Silent failure
A failure in which a system produces a confident but wrong output rather than an error. More dangerous than a visible error because customers often encounter it before the operator does. A key target of the failure-history question and a driver of what production monitoring must watch.
Defined in 4 GAGE programs, which carry 5 distinct definitions of it. The wording above is taught in AI Governance: Applied Mastery.
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
A failure mode in which a program encounters an error condition but continues running, producing no visible crash or error message. Caused most commonly by bare `except: pass` clauses. In robotic systems, silent failures manifest as Tier 2 (no output) symptoms: the node is alive but non-functional.
A failure in which a system produces a confident but wrong output rather than an error. More dangerous than a visible error because customers often encounter it before the operator does. A key target of the failure-history question and a driver of what production monitoring must watch.
An agent mistake that throws no error and looks normal (a mis-mapped data field, a confident wrong number), surfacing only later; the reason data-entry and reporting agents need scheduled spot-checks, not only a live gate.
A downstream break that produces a plausible but incorrect result with no error thrown, allowing the wrong output to be consumed and trusted for an extended period before anyone notices.
A failure that produces no error signal; the system returns a confident wrong answer with nothing to catch. Most dangerous AI failures are silent, which is why detection must be designed in from outside the model.
Where it is taught
The exact lessons this term appears in. The first 7 topics of every program are free with a free account.
- AI Agents for Small Business: Affordable Automation at Scale · Bonus: SMB AI Adoption Path, AI Literacy & Professional Conduct
- The schema change that broke the forecaster: blast-radius analysis downstream · Quality as Physics, AI Data Governance: The Data Chair
- The license to govern: explaining to a skeptic exactly how your model fails · Build Before You Govern, AI Governance: Applied Mastery
- The vendor interrogation: questions that expose what the sales deck hides · Shipping AI and Surviving the Incident, AI Governance: Applied Mastery
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.