System:
Distributed autonomous system (satellite constellation, AI decision pipeline, or multi-agent system)
Failure mode:
System-level misalignment despite locally correct behavior
Observed drift:
Each node adjusts behavior based on local conditions.
Outputs remain within acceptable bounds.
No immediate error is detected.
However, small deviations begin to accumulate across nodes:
- overlapping actions
- inconsistent prioritization
- increasing variance in downstream outcomes
The system still appears stable.
But alignment is already degrading.
Correction mechanism:
Centralized oversight or coordination layer (e.g., ground control, retraining loop, governance intervention)
This mechanism assumes:
- visibility into system state
- sufficient response time
- coherence across nodes
Failure boundary:
When local adjustments propagate faster than the correction mechanism can reconcile,
system-level behavior diverges beyond recoverable limits.
At this point:
- corrections become reactive instead of stabilizing
- interventions lag behind system state
- coherence cannot be restored without reset
Concrete example:
Multiple satellites independently increase observation density in response to a local anomaly.
Each action is correct locally.
Across the system:
- coverage becomes redundant in one region
- blind spots emerge elsewhere
- resource allocation degrades
No single node fails.
But the system as a whole loses effective coverage.