Creative Commons Proposes CC Signals for AI-Era Content Sharing
Creative Commons (CC) has launched a new initiative called ‘CC Signals’ to help data holders express how their content can be reused by AI systems, marking a pivotal move in shaping norms for the age of machine learning. The CC Signals project is intended as a modern counterpart to the traditional Creative Commons licenses. It introduces a preference signalling framework for datasets, especially those used to train AI models, grounded in reciprocity, shared benefit, and openness. “CC signals are designed to sustain the commons in the age of AI,” Anna Tumadóttir, CEO of Creative Commons, said. “Just as the CC licenses helped build the open web, we believe CC signals will help shape an open AI ecosystem grounded in reciprocity.” Unlike traditional licences, CC Signals are envisioned as a mix of legal and normative tools, with both machine and human-readable elements. These signals won’t always be legally enforceable but will carry ethical and social weight, reflecting the idea of mutual exchange in a data-driven world. Sarah Hinchliff Pearson, general counsel at Creative Commons, highlighted the collective value of the initiative. “A single preference, uniquely expressed, is inconsequential in the machine age. But together, we can demand a different way.” The project is now entering a public feedback phase, with an alpha release planned for November 2025. CC has published early design documents and opened up discussions on GitHub, inviting contributors to review the technical implementation, submit issues, and participate in community town halls. As AI systems continue to reshape the boundaries of content usage, CC Signals offers a middle path, neither fully extractive nor entirely closed, intended to keep knowledge open while respecting the intent of its creators.
A new licensing system is emerging for the era of AI-enabled content.
A new licensing system is emerging for the era of AI-enabled content.
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["AI", "machine learning", "R", "Git", "GitHub", "API", "ViT", "RPA", "data-driven", "programming_languages:R"]
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