Explainable AI Quiz Form
Test your knowledge of explainable AI concepts, methods, and applications. Please answer all questions in the Explainable AI Quiz Form below.
What does 'explainable AI' primarily refer to?
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AI systems whose decisions can be understood by humans
AI systems that require no human oversight
AI that only uses rule-based logic
AI that generates random outputs
Which of the following is a common technique for explaining AI models?
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Feature importance
Saliency maps
Random guessing
LIME (Local Interpretable Model-agnostic Explanations)
Why is explainability important in AI?
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It builds user trust and helps identify model errors
It makes AI models faster
It guarantees perfect accuracy
It eliminates the need for data
Select all challenges commonly faced when implementing explainable AI.
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Trade-off between accuracy and interpretability
Lack of standardized methods
Increased computational complexity
Guaranteed model fairness
Rate your familiarity with explainable AI concepts.
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Not familiar
1
2
3
4
Very familiar
5
1 is Not familiar, 5 is Very familiar
Which of these is NOT a goal of explainable AI?
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Making AI decisions transparent
Improving user understanding
Obscuring model logic
Supporting regulatory compliance
Briefly define 'model interpretability' in your own words.
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Which method is often used to explain predictions in tabular data models?
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SHAP (SHapley Additive exPlanations)
GANs (Generative Adversarial Networks)
Reinforcement learning
Data augmentation
Explainable AI is especially important in which of the following domains?
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Healthcare
Finance
Gaming
Autonomous vehicles
Provide a real-world example where explainable AI could be critical.
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