Free iSQI CT-AI_v1.0_World Exam Questions

Question 1

Consider a machine learning model where the model is attempting to predict if a patient is at risk for stroke. The model collects information on each patient regarding their blood pressure, red blood cell count, smoking, status, history of heart disease, cholesterol level, and demographics. Then, using a decision tree the model predicts whether or not the associated patient is likely to have a stroke in the near future. One the model is created using a training data set, it is used to predict a stroke in 80 additional patients. The table below shows a confusion matrix on whether or not the model mode a correct or incorrect prediction. The testers have calculated what they believe to be an appropriate functional performance metric for the model. They calculated a value of 2/3 or 0.6667.

A : F1 –source

B : Precision

C : Recall

D : Accuracy

Answer: D

Question 2

Which of the following characteristics of AI-based systems make it more difficult to ensure they are safe?

A : Simplicity

B : Sustainability

C : Non-determinism

D : Robustness

Answer: C

Question 3

There is a growing backlog of unresolved defects for your project. You know the developers have an ML model that they have created which has learned which developers work on which type of software and the speed with which they resolve issues. How could you use this model to help reduce the backlog and implement more efficient defect resolution?

A : Use it to prioritize defects automatically based on the time expected for the fix to be made, the speed of the fix, and the likelihood of regressions.

B : Use it to assign defects to the best developer to resolve the problem and to load balance the defect assignments among the developers.

C : Use it to determine the root cause of each defect and develop a process improvement plan that can be implemented to remove the most common root causes.

D : Use it to review the code and determine where more defects are likely to occur so that testing can be targeted to those areas.

Answer: B

Question 4

Consider a machine learning model where the model is attempting to predict if a patient is at risk for stroke. The model collects information on each patient regarding their blood pressure, red blood cell count, smoking, status, history of heart disease, cholesterol level, and demographics. Then, using a decision tree the model predicts whether or not the associated patient is likely to have a stroke in the near future. One the model is created using a training data set, it is used to predict a stroke in 80 additional patients. The table below shows a confusion matrix on whether or not the model mode a correct or incorrect prediction. The testers have calculated what they believe to be an appropriate functional performance metric for the model. They calculated a value of 2/3 or 0.6667.

A : F1 –source

B : Precision

C : Recall

D : Accuracy

Answer: D

Question 5

Which of the following is an example of an input change where it would be expected that the AI system should be able to adapt?

A : It has been trained to recognize cats and is given an image of a dog.

B : It has been trained to recognize human faces at a particular resolution and it is given a human face image captured with a higher resolution.

C : It has been trained to analyze mathematical models and is given a set of landscape pictures to classify.

D : It has been trained to analyze customer buying trend data and is given information on supplier cost data.

Answer: B