Question 1

Your team is working on a new facial recognition application. Since this technology has the potential to be mis-used you think it's important to set guidelines for the proper use of this application and you want to make sure the AI system is built for some positive purpose. What area of Trustworthy AI does this best fall under?

Options :

A : Transparent AI

B : Governed AI

C : Responsible AI

D : Explainable AI

Answer: C

Question 2

During which phase of an AI project should you consider Trustworthy AI considerations?

Options :

A : Phase I: Business Understanding

B : Phase II: Data Understanding

C : Phase VI: Model Operationalization

D : Every Phase of the AI project

Answer: D

Question 3

A project manager meets with a customer for initial discussions about an upcoming project. At the end of the meeting, the customer asks the project manager for a rough estimate of the project duration. Based on her experience with three similar projects, the project manager provides an estimate of 8-10 months. What's wrong with this timeframe?

Options :

A : It's underestimating the project timeline by 3 months

B : It fits into a waterfall timeframe, but not an agile project timeframe

C : It's not accounting for data preparation timelines

D : It's not accounting for potential project delays

Answer: D

Question 4

Your team has collected petabytes of data for your AI project. As the project lead, you understand this is too much data to use for this iteration of the project. What is the best course of action to take with this data?

Options :

A : Data selection and attribute pruning to reduce overall size and data complexity.

B : Data Deduping to reduce overall size and data complexity.

C : Data integration focused on reducing the number of data sources.

D : Careful algorithm selection that reduces the need for data.

Answer: A

Question 5

Your team is working on a new loan decision model that takes a number of factors and data points into consideration and then automatically approves or denies a loan. After a month in operation someone does a review and notices that the system is denying a large number of loans from a certain demographic when all other factors from people in other regions (such as age, salary, and credit score) are the same. What is most likely happening here?

Options :

A : Biased data sets leading to algorithmic discrimination

B : Generative AI models hallucinating data results

C : Nothing is wrong, algorithmic decisions will never be 100%

D : Data privacy issues leading to data sharing concerns

Answer: A

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