Mise à jour de la base de données, veuillez patienter...

Thanks to everyone who attended our CC signals project kickoff last week. We’re receiving plenty of feedback, and we appreciate the insights. We are listening to all of it and hope that you continue to engage with us as we seek to make this framework fit for purpose.

Some of the input focuses on the specifics of the CC signals proposal, offering constructive questions and suggesting ideas for improving CC signals in practice. The most salient type of feedback, however, is touching on something far deeper than the CC signals themselves – the fact that so much about AI seems to be happening to us all, rather than with or for us all, and that the expectations of creators and communities are at risk of being overshadowed by powerful interests.

This sentiment is not a surprise to us. We feel it, too. In fact, it is why we are doing this project. CC’s goal has always been to grow and sustain the thriving commons of knowledge and culture. We want people to be able to share with and learn from each other, without being or feeling exploited. CC signals is an extension of that mission in this evolving AI landscape.

We believe that the current practices of AI companies pose a threat to the future of the commons. Many creators and knowledge communities are feeling betrayed by how AI is being developed and deployed. The result is that people are understandably turning to enclosure. Eventually, we fear that people will no longer want to share publicly at all. 

CC signals are a first step to reduce this damage by giving more agency to those who create and hold content. Unlike the CC licenses, they are explicitly designed to signal expectations even where copyright law is silent or unclear, when it does not apply, and where it varies by jurisdiction. We have listened to creators who want to share their work but also have concerns about exploitation. CC signals provide a way for creators to express those nuances.  The CC signals build on top of developing standards for expressing AI usage preferences (e.g., via robots.txt). Creators who want to fully opt out of machine reuse do not need to use a CC signal. CC signals are for those who want to keep sharing, but with some terms attached.

The challenge we’re all facing in this age of AI is how to protect the integrity and vitality of the commons. The listening we’ve been doing so far, across creator communities and open knowledge networks, has led us here, to CC signals. Our shared commitment is to protect the commons so that it remains a space for human creativity, collaboration, and innovation, and to make clear our expectation that those who draw from it give something in return. 

Our goal is to advocate for reciprocity while upholding our values that knowledge and creativity should not be treated as commodities. 

Our goal is to find a path between a free-for-all and an internet of paywalls.

Copyright will not get us there. Nor should it. And we don’t think the boundaries of copyright tell us everything we need to know about navigating this moment. Just this week, Open Future released a report that calls for going beyond copyright in this debate, on the path to a healthy knowledge commons.

This is the beginning of the conversation, not the end. We are listening. From what we have heard, CC signals, or something like it, is the best practical mechanism to avoid the dual traps of total exploitation or total enclosure, both of which damage the commons. We have shared our current progress because we want to learn how to design it to meet your needs. We invite you to continue sharing feedback so we can shape CC signals together in a way that works for diverse communities.

In the months ahead, we’ll be providing more detail about how CC signals are developing, including key themes we are hearing, along with the questions we are exploring and our next steps.

The post Why CC Signals: An Update appeared first on Creative Commons.

Creative Commons (CC) today announces the public kickoff of the CC signals project, a new preference signals framework designed to increase reciprocity and sustain a creative commons in the age of AI. The development of CC signals represents a major step forward in building a more equitable, sustainable AI ecosystem rooted in shared benefits. This step is the culmination of years of consultation and analysis. As we enter this new phase of work, we are actively seeking input from the public. 

As artificial intelligence (AI) transforms how knowledge is created, shared, and reused, we are at a fork in the road that will define the future of access to knowledge and shared creativity. One path leads to data extraction and the erosion of openness; the other leads to a walled-off internet guarded by paywalls. CC signals offer another way, grounded in the nuanced values of the commons expressed by the collective.

Based on the same principles that gave rise to the CC licenses and tens of billions of works openly licensed online, CC signals will allow dataset holders to signal their preferences for how their content can be reused by machines based on a set of limited but meaningful options shaped in the public interest. They are both a technical and legal tool and a social proposition: a call for a new pact between those who share data and those who use it to train AI models.

