At Creative Commons, we’ve long believed that binary systems rarely reflect the complexity of the real world—nor do they serve the commons very well. The internet, like the communities that built it, thrives on nuance, experimentation, and shared stewardship. That’s why we’re continuously working to introduce choice where there has been little, and to advocate for systems that acknowledge the diversity of values and needs across the web. CC signals is one expression of that thinking, and lately we’ve been exploring how those ideas can travel into other emerging standards that are shaping the future of the web.

Strange Bedfellows

That brings us to Real Simple Licensing (RSL). Publicly launched in September 2025, today the RSL Collective releases the RSL 1.0 standard. RSL is an open standard that lets publishers define machine-readable licensing terms for their content, including attribution, pay per crawl, and pay per inference compensation. This is an example of emerging technical systems used by websites to automate compensation for when their digital content—such as text, images, and structured data—is accessed by machines. We’ve been referring to these systems as pay-to-crawl. Think of it as the web’s attempt to answer the question: what tools are needed when bots become the biggest readers? If you are new to the concept, we recently published an issue brief that breaks it down in plain language.

On the surface, Creative Commons and pay-to-crawl systems are strange bedfellows. We have always been a champion of the open web and are concerned about a world where knowledge is harder to access. But we also recognize that responsible, interoperable systems can create leverage where none previously existed. Thoughtfully designed, pay-to-crawl systems may help curb extractive behavior by powerful actors while keeping the web open for everyone else.

Attribution + Compensation

In its early version 1.0 draft, RSL included attribution as one condition for machine access and reuse. From the standard: 

Attribution-Only License 

The publisher permits free reuse of the content on its site, provided that visible credit and a functional link to the original source are included. 

This is important as one example of more choices given to web publishers beyond the binary no access or all access. The inclusion of attribution also mirrors some elements of the proposed CC signal Credit. 

You must give appropriate credit based on the method, means, and context of your use.

Attribution + Reciprocity

But as the CC signals framework recognizes, attribution alone is not enough to address the very present power imbalances between AI developers and the commons. We need new tools that ensure the commons thrives and is sustained. 

We believe now is the time to act to infuse concepts of reciprocity in standards that are ready for adoption. That’s why we worked with the RSL Collective ahead of the release of version 1.0 to integrate a contribution component to the standard, which is described as:

A good faith monetary or in-kind contribution that supports the development or maintenance of the assets, or the broader content ecosystem. 

This is not about turning access into a tollbooth. It’s about acknowledging that extraction without reinvestment leads to collapse. There is a meaningful difference between paying a fee and giving back. One is transactional. The other is about responsibility.

When AI systems derive immense value from the digital commons, contribution isn’t compensation. It’s participation in the social contract that made that value possible in the first place.

Contribution could be in the form of:

• A donation back to a non-profit that stewards the dataset; 
• Support for the broader ecosystem that sustains the work;
• Openly licensing the model, or sharing a modified dataset back to the original steward;
• Or other models we haven’t yet imagined.

A Big Step: Many More to Come

The future of the web is being negotiated right now, in standards documents, in product decisions, and in design choices that shape how power flows online. Collaboration is vital if we’re going to achieve a systems-level response to rebalance power in the digital commons. 

There’s much more work to be done, particularly in developing what adherence to contribution means in different contexts. But we’re excited about where this is going. 

Our door is open. We welcome ideas, critiques, and collaboration. If you have ideas, consider engaging with us on LinkedIn or joining CC’s community platform on Zulip. 

Our year-end fundraising campaign is happening right now. While you are here, please consider making a donation to support this work.

Posted 10 December 2025

Tags

• cc signals