Question 1

A project involves integrating AI systems across multiple departments, each with different accesslevels. This complex AI project has presented the project manager with significant issues related todata misuse. The project team has been focused on their ethics guidelines but continues toexperience data misuse. The project involves different regional data protection regulations whichfurther increases the complexity.What issue will cause these challenges to occur?

Options :

A : Limited awareness of explainability requirements

B : Lack of a detailed plan addressing a governance strategy

C : Overlooking algorithmic bias and fairness concerns

D : Failure to implement robust encryption for data security

Answer: B

Question 2

After implementing an iteration of an Al solution, the project manager realizes that the system is notscalable due to high maintenance requirements. What is an effective way to address this issue?

Options :

A : Switch to a rule-based system to reduce maintenance complexity

B : Incorporate a generative Al approach to streamline model updates

C : Adopt a modular architecture to isolate different system components

D : Utilize cloud-based solutions to enhance maintenance scalability

Answer: C

Question 3

An aerospace company is in the data preparation phase of an AI project. The project team mustverify data quality to make a go/no-go decision for model development. They need to integrate datafrom several sensors with different sampling rates.What is an effective method that helps to ensure data consistency?

Options :

A : Developing a custom data integration framework

B : Utilizing data interpolation methods

C : Applying a real-time data synchronization protocol

D : Aggregating sensor data

Answer: B

Question 4

A government agency is using an AI system to analyze public data for policymaking decisions. The project manager needs to address risks related to data accuracy, privacy, and misuse. What represents the highest risk to the agency?

Options :

A : The AI system is not regularly updated with new data

B : The AI system relies on third-party providers

C : User data is stored in an unsecured database

D : The system lacks a transparency process

Answer: C

Question 5

A manufacturing company is operationalizing an AI-driven quality control system. The projectmanager needs to ensure data privacy and regulatory compliance due to the critical nature ofprotecting sensitive operational data.What is an effective technique that addresses these requirements?

Options :

A : Implementing a zero-trust architecture for network security

B : Utilizing a secure multiparty computation framework

C : Applying data anonymization to the dataset

D : Using a hybrid encryption scheme for storage

Answer: C