You present it, you own it — accountability for what AI presents.
When an AI answer is presented as authoritative, public developments suggest responsibility tends to sit with the party that presented it — rather than the sources behind it or the reader. If that is where responsibility lands, you benefit from being able to show afterwards what was presented, on whose authority, and on what cited basis. That is an evidence-and-authority question. It is what the trust layer for consequential action exists to answer.
What was publicly reported
This section relays a public report. It is not legal advice, and KYE Protocol™ relays the judgment without independently verifying it. As reported by THE DECODER on 9 June 2026, the Regional Court of Munich (Landgericht München) held that Google's AI Overviews are attributable to Google itself — rather than to the underlying sources or to users. The reported reasoning, in short:
- The holding, as reported — an AI provider is responsible for the answers its AI presents; responsibility was not shifted to the sources or the reader.
- The reasoning, as reported — presenting content as a coherent, autonomous, authoritative answer means a provider cannot transfer the entire burden of verification to the reader.
- Independent regulatory context — separately, the EU AI Act™ already places logging and human-oversight duties on the deployer at the point of use (Article 12, Article 14). Those duties are discharged at runtime, not in a later review.
The full, carefully-sourced account is in AI Legal Briefs™ No. 1, which reports what was decided and, separately and clearly labelled, what KYE Protocol™ reads into it. Whether and how any ruling applies to your organisation is a matter for your own legal advisers.
The principle KYE Protocol™ designs to
This is KYE Protocol™'s design principle, clearly separated from the reported facts above. It is not legal advice. The dispute is concrete in a way much of the AI debate is not. The question is who bears responsibility when plausibility is consumed as knowledge — not whether the statement is clever, nor how capable the model is. Where responsibility sits with the party that presents AI output authoritatively, that party benefits from runtime proof:
- What was presented — captured as a signed Evidence Pack™ at the moment of the action, not reassembled from logs weeks later.
- On whose authority — which principal held authority for the action, traced across the delegation chain and resolved to Authority Finality™.
- On what cited basis — the evidence is replay-derivable from public keys alone, so a regulator, an auditor, or a counterparty can check it without trusting the vendor.
KYE Protocol™ governs whether an AI action is authorised and records the basis as replay-verifiable evidence. It does not make a model's statements true and makes no claim about the correctness of any AI output — it makes the authority and the basis provable.
If you present it, be able to prove it.
Your team may be putting AI into a path where its output is presented as authoritative — an answer to a customer, a recommendation to a clinician, a statement to a regulator. The trust layer is what lets you adopt it without losing legitimate control. Start with one governed pilot on a single real action. Leave with an Evidence Pack™ you can hand to your board, your auditor, or your regulator.