Canonical · L3 Category·Shipped
Trust telemetry
Trust telemetry is measurement of earned autonomy, not output appearance. It is evidence about what an AI system has safely done, where it has failed, when it escalated, how it recovered, and whether its autonomy should expand, hold, or contract.
Plain definition
Trust telemetry is evidence about what an AI system has safely done, where it has failed, when it escalated, how it recovered, and whether its autonomy should expand, hold, or contract.
Why it matters
Dashboards report state. Trust telemetry interprets state as movement of the trust boundary, so the substrate can decide whether to act, ask, or escalate the next time a similar decision arrives.
What it is not
- Observability tooling.
- A metrics framework.
- A dashboard.
- Audit logging.
Where it appears in Ubiquity
Trust telemetry lives in the Ubiquity substrate as the evidence stream behind Signals → Warrants → Rules.
Ladder context
Demand ladder
L1 Pain→L2 Contrast→L3 Category→L4 Primitive→L5 Branded
← Up the funnel
Dashboards vs. trust telemetryDown the funnel →
This is a leaf of the ladder.Adjacent transitions
Related terms
Frequently asked
- What is trust telemetry?
- Evidence about what an AI system has earned: outcomes, escalations, corrections, refusals, recoveries — interpreted as trust-boundary movement.
- Is trust telemetry the same as observability?
- No. Observability shows internal state. Trust telemetry interprets state as governance signal.
- Can trust be measured in AI systems?
- It can be evidenced. Trust telemetry tracks the signals that update where autonomy is granted next.
- How does telemetry affect autonomy?
- By moving the trust boundary — expanding it where evidence stabilizes, holding it where evidence wobbles, contracting it where evidence collapses.