“CC signals are designed to sustain the commons in the age of AI,” said Anna Tumadóttir, CEO, Creative Commons. “Just as the CC licenses helped build the open web, we believe CC signals will help shape an open AI ecosystem grounded in reciprocity.”

CC signals recognize that change requires systems-level coordination. They are tools that will be built for machine and human readability, and are flexible across legal, technical, and normative contexts. However, at their core CC signals are anchored in mobilizing the power of the collective. While CC signals may range in enforceability, legally binding in some cases and normative in others, their application will always carry ethical weight that says we give, we take, we give again, and we are all in this together. 

“If we are committed to a future where knowledge remains open, we need to collectively insist on a new kind of give-and-take,” said Sarah Hinchliff Pearson, General Counsel, Creative Commons. “A single preference, uniquely expressed, is inconsequential in the machine age. But together, we can demand a different way.”

Now Ready for Feedback 

More information about CC signals and early design decisions are available on the CC website. We are committed to developing CC signals transparently and alongside our partners and community. We are actively seeking public feedback and input over the next few months as we work toward an alpha launch in November 2025. 

Get Involved

Join the discussion & share your feedback

To give feedback on the current CC signals proposal, hop over to the CC signals GitHub repository. You can engage in a few ways: 

1. Read about the technical implementation of CC signals
2. Join the discussion to share feedback about the CC signals project
3. Submit an issue for any suggested direct edits

Attend a CC signals town hall

We invite our community to join us for a brief explanation of the CC signals framework, and then we will open the floor to you to share feedback and ask questions. 

Tuesday, July 15
6–7 PM UTC
Register here.

Tuesday, July 29
1–2 PM UTC
Register here.

Friday, Aug 15
3–4 PM UTC
Register here. 

Support the movement

CC is a nonprofit. Help us build CC signals with a donation. 

The age of AI demands new tools, new norms, and new forms of cooperation. With CC signals, we’re building a future where shared knowledge continues to thrive. Join us.

The post Introducing CC Signals: A New Social Contract for the Age of AI appeared first on Creative Commons.

Whether you are a creator, researcher, or anyone licensing your work with a CC license, you might be wondering how it can be used to train AI. Many AI developers, who wish to comply with the CC license terms, are also seeking guidance. 

The application of copyright law to AI training is complex. The CC licenses are copyright licenses, so it follows that applying CC licenses to AI training is just as complex. 

The short answer is: AI training is often permitted by copyright. This means that the CC license conditions have limited application to machine reuse. This also means that using a more restrictive CC license in an effort to prevent AI training is not an effective approach. In fact, restrictive licensing may actually end up preventing the kind of sharing you want (like allowing for translation, for example), while not being effective to block AI training. 

For the long answer, read our new guide that provides a legal analysis and overview of the considerations when using CC-licensed works for AI training. 

  For an at-a-glance overview, head over to the Using CC-Licensed Works for AI training webpage. 

  For a more in-depth analysis, check out our handy PDF download. 

For those who love a visual, take a look at our supplementary flowchart. 

If the CC licenses have limited application to machine reuse, what agency do creators have in the AI ecosystem? 

This is an important question. As you’ve heard us talk about before, we’re actively developing a CC preference signals framework to help bridge this gap. The framework is designed to offer new choices for stewards of large collections of content to signal their preferences when sharing their works, using scaffolding inspired by the architecture of the CC licenses. This is not mediated through copyright or the CC licenses. It is governed by something that tends to be even more widely adopted: a social contract. Stand by for the release of the paper prototype of CC preference signals framework at the end of June 2025. 

While you are here, please consider making an annual recurring donation via our Open Infrastructure Circle. This work will require a large amount of resourcing, over many years, to make happen. 

The post Understanding CC Licenses and AI Training: A Legal Primer appeared first on Creative Commons.

A thriving and connected community is key to building a stronger open movement. That’s why, as part of our 2025–2028 strategic plan, we’re placing community at the center of everything we do. Our vision is clear: a world where communities actively leverage CC’s open infrastructure to share knowledge in the public interest.

This year, we’re focusing on re-engaging with the CC community and building new relationships, especially as emerging technologies like AI reshape how people create and share. We want to ensure CC’s tools, training, and resources evolve to meet real community needs, and we’re committed to being transparent and realistic about what we can offer in support. This is happening during a period of economic uncertainty for organizations in the open movement, so we are focusing on delivering sustainable pathways for community engagement at CC.

From CC Global Summit to New Ways of Connecting 

One big change you may have noticed is that we haven’t announced the next CC Global Summit. Unfortunately, CC’s budgets over the last two years have not allowed for such a significant expense, and most of the past Global Summits ran at a deficit. Without sufficient funding to support participant attendance, the Global Summits cannot be as inclusive as we aspire for them to be.

But this doesn’t mean we can’t spend time together – quite the opposite! We believe that supporting more regional gatherings for in-person engagement and virtual gatherings for increased inclusion will help to meet these challenges. Interested in exploring collaborating on an event in your region or in your community? Let’s chat. 

The CC Community in 2025

Earlier this year, we shared some of the history of the Creative Commons Global Network (CCGN), and talked about the importance of an expanded view of the CCGN. 

In thinking about the future of our community, the shared sentiment is that the CC community is much more expansive than the formal structures of the CCGN; the CC community is anyone who uses, advocates for, or supports the infrastructure that enables open licensing or who supports and believes in the power of the commons.

To enable this broader community, we are evaluating the existing (though currently inactive) membership process of the CC Global Network and how we support country chapters. Our goal is to strengthen our community engagement spaces and create clearer, more accessible pathways for people to get involved with CC.

Let’s Get to Work!

We are excited to reconnect and hear about your experiences and vision for the future of the CC community. Your input will help shape future decisions around governance, community infrastructure, communication tools, and engagement spaces. Please fill out the CC Community Survey by May 30:

• Creative Commons Community Survey – English
• Creative Commons Community Survey – Español
• Creative Commons Community Survey – Français

Our commitment is to make CC a space where collaboration thrives, knowledge flows freely, and communities feel empowered to shape the future of the commons. Stay tuned for opportunities to share your input, connect with others, and co-create what comes next.

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The post The Next Chapter: Strengthening the Creative Commons Community Together appeared first on Creative Commons.

If you’ve been following along on the blog this year, you’ll know that we’ve been thinking a lot about the future of open, particularly in this age of AI. With our 2025-2028 strategy to guide us, we’ve been louder about a renewed call for reciprocity to defend and protect the commons as well as the importance of openness in AI and open licensing to avoid an enclosure of the commons. 

Last month, we took some of these conversations on the road and hosted the Open House for an Open Future during SXSW in Austin, TX, as part of a weekend-long Wiki Haus event with our friends at the Wikimedia Foundation. 

During the event, we spoke with Audrey Tang and Cory Doctorow about the future of open, especially as we look towards CC’s 25th anniversary in 2026.  In this wide-ranging conversation, a number of themes were reflected that capture both where we’ve been over the last 25 years and where we should be focusing for the next 25 years, including: 

• The Fight for Technological Self-Determination: Contractual restrictions are increasingly being used to lock down essential technologies, from printer ink to hospital ventilators. The push for openness and economic fairness must go beyond just content-sharing and extend to fighting for the rights of people to repair, modify, and use technology freely.
  
• Shifting from Resistance to Building Alternatives: The open movement is not just about opposing corporate restrictions but also about creating viable, open alternatives. Initiatives like Gov Zero show that fostering decentralized, user-controlled platforms can help counteract monopolistic digital ecosystems.
  
