- From: Christian Hommrich <christian.hommrich@trailprotocol.org>
- Date: Mon, 13 Apr 2026 20:41:42 +0200
- To: Phillip Long <pdlong2@asu.edu>
- Cc: public-credentials@w3.org
Phil, Your CC-license analogy is spot on - and I think it points to something even bigger than a disclosure convention. Creative Commons worked because it combined a simple visual stamp with a machine-readable legal layer underneath. For AI disclosure to work at scale, we need the same architecture: a human-readable indicator backed by a verifiable, machine-readable identity layer. That's exactly what we're building with did:trail - a W3C DID method specifically designed for AI agent identity. Here's how your CC-stamp vision maps to what we've been working on: 1. The "stamp" you describe could be implemented as an AI-Disclosure Verifiable Credential (VC) - a cryptographically signed attestation that states: "This content was produced with AI assistance of type X, by agent Y, deployed by organization Z." 2. The identity behind the stamp matters. A CC license works because we trust the author declared it. For AI disclosure, we need to verify WHICH agent contributed, WHO deployed it, and WHAT capabilities it had. did:trail provides that identity foundation - verifiable, cross-platform, and protocol-agnostic. 3. The regulatory urgency is real. The EU AI Act enforcement begins August 2026, and transparency obligations for AI-generated content are a core requirement. A W3C-backed disclosure framework built on verifiable credentials would give organizations a standards-based compliance path. Your suggestion of a dedicated workgroup aligns perfectly with what several of us have been discussing. We'd be very interested in contributing the technical identity infrastructure (did:trail as the agent identity layer, VCs as the disclosure mechanism) to such an effort. We'd welcome your thoughts directly in our GitHub Discussion #10 [1] - that's where we're actively exploring these use cases with the community. [1] https://github.com/trailprotocol/trail-did-method/discussions/10 Best, Christian Hommrich TrailSign AI | trailprotocol.org
Received on Monday, 13 April 2026 18:41:59 UTC