Failure mode
A failure mode is a distinct way in which a system, component, process, or operation can fail or produce an undesirable result.
The Art of AI Product Development
A failure mode is a distinct way an AI system can produce an incorrect, harmful, or otherwise undesired result.
- How it is used
- Frames AI failure as a user-experience decision that begins by defining errors for the specific application.
- How deep it goes
- Works through error types, user recognition, and tolerance questions, without specifying a numerical threshold or implementation procedure.
- Examples
- Contrasts visible and aggregated movie-review sentiment errors, then considers an unrealistic brainstorming suggestion that inspires an idea.
- What you can do after
- Evaluate/understand failure modes by identifying likely errors, whether users notice them, and how the situation affects tolerance.
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Prompt Engineering in Practice
A failure mode is a distinct way in which a system, artifact, or process can produce an incorrect or undesired result.
- How it is used
- Diagnoses how prompt components affect outputs during prompt design.
- How deep it goes
- Explains partial failures through missing or weakened components, while deferring formal component vocabulary.
- Examples
- Uses incident reports to contrast generic summaries with engineering post-incident summaries.
- What you can do after
- Diagnose how unclear instructions, unlabeled inputs, or weak output guidance affect results.
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Related concepts
- overfittingincludes · Overfitting is a modeling condition in which a model fits patterns or idiosyncrasies in its training data too closely and consequently generalizes poorly to new data.
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