts on how copyright can be reshaped to better balance the interests of authors and rights holders with the public interest, so as to allow for the full exercise of fundamental rights, such as freedom of expression and access to knowledge, culture and information. The main output of the WG are its position papers, in which it puts forward some ideas for a better copyright system. The WG´s 2021 position paper focused on different types of user rights, which could help balance the interests of rights holders and of users. The 2022 position paper approached the topic of an international instrument for the global harmonization of user rights, and you can watch the group’s webinar recording to hear more about it.
Hala says “if it’s open then you give a big opportunity for partnership” because the transparency created by openness makes it clear what you do and what you have and invites others to work with you. In this episode Hala shares some insight on copyright in Egypt and what open culture looks like in the work she does.
Open Culture VOICES is a series of short videos that highlight the benefits and barriers of open culture as well as inspiration and advice on the subject of opening up cultural heritage. Hala is the Head of the Legal Department at the Library of Alexandria. With more than 25 years of experience she has worked on IP and Copyright issues around the world with her work the library and with WIPO.
Hala responds to the following questions:
What are the main benefits of open GLAM?
What are the barriers?
Could you share something someone else told you that opened up your eyes and mind about open GLAM?
Do you have a personal message to those hesitating to open up collections?
Closed captions are available for this video, you can turn them on by clicking the CC icon at the bottom of the video. A red line will appear under the icon when closed captions have been enabled. Closed captions may be affected by Internet connectivity — if you experience a lag, we recommend watching the videos directly on YouTube.
Looking for that perfect picture to illustrate your post? That catchy tune to jazz up your video? Look no further than Openverse, the huge library of free and open stock photos, images, and audio contributed to the public commons by people around the world, now available at its new domain: openverse.org.
Here at CC we use Openverse daily to explore the public commons and find works to reuse in our communications and projects. Powerful tools like Openverse demonstrate how open technologies and communities like WordPress can build on the rich public commons we all help create to support what we call better sharing: sharing that is inclusive, just and equitable — where everyone has wide opportunity to access content, to contribute their own creativity, and to receive recognition and rewards for their contributions.
Finding and using free and open works has never been easier: Just visit Openverse, enter some keywords, and pick your favorite from the results. You can also filter by content type, sources, aspect ratio, size, open license and public domain statuses, and more, like the search for the keywords “art” and “universe” we used to find the image in this post.
Once you’ve picked a work, Openverse provides everything you need to use it: Visit the work in its home collection and copy a well-formed attribution statement to give proper credit for your use.
Openverse was incubated here at CC as “CC Search”, moving to the WordPress community in 2021, and has continued to thrive in its new home, now cataloging over 600 million images and audio tracks, with new collections of open works being added all the time, like the recent addition of more than 15 million images from iNaturalist, the project that enables citizen scientists and researchers to document and understand global biodiversity.
Contributors in the WordPress community continue to add new features and capabilities to Openverse. Coming up next will be new tools to easily use images from Openverse directly in WordPress itself; content safety features that will enable users to blur or opt in/out from specific types of sensitive content; and improvements to search relevancy and the quality of results.
Nicole believes that “the greatest advantage of open cultural heritage is digital equity,” which is a guiding principle for many cultural institutions around the world. In this episode Nicole talks about how making collections open greatly increases accessibility across global demographics and interest groups which makes an institution more relevant to a wider audience.
Open Culture VOICES is a series of short videos that highlight the benefits and barriers of open culture as well as inspiration and advice on the subject of opening up cultural heritage. Nicole is at the time of the recording the Director of Global Strategic Initiatives at CLIR which is the Council on Library and Information Resources where she works to enhance research, teaching, and learning environments in collaboration with libraries, cultural institutions, and communities of higher learning.
Nicole responds to the following questions:
What are the main benefits of open GLAM?
What are the barriers?
Could you share something someone else told you that opened up your eyes and mind about open GLAM?
Do you have a personal message to those hesitating to open up collections?
Closed captions are available for this video, you can turn them on by clicking the CC icon at the bottom of the video. A red line will appear under the icon when closed captions have been enabled. Closed captions may be affected by Internet connectivity — if you experience a lag, we recommend watching the videos directly on YouTube.
“Better Sharing With AI” by Creative Commons was generated by the DALL-E 2 AI platform with the text prompt “A surrealist painting in the style of Salvador Dali of a robot giving a gift to a person playing a cello.” CC dedicates any rights it holds to the image to the public domain via CC0.
