Trust fabric · Responsible AI
Intelligence you can defend.
A principle with no implementation is a slogan. Each commitment below names the mechanism that enforces it and the artefact that proves it.
Human authority is inviolableSign-off is enforced server-side, bound to a content hash, and cannot be disabled by configuration, feature flag or administrative role.
Explanation is a rightEvery output links to cited, versioned evidence, reachable from any statement in no more than two interactions.
Uncertainty is disclosedCalibrated intervals on every prediction, separating uncertainty from missing data from uncertainty inherent to the model.
Determinism where it is defensibleClassification, dosing and eligibility run on versioned, inspectable rules. Language models draft over cited findings and originate nothing.
Consent is purpose-boundGranular and revocable, evaluated on every access, with revocation propagating to derived artefacts.
Equity is designed forSubgroup performance, calibration and refusal rate reported in every validation — favourable or not.
Obligations persistA finding reclassified by new evidence is flagged for review rather than silently left stale.
Automation bias
The failure mode nobody monitors.
The counterpart to autonomous error is human abdication. We monitor reviewer rejection rate for a healthy band rather than minimising it. A rate approaching zero is read as a warning — it usually means review has stopped being real — and it triggers quality review of the review process, not retraining of the model.
Summative usability studies deliberately include outputs that are wrong in ways a careful reviewer would catch. A study in which every output is correct measures workflow, not safety.
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