expertise needed

human factors

Requires knowledge of how people oversee, rely on and interact with AI systems: designing human review workflows, managing reviewer workload and fatigue, and communicating model confidence and limits to users.

8 techniques
GoalsModelsData TypesDescription
Human-in-the-Loop Safeguards
Process
Architecture/model Agnostic
Requirements/black Box
Any
Human-in-the-loop safeguards hold an AI system's output at a checkpoint until a trained person has reviewed it....
Confidence Thresholding
Algorithmic
Architecture/model Agnostic
Requirements/black Box
+1
Any
Confidence thresholding uses a model score to decide whether a prediction should proceed automatically or receive...
API Usage Pattern Monitoring
Algorithmic
Architecture/model Agnostic
Requirements/black Box
Any
API usage pattern monitoring examines how each account uses a deployed model's API, to catch misuse that no single...
Out-of-Domain Detection
Algorithmic
Architecture/model Agnostic
Architecture/neural Networks/transformer/llm
+2
Text
Out-of-domain detection checks whether a user's query falls inside the topics and tasks a conversational AI system is...
Appropriate Reliance Measurement
Metric
Architecture/model Agnostic
Requirements/black Box
Any
Appropriate reliance measurement tests whether people who receive an AI system's advice follow it when it is right and...
Explanation Satisfaction Scale
Metric
Architecture/model Agnostic
Requirements/black Box
Any
The Explanation Satisfaction Scale is a short questionnaire on which people who have used an AI system's explanations...
Forward Simulation Test
Testing
Architecture/model Agnostic
Requirements/black Box
Any
A forward simulation test checks whether people who have studied a model's explanations can predict the model's output...
Think-Aloud Study of Explanation Use
Testing
Architecture/model Agnostic
Requirements/black Box
Any
A think-aloud study of explanation use asks a small number of participants to say what they are thinking while they use...
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