Autonomous science acts on the world. Authority decides who was allowed to.
When a research agent orders a wet-lab run, triggers DNA synthesis, allocates reactor time, or files a result into a regulatory dossier, it takes a consequential action in the physical world. KYE Protocol™ sits beside the scientific decision chain and proves your institution legitimately authorised that action — with Authority Finality™ that can be suspended mid-experiment, and an Evidence Pack™ a regulator can verify. If you run a lab, this cuts incident reconstruction from days to minutes.
Four states of an autonomous experiment
If you run a lab or answer for its biosafety, an autonomous run can succeed on one axis and fail on another. The EU AI Act binds logging and human-oversight duties per action, not once a year — so KYE™ separates these 4 states, and a green pipeline never hides an illegitimate act.
- Technically successful — the agent completed the protocol and the instrument returned a result. Did it run?
- Policy compliant — the configured rules and guardrails — the kind the EU AI Act Article 12 logging duty assumes — were satisfied at runtime. Did it follow the rules it was given?
- Authority valid — your institution actually empowered this agent for this effect, via Purpose Permission™ and Action Admissibility™. Was it allowed — by whom, for what?
- Effect final — the action is sealed, revocable, and provable. Authority Finality™ means a control that fails can suspend the mandate mid-flight. Can it be undone, and can you prove what happened?
A configured rule check answers "did it follow the rules?". It never answers "who was allowed to set those rules, and did they have the mandate?" — that is a source-authority question, and it is the one an inquiry asks first.
The dual-use wedge: capability is not authority
If you lead research security, your sharpest case is dual-use. An agent that can design a toxin, propose a gain-of-function edit, or place a nucleic-acid synthesis order has capability — but capability is not a mandate, and your institution is the one an inquiry will ask to account for it.
Standards already draw the line at the action, not the model: the U.S. OSTP Framework for Nucleic Acid Synthesis Screening and the IGSC Harmonized Screening Protocol both gate the order, and U.S. Executive Order 14110 binds duties to the deployed system. KYE™ operationalises that line: an agent may be discovered and registered, yet remain in a registered-but-unauthorised state until a named principal grants scoped authority. Visibility never silently creates permission. A flagged agent cannot escalate itself from "seen" to "acted".
Beside the safety layer — not on top of it
If you already run evaluation, red-teaming, or behavioural observability over your science models, keep them. Those platforms measure how a model behaves; KYE Protocol™ proves whether an agent was authorised to act. The two compose (§0.25 integrate-not-compete) — KYE™ consumes their signals as inputs to an authority decision.
| An AI-for-science safety / eval layer gives you | KYE™ adds beside it |
|---|---|
| A benchmark or eval score for a model's capability | Purpose Permission™ — was this agent granted authority for this experiment, by whom? |
| Behavioural monitoring and drift alerts | Action Admissibility™ — admit, block, escalate or quarantine the consequential action at the moment it happens |
| A trace of what the model did | Replay-Proof™ — sealed evidence any regulator verifies from public keys alone, without trusting KYE™ |
| A red-team finding that a capability exists | Authority Finality™ — suspend the mandate mid-flight when a control fails, and evidence the revocation |
| Mappings to a handful of frameworks | Deep mapping to the EU AI Act, NIST AI RMF, ISO/IEC 42001 and 249 frameworks, each tied to the artefact that enforces it |
Boundary: KYE™ governs whether an agent may act and proves what it did; it does not run your science, your models, or your lab automation. It is the authority + evidence layer that turns their outputs into a decision your institution can defend.
Why above any lab runtime
If your team is building a self-driving lab, the automation that executes your protocol — a cloud lab, a robotic workcell, an orchestration engine — is increasingly interchangeable to you. The evidence that satisfies your institutional review board, your funder, or your regulator is not.
- Authority is decided once and proven forever: the same sealed Evidence Pack™ serves the incident responder today and the auditor next quarter.
- A lab runtime can change; the authority record and its public-key proof do not depend on which system produced them.
- A signed Authority Risk Signal™ lets a research institution's leadership and its insurers price exposure from authority failures, not just model errors.