IAPP aigp practice test

Exam Title: Artificial Intelligence Governance Professional

Last update: Nov 27 ,2025
Question 1

Which of the following is a subcategory of Al and machine learning that uses labeled datasets to train
algorithms?

  • A. Segmentation.
  • B. Generative Al.
  • C. Expert systems.
  • D. Supervised learning.
Answer:

D


Explanation:
Supervised learning is a subcategory of AI and machine learning where labeled datasets are used to
train algorithms. This process involves feeding the algorithm a dataset where the input-output pairs
are known, allowing the algorithm to learn and make predictions or decisions based on new, unseen
data. Reference: AIGP BODY OF KNOWLEDGE, which describes supervised learning as a model
trained on labeled data (e.g., text recognition, detecting spam in emails)​​.

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Question 2

A company developed Al technology that can analyze text, video, images and sound to tag content,
including the names of animals, humans and objects.
What type of Al is this technology classified as?

  • A. Deductive inference.
  • B. Multi-modal model.
  • C. Transformative Al.
  • D. Expert system.
Answer:

B


Explanation:
A multi-modal model is an AI system that can process and analyze multiple types of data, such as
text, video, images, and sound. This type of AI integrates different data sources to enhance its
understanding and decision-making capabilities. In the given scenario, the AI technology that tags
content including names of animals, humans, and objects falls under this category. Reference: AIGP
BODY OF KNOWLEDGE, which outlines the capabilities and use cases of multi-modal models​​.

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Question 3

All of the following are common optimization techniques in deep learning to determine weights that
represent the strength of the connection between artificial neurons EXCEPT?

  • A. Gradient descent, which initially sets weights arbitrary values, and then at each step changes them.
  • B. Momentum, which improves the convergence speed and stability of neural network training.
  • C. Autoregression, which analyzes and makes predictions about time-series data.
  • D. Backpropagation, which starts from the last layer working backwards.
Answer:

C


Explanation:
Autoregression is not a common optimization technique in deep learning to determine weights for
artificial neurons. Common techniques include gradient descent, momentum, and backpropagation.
Autoregression is more commonly associated with time-series analysis and forecasting rather than
neural network optimization. Reference: AIGP BODY OF KNOWLEDGE, which discusses common
optimization techniques used in deep learning​​.

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Question 4

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.
Answer:

A


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​​.

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Question 5

Which of the following best defines an "Al model"?

  • A. A system that applies defined rules to execute tasks.
  • B. A system of controls that is used to govern an Al algorithm.
  • C. A corpus of data which an Al algorithