Which testing technique is BEST for determining how an AI model makes decisions?

The correct answer is C. White box. White box testing gives the tester full visibility into the internal workings of the system - including code, model architecture, weights, training data, and decision logic. This transparency is essential for understanding HOW a model arrives at its outputs, making it ideal for…

AI Security Assurance and Resilience

Question

Options

ARed team
BBlack box
CWhite box
DBlue team

How the community answered

(27 responses)

A
4% (1)
C
89% (24)
D
7% (2)

Explanation

White box testing gives the tester full visibility into the internal workings of the system - including code, model architecture, weights, training data, and decision logic. This transparency is essential for understanding HOW a model arrives at its outputs, making it ideal for interpretability and explainability analysis. Black box testing (B) examines only inputs and outputs with no internal visibility, so it can identify what decisions were made but not why. Red teaming (A) focuses on adversarial exploitation of vulnerabilities. Blue teaming (D) is a defensive monitoring and detection function, not a model analysis technique.

Topics

#AI testing#White box testing#AI explainability#Model interpretability

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