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Classifying AI failures — hallucination, refusal, irrelevance, tone mismatch, latency.
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Basé sur la classification professionnelle SOC
Proactively identifying failure modes, misuse, and unintended consequences.
Managing shared context, memory, and state across multiple agents.
Coordinating text, image, voice, and tool-use modalities in a single interaction.
Helping users form warranted trust in the AI — neither overtrust nor undertrust — through deliberate confidence and source signalling.
Reading user emotional state from text signals — caps, punctuation density, repetition, latency — and adapting before the user disengages.
Designing review workflows to surface and mitigate bias in AI outputs.
| name | failure-taxonomy |
| description | Classifying AI failures — hallucination, refusal, irrelevance, tone mismatch, latency. |
Not all AI failures are the same. A hallucination is different from a refusal, which is different from a tone mismatch. A failure taxonomy classifies failure types so teams can track, prioritise, and address them systematically.
Content Failures:
