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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) The input data has not been tested for quality prior to use for testing.
D) A lack of similarity between the training and testing data.

2. An image classification system is being trained for classifying faces of humans. The distribution of the data is
70% ethnicity A and 30% for ethnicities B, C and D. Based ONLY on the above information, which of the following options BEST describes the situation of this image classification system?
SELECT ONE OPTION

A) This is an example of sample bias.
B) This is an example of algorithmic bias.
C) This is an example of hyperparameter bias.
D) This is an example of expert system bias.

3. "Splendid Healthcare" has started developing a cancer detection system based on ML. The type of cancer they plan on detecting has 2% prevalence rate in the population of a particular geography. It is required that the model performs well for both normal and cancer patients.
Which ONE of the following combinations requires MAXIMIZATION?
SELECT ONE OPTION

A) Maximize precision and accuracy
B) Maximize accuracy and recall
C) Maximize recall and precision
D) Maximize specificity number of classes

4. A software component uses machine learning to recognize the digits from a scan of handwritten numbers. In the scenario above, which type of Machine Learning (ML) is this an example of?
SELECT ONE OPTION

A) Reinforcement learning
B) Clustering
C) Regression
D) Classification

Solutions: