Renewable energy and critical mineral supply chains are undergoing significant expansion driven by worsening climate change and environmental impacts and technological advancements, amid significant geographic concentration. These changes have implications for challenges and opportunities for decent work across regions and segments of the workforce.
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As we look back on 2025, it’s clear that the internet as we know it is changing. Technology-enabled access to knowledge should be flourishing. Instead, information is being removed from the web or locked away in walled gardens. We are experiencing a crisis in the commons, driven in part by current AI development practices. New systems are emerging in response—from content monetization schemes and licensing agreements designed to protect large rightsholders, to the ongoing morass of lawsuits about how AI services are using content as data. We are in the midst of a major reconfiguration of how we share and reuse content on the web.
“Distorted Forest Path” by Lone Thomasky & Bits&Bäume, CC BY 4.0, remixed by Creative Commons, CC BY 4.0.
CC Signals: A Refresher
It is within this environment that we continue to develop CC signals.
We introduced the CC signals concept last June during a live webinar, and further explored the motivation behind this work in our reportFrom Human Content to Machine Data. We also shared the outcomes of our open feedback period following the CC signals kickoff. Since then, we’ve been experimenting in partnership with values-aligned stakeholders and developing pilot projects to test ideas raised by the community.
The goal of CC signals is to help creators and custodians of collections express how they want their content or data to be used in AI development in ways that uphold reciprocity, recognition, and sustainability. Today’s AI systems depend on vast amounts of human-created content, often collected without the awareness or involvement of those who made it. This has concentrated power and undermined trust in the social contract of the commons.
CC signals responds by promoting community agency while preserving Creative Commons’ core commitment to access and openness. Ultimately, through CC signals and other interventions that infuse concepts of reciprocity in standards and practices, we envision an open internet where participation is equitable, creators are respected, and innovation advances the commons—not unchecked extraction.
CC Signals: Where Are We Now?
CC signals is an evolving, values-driven framework—currently being tested through a series of pilot efforts. Our strategy is to explore modular approaches across legal, technical, and normative dimensions to encourage responsible AI development practices. This allows CC signals to adapt as norms, technologies, and standards continue to evolve.
At present, two key implementations are underway:
Implementing CC signals on Mozilla Data Collective: We are working in partnership with our friends at Mozilla, looking at how implementation of CC signals would work on the Mozilla Data Collective platform, which is purpose-built to enable ethical dataset sharing and fair value exchange. Our plan is to test various ways of incorporating some measure of legal enforceability into CC signals. We also hope to use this as an opportunity to test which CC signal elements are most popular and impactful, and which ones have the biggest impact on AI developer behavior.
Adapting the CC signals contribution element in the RSL framework: Using the framework of the ecosystem contribution signal element, we are working with the RSL Collective to embed the notion of reciprocal contribution into this evolving standard. As a platform that will let rightsholders set machine-readable licensing terms for their content, integrating the contribution element ensures that standards such as RSL provide mechanisms for AI developers to contribute back to the commons at the collective or community level, not simply a one-to-one payment.
Beyond CC signals itself, we are also exploring whether updates to CC’s license infrastructure could further strengthen and support the commons in the age of AI.
Looking Ahead
We are actively seeking expressions of interest from dataset custodians who are interested in participating in the Mozilla Data Collective pilot project. If that’s you, we’d love to hear from you.
We are also exploring sector-specific CC signals integrations, particularly within cultural heritage and science.
Ultimately, CC signals are incarnations of what we want to see in the world—more recognition for authorship, sustainable commons communities, mutual commitments to shared resources. We are focused on building a vocabulary and vision for the values we think a successful commons needs to thrive.
This work is resource-intensive. We need your support to ensure this work continues to be led by public interest organizations. Please donate today.
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