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AIGP Practice Questions

Question # 1
You are part of your organization’s ML engineering team and notice that the accuracy of a model that was recently deployed into production is deteriorating. What is the best first step address this?
A. Replace the model with a previous version.
B. Conduct champion/challenger testing.
C. Perform an audit of the model.
D. Run red-teaming exercises.


B. Conduct champion/challenger testing.

Explanation:

When the accuracy of a model deteriorates, the best first step is to conduct champion/challenger testing. This involves deploying a new model (challenger) alongside the current model (champion) to compare their performance. This method helps identify if the new model can perform better under current conditions without immediately discarding the existing model. It provides a controlled environment to test improvements and understand the reasons behind the deterioration. This approach is preferable to directly replacing the model, performing audits, or running red-teaming exercises, which may be subsequent steps based on the findings from the champion/challenger testing.

[Reference: AIGP BODY OF KNOWLEDGE, sections on model performance management and testing strategies., , ]

Question # 2
What is the primary purpose of conducting ethical red-teaming on an Al system?
A. To improve the model's accuracy.
B. To simulate model risk scenarios.
C. To identify security vulnerabilities.
D. To ensure compliance with applicable law.


B. To simulate model risk scenarios.

Explanation:

The primary purpose of conducting ethical red-teaming on an AI system is to simulate model risk scenarios. Ethical red-teaming involves rigorously testing the AI system to identify potential weaknesses, biases, and vulnerabilities by simulating real-world attack or failure scenarios. This helps in proactively addressing issues that could compromise the system's reliability, fairness, and security.

Reference:

AIGP Body of Knowledge on AI Risk Management and Ethical AI Practices.

Question # 3
A company is working to develop a self-driving car that can independently decide the appropriate route to take the driver after the driver provides an address.

If they want to make this self-driving car “strong” Al, as opposed to "weak,” the engineers would also need to ensure?
A. Thatthe Al has full human cognitive abilities that can independently decide where to take the driver.
B. That they have obtained appropriate intellectual property (IP) licenses to use data for training the Al.
C. That the Al has strong cybersecurity to prevent malicious actors from taking control of the car.
D. That the Al can differentiate among ethnic backgrounds of pedestrians.


A. Thatthe Al has full human cognitive abilities that can independently decide where to take the driver.


Question # 4
What is the best reason for a company adopt a policy that prohibits the use of generative Al?
A. Avoid using technology that cannot be monetized.
B. Avoid needing to identify and hire qualified resources.
C. Avoid the time necessary to train employees on acceptable use.
D. Avoid accidental disclosure to its confidential and proprietary information.


D. Avoid accidental disclosure to its confidential and proprietary information.

Explanation:

The primary concern for a company adopting a policy prohibiting the use of generative AI is the risk of accidental disclosure of confidential and proprietary information. Generative AI tools can inadvertently leak sensitive data during the creation process or through data sharing. This risk outweighs the other reasons listed, as protecting sensitive information is critical to maintaining the company’s competitive edge and legal compliance. This rationale is discussed in the sections on risk management and data privacy in the IAPP AIGP Body of Knowledge.

Question # 5
Random forest algorithms are in what type of machine learning model?
A. Symbolic.
B. Generative.
C. Discriminative.
D. Natural language processing.


C. Discriminative.

Explanation:

Random forest algorithms are classified as discriminative models. Discriminative models are used to classify data by learning the boundaries between classes, which is the core functionality of random forest algorithms. They are used for classification and regression tasks by aggregating the results of multiple decision trees to make accurate predictions.

[Reference: The AIGP Body of Knowledge explains that discriminative models, including random forest algorithms, are designed to distinguish between different classes in the data, making them effective for various predictive modeling tasks​​., , ]

Question # 6
What is the key feature of Graphical Processing Units (GPUs) that makes them well-suited to running Al applications?
A. GPUs run many tasks concurrently, resulting in faster processing.
B. GPUs can access memory quickly, resulting in lower latency than CPUs.
C. GPUs can run every task on a computer, making them more robust than CPUs.
D. The number of transistors on GPUs doubles every two years, making thechips smaller and lighter.


A. GPUs run many tasks concurrently, resulting in faster processing.

Explanation:

GPUs (Graphical Processing Units) are well-suited to running AI applications due to their ability to run many tasks concurrently, which significantly enhances processing speed. This parallel processing capability makes GPUs ideal for handling the large-scale computations required in AI and deep learning tasks.

Reference:

AIGP BODY OF KNOWLEDGE, which explains the importance of compute infrastructure in AI applications​​.

Question # 7
CASE STUDY

Please use the following answer the next question:

XYZ Corp., a premier payroll services company that employs thousands of people globally, is embarking on a new hiring campaign and wants to implement policies and procedures to identify and retain the best talent. The new talent will help the company's product team expand its payroll offerings to companies in the healthcare and transportation sectors, including in Asia.

It has become time consuming and expensive for HR to review all resumes, and they are concerned that human reviewers might be susceptible to bias.

Address these concerns, the company is considering using a third-party Al tool to screen resumes and assist with hiring. They have been talking to several vendors about possibly obtaining a third-party Al-enabled hiring solution, as long as it would achieve its goals and comply with all applicable laws.

The organization has a large procurement team that is responsible for the contracting of technology solutions. One of the procurement team's goals is to reduce costs, and it often prefers lower-cost solutions. Others within the company are responsible for integrating and deploying technology solutions into the organization's operations in a responsible, cost-effective manner.

The organization is aware of the risks presented by Al hiring tools and wants to mitigate them. It also questions how best to organize and train its existing personnel to use the Al hiring tool responsibly. Their concerns are heightened by the fact that relevant laws vary across jurisdictions and continue to change.

All of the following are potential negative consequences created by using the Al tool when making hiring decisions EXCEPT?
A. Reputational harm.
B. Civil rights violations.
C. Discriminatory treatment.
D. Intellectual property infringement.


D. Intellectual property infringement.


Question # 8
What is the term for an algorithm that focuses on making the best choice achieve an immediate objective at a particular step or decision point, based on the available information and without regard for the longer-term best solutions?
A. Single-lane.
B. Optimized.
C. Efficient.
D. Greedy.


D. Greedy.

Explanation:

A greedy algorithm is one that makes the best choice at each step to achieve an immediate objective, without considering the longer-term consequences. It focuses on local optimization at each decision point with the hope that these local solutions will lead to an optimal global solution. However, greedy algorithms do not always produce the best overall solution for certain problems, but they are useful when an immediate, locally optimal solution is desired. Reference: AIGP Body of Knowledge, algorithm types section.

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IAPP AIGP Exam Dumps

Exam Name: Artificial Intelligence Governance Professional
Certification Name: Artificial Intelligence Governance

IAPP AIGP exam dumps are created by industry top professionals and after that its also verified by expert team. We are providing you updated Artificial Intelligence Governance Professional exam questions answers. We keep updating our Artificial Intelligence Governance practice test according to real exam. So prepare from our latest questions answers and pass your exam.

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  • Last Updation Date: 21-Jan-2025

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