ISQI CT-AI_v1.0_World : ISTQB Certified Tester AI Testing (v1.0)

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

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

2. ln the near future, technology will have evolved, and Al will be able to learn multiple tasks by itself without needing to be retrained, allowing it to operate even in new environments. The cognitive abilities of Al are similar to a child of 1-2 years.' In the above quote, which ONE of the following options is the correct name of this type of Al?
SELECT ONE OPTION

A) Super Al
B) Narrow Al
C) Technological singularity
D) General Al

3. A company producing consumable goods wants to identify groups of people with similar tastes for the purpose of targeting different products for each group. You have to choose and apply an appropriate ML type for this problem.
Which ONE of the following options represents the BEST possible solution for this above-mentioned task?
SELECT ONE OPTION

A) Association
B) Classification
C) Clustering
D) Regression

4. Which ONE of the following tests is LEAST likely to be performed during the ML model testing phase?
SELECT ONE OPTION

A) Testing the speed of the training of the model.
B) Testing the accuracy of the classification model.
C) Testing the API of the service powered by the ML model.
D) Testing the speed of the prediction by the model.

Solutions: