IETF Internet-Draft: AI Content Disclosure Header

Summary

As AI-generated content proliferates across the web, users [BV-Report], platforms, and regulators increasingly demand transparent disclosure of algorithmic involvement in content creation [PAI-Framework]. Existing approaches to disclosure (e.g., HTML disclaimers) lack machine-readability [GV-Prov], making automation, indexing, and compliance challenging.¶ This document defines the AI-Disclosure HTTP header field, providing a lightweight, machine-readable mechanism focused specifically on signaling the presence and mode of AI involvement in the generation of an HTTP response's content. It utilizes HTTP Structured Fields [RFC9651] to offer a simple dictionary format directly within the HTTP response headers.¶ The goal of AI-Disclosure is to offer a low-overhead, easily parsable signal primarily for automated systems like web crawlers, archiving tools, or user agents that may need a quick indication of AI usage without processing complex manifests. This header is intended to be applied at the entire response level.¶ It is important to distinguish this mechanism from more comprehensive content provenance and authenticity frameworks like the Coalition for Content Provenance and Authenticity (C2PA) specification [C2PA-Spec]. C2PA provides richer, cryptographically signed assertions about content provenance, potentially covering detailed creation/modification history and applying to specific regions within an asset ("Regions of Interest"). C2PA information can be linked via methods including the HTTP Link header [RFC8288] pointing to an associated manifest.¶ AI-Disclosure can be seen as complementary to such systems within a layered disclosure strategy. While C2PA offers strong, verifiable, and granular provenance, AI-Disclosure provides a simpler, advisory signal directly in the HTTP interaction for basic AI involvement awareness. Systems requiring high assurance or sub-resource granularity should utilize frameworks like C2PA.¶