Over the last year, innovation and use of generative artificial intelligence (AI) has exploded, providing new ways for people to create content of all sorts. For example, it’s been used to help create award winning art, develop educational materials, expedite software development, and craft business materials. Recently, three artists filed a class action lawsuit in the USA against StabilityAI and Midjourney, two companies that use the Stable Diffusion tool to enable people to generate images using simple text prompts. It follows on the heels of litigation brought by the same attorneys and other plaintiffs against GitHub and OpenAI for their Copilot and Codex tools for generating software code.
AI is an area that Creative Commons has longfocused on, including most recently in a webinar series we held last fall. We are going to expand on our views in future posts, including exploring why we think the legal arguments in the US court case against StabilityAI, Midjourney, and DeviantArt are ill-founded. (Getty Images also subsequently filed a similar suit against StabilityAI in the US, as well as apparently commencing litigation in the UK, but we have yet to see that complaint.)
But before digging into all of the legal issues, we wanted to take a step back and restate our general approach to generative AI.
CC on Generative AI
Creative Commons has always sought out ways to harness new technology to serve the public interest and to support better sharing of creative content — sharing that is inclusive, just, equitable, reciprocal and sustainable. We support creators to share their works as broadly and openly as they want, so that people can enjoy them globally without unnecessary barriers. We also advocate for policies that ensure new and existing creators are able to build on a shared commons, while respecting creators’ legitimate interests in control and compensation for their creative expressions.
A founding insight of Creative Commons is that all creativity builds on the past. When people learn to play the cello or paint a picture, for instance, they necessarily learn from and train their own skills by engaging pre-existing works and artists — for instance, noticing the style in which cellists like Yo-Yo Ma arrange notes, or building on surrealist styles initiated by artists like Dali. Similarly, while Star Wars invented the character of Luke Skywalker, it built on the idea of the hero’s journey, among many other elements from past works. People observe the ideas, styles, genres, and other tropes of past creativity, and use what they learn to create anew. No creativity happens in a vacuum, purely original and separate from what’s come before.
Generative AI can function in a similar way. Just as people learn from past works, generative AI is trained on previous works, analyzing past materials in order to extract underlying ideas and other information in order to build new works. Image generation tools like Stable Diffusion develop representations of what images are supposed to look like by examining pre-existing works, associating terms like “dog” or “table” with shapes and colors such that a text prompt of those terms can then output images.
Given how digital technologies function, training AI in this way necessarily involves making an initial copy of images in order to analyze them. As we’ve explored in the past and will discuss in future posts about these recent lawsuits, we think this sort of copying can and should be permissible under copyright law. There are certainly nuances when it comes to copyright’s interaction with these tools — for instance, what if the tools are later used by someone to generate an output that does copy from a specific creative expression? But treating copying to train AI as per se infringing copyright would in effect shrink the commons and impede others’ creativity in an over-broad way. It would expand copyright to give certain creators a monopoly over ideas, genres, and other concepts not limited to a specific creative expression, as well as over new tools for creativity.
Copyright, and intellectual property law in general, are only one lens to think about AI: It’s still important to grapple with legitimate concerns about this technology and consider what responsible development and use should be. For instance, what impact will these tools have on artists and creators’ jobs and compensation? How can we ensure that AI that is trained on the commons contributes back to the commons as well, supporting all types of creators? What about the use of these tools to develop harmful misinformation, to exploit people’s privacy (eg, their biometric data), or in ways that perpetuate biases? More generally, how can we ensure human oversight and responsibilities to ensure that these tools work well for society?
These are just some of the tricky issues that will need to be worked out to ensure people can harness AI tools in ways that support creativity and the public interest. Along with other policy and legal approaches to governing AI, it’s important to look to community-driven solutions that support responsible development and use. Already, StabilityAI will let artists opt-out of its training data set, as well as opt in to provide greater information about their works. While this precise approach raises a variety of views, indexing of the web has functioned well using a similar sort of opt-out approach — set through global technical standards and norms, rather than law. Creators of some generative AI tools are using licenses that constrain how they are deployed, which also carries various trade-offs.
What’s Next? Community Input
Supporting community-driven solutions has also always been at the heart of Creative Commons’ approach to creativity. If you’re interested in this subject, we are going to be holding meetings with the Creative Commons community, and we also plan to continue meeting with diverse stakeholders to explore what sorts of solutions may be helpful in this area. As we go along we’ll continue to report on what we’ve learned and seek out more community feedback.
Join the CC team at a community discussion about generative AI: How can we make it work better for everyone and support better sharing in the commons?
To enable participation around the world, we’ve scheduled three times for this conversation. Come to the one that works best for your schedule, or join as many as you like. We’ll be focused on the same questions and issues at each meeting, but different participants will bring different perspectives, reshaping each conversation. To enable participants to speak freely, these meetings will not be recorded, but the CC team will be taking notes to share outcomes from the conversations.
