Appreciate the kind words from Trust In Media Cooperative. Their closing question gets at something we encounter every day in the C2PA standards work: the credibility signals that will matter most are the ones that cannot be separated from the content. Labels can be removed. Most metadata gets stripped during distribution. Terms of service go unread. Every intermediary between origin and destination is a point where context disappears. The C2PA text standard published in January takes a different approach. Cryptographic proof of origin embedded directly in the text. It survives copy-paste, redistribution, and scraping. The provenance travels with the content wherever it goes, regardless of who handles it. That is the infrastructure shift. Not better labels. Provenance that persists. #C2PA #ContentProvenance #AI #Provenance
As AI-generated content becomes more common online, transparency standards and credibility tools are becoming increasingly important infrastructure for the information environment itself. Our friend Erik Svilich at Encypher has been doing important work in this space through the Coalition for Content Provenance and Authenticity (C2PA), which is developing open technical standards designed to help establish provenance, context, and authenticity for digital content. The goal is not simply labeling content. It is creating stronger systems for understanding where content came from, how it was created, and whether it has been altered. That matters across sectors. Journalists verifying footage. Businesses responding to reputational incidents. Platforms moderating content. Everyday users trying to determine what information they can trust. Trust does not come from labels alone. It depends on transparency, shared standards, and systems that help people evaluate information with greater confidence and context. What credibility signals will matter most as AI-generated content becomes more widespread? #digitalcontent #AI #C2PA #provenance