• The Power of Exit as a Lever for Change: Simply having the option to leave restrictive platforms can influence corporate behavior. Efforts like Free Our Feeds and Bluesky aim to create credible exit strategies that prevent users from being locked into exploitative digital environments.
  
• Beyond Copyright: New Frameworks for Openness and Innovation: While Creative Commons began as a response to copyright limitations, the next phase should focus on broader issues like supporting an infrastructure for open sharing, ethical AI development, and open governance models that empower communities rather than just limiting corporate control.
  
• Reclaiming the Ethos of Open Source and Free Software: The movement must reconnect with its ethical roots, focusing on freedom to create, share, and innovate—not just openness for the sake of efficiency. This includes resisting corporate capture of “openness” and ensuring technological advances serve public interest rather than private profit.

Since the proliferation of mainstream AI, we’ve been analyzing the limitations of copyright (and, by extension, the CC licenses since they are built atop copyright law) as the right lens to think about guardrails for AI training. This means we need new tools and approaches in this age of AI that complement open licensing, while also advancing the AI ecosystem toward the public interest. Preference signals are based on the idea that creators and dataset holders should be active participants in deciding how and/or if their content is used for AI training. Our friends at Bluesky, for example, have recently put forth a proposal on User Intents for Data Reuse, which is well worth a read to conceptualize how a preference signals approach could be considered on a social media platform. We’ve also been actively participating in the IETF’s AI Preferences Working Group, since submitting a position paper on the subject mid-2024.

As CC gets closer to launching a protocol based on prosocial preference signals—a simple pact between those stewarding the data and those reusing it for generative AI training—we had the opportunity during SXSW to chat with some great thought leaders about this very topic. Our panelists were Aubra Anthony, Senior Fellow, Technology and International Affairs Program at Carnegie Endowment for International Peace; Zachary J. McDowell, Phd, Assistant Professor, Department of Communication, University of Illinois at Chicago; Lane Becker, President, Wikimedia LLC at Wikimedia Foundation, and our very own Anna Tumadóttir, CEO, Creative Commons to explore sharing in the age of AI. A few key takeaways from this conversation included:

• Balancing Norms and Legal Frameworks: There is a growing interest in developing normative approaches and civil structures that go beyond traditional legal frameworks to ensure equitable use and transparency.
  
• Navigating AI Traffic and Commercial Use: Wikimedia is adapting to the influx of AI-driven bot traffic and exploring how to differentiate between commercial and non-commercial use. The idea of treating commercial traffic differently and finding ways to fundraise off bot traffic is becoming more prominent, raising important questions about sustainability in an open knowledge ecosystem. From CC’s perspective, we’ve found that as our open infrastructures mature they become increasingly taken for granted, a notion that is not conducive to a sustainable open ecosystem.
  
• Openness in the Age of AI: There is growing reticence around openness, with creators becoming more cautious about sharing content due to the rise of generative AI (note, this is exactly what our preference signals framework is meant to address, so stay tuned!). We should emphasize the need for open initiatives to adapt to the broader social and economic context, balancing openness with creators’ concerns about protection and sustainability.
  
• Making Participation Easy and Understandable: To encourage widespread participation in open knowledge systems and for preference signal adoption, tools will need to be simple and intuitive. Whether through collective benefit models or platform cooperativism, ease of use and clarity are essential to engaging the broader public in contributing to open initiatives.

Did you know that many social justice and public good organizations are unable to participate in influential and culture-making events like SXSW due to a lack of funding? CC is a nonprofit organization and all of our activities must be cost-recovery. We’d like to sincerely thank our event sponsor, the John S. and James L. Knight Foundation for making this event and these conversations possible. If you would like to contribute to our work, consider joining the Open Infrastructure Circle which will help to fund a framework that makes reciprocity actionable when shared knowledge is used to train generative AI.

The post CC @ SXSW: Protecting the Commons in the Age of AI appeared first on Creative Commons.