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ISQI CT-AI_v1.0_World Exam Syllabus Topics:

ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:

Question 1

Which ONE of the following statements is a CORRECT adversarial example in the context of machine learning systems that are working on image classifiers.
SELECT ONE OPTION

A. These examples are model specific and are not likely to cause another model trained on same task to fail.
B. Black box attacks based on adversarial examples create an exact duplicate model of the original.
C. These attacks can't be prevented by retraining the model with these examples augmented tothe training data.
D. These attack examples cause a model to predict the correct class with slightly less accuracy even though they look like the original image.

Question 2

In a certain coffee producing region of Colombia, there have been some severe weather storms, resulting in massive losses in production. This caused a massive drop in stock price of coffee.
Which ONE of the following types of testing SHOULD be performed for a machine learning model for stock-price prediction to detect influence of such phenomenon as above on price of coffee stock.
SELECT ONE OPTION

A. Testing for security
B. Testing for accuracy
C. Testing for bias
D. Testing for concept drift

Question 3

Max. Score: 2
Al-enabled medical devices are used nowadays for automating certain parts of the medical diagnostic processes. Since these are life-critical process the relevant authorities are considenng bringing about suitable certifications for these Al enabled medical devices. This certification may involve several facets of Al testing (I - V).
I.Autonomy
II.Maintainability
III.Safety
IV.Transparency
V.Side Effects
Which ONE of the following options contains the three MOST required aspects to be satisfied for the above scenario of certification of Al enabled medical devices?
SELECT ONE OPTION

A. Aspects II, III and IV
B. Aspects III, IV, and V
C. Aspects I, II, and III
D. Aspects I, IV, and V

Question 4

"BioSearch" is creating an Al model used for predicting cancer occurrence via examining X-Ray images. The accuracy of the model in isolation has been found to be good. However, the users of the model started complaining of the poor quality of results, especially inability to detect real cancer cases, when put to practice in the diagnosis lab, leading to stopping of the usage of the model.
A testing expert was called in to find the deficiencies in the test planning which led to the above scenario.
Which ONE of the following options would you expect to MOST likely be the reason to be discovered by the test expert?
SELECT ONE OPTION

A. The input data has not been tested for quality prior to use for testing.
B. A lack of focus on non-functional requirements testing.
C. A lack of similarity between the training and testing data.
D. A lack of focus on choosing the right functional-performance metrics.

Solutions: