A bank is deploying a credit-scoring AI system that uses a deep neural network. The system must comply with GDPR, and the bank must be able to explain decisions to customers. The team is selecting test techniques. Which combination of techniques is most appropriate?

Adversarial testing and robustness testing

White-box testing and coverage analysis

Black-box testing with explainability tools and fairness metrics

Metamorphic testing and differential testing

A team is evaluating a binary classification model for fraud detection. The dataset is highly imbalanced, with very few fraudulent transactions. They need to choose a primary evaluation metric. Which metric is most appropriate?

Precision and recall (or F1-score)

Which factor is most likely to influence the selection of test techniques for an AI-based system?

The type of AI system and the associated risk level

The number of developers on the team

The color scheme of the user interface

The programming language used to implement the system

A team is preparing to test a sentiment analysis model. They have a dataset of customer reviews, but they suspect the dataset contains duplicate entries and mislabeled examples. Which technique should they use to validate the data?

Metamorphic testing to verify input-output relations

Adversarial testing to find model vulnerabilities

Model evaluation using accuracy metrics

Data profiling to identify duplicates and inconsistencies

Certified Tester AI Testing

Domain 9Objective 8

Selecting Test Techniques for AI-Based Systems CT-AI Practice Questions (Page 2)

Part of the Domain 9: Methods and Techniques for the Testing of AI-Based Systems domain, which makes up ~13% of our current practice bank. ISTQB does not publish an official question count, but from its 60-minute exam (~25–40 total, ~3–5 in this domain), expect 1–1 from this objective — we provide 31 practice questions to prepare you well beyond it. (estimate)

31questions here

7free pages

7concepts

Questions 6–10

6application · medium
A bank is deploying a credit-scoring AI system that uses a deep neural network. The system must comply with GDPR, and the bank must be able to explain decisions to customers. The team is selecting test techniques. Which combination of techniques is most appropriate?
Select an answer first
7application · medium
A team is evaluating a binary classification model for fraud detection. The dataset is highly imbalanced, with very few fraudulent transactions. They need to choose a primary evaluation metric. Which metric is most appropriate?
Select an answer first
8foundation · easy
Which AI-specific test technique involves testing the system with intentionally crafted inputs designed to cause incorrect behavior?
Select an answer first
9foundation · easy
Which factor is most likely to influence the selection of test techniques for an AI-based system?
Select an answer first
10application · easy
A team is preparing to test a sentiment analysis model. They have a dataset of customer reviews, but they suspect the dataset contains duplicate entries and mislabeled examples. Which technique should they use to validate the data?
Select an answer first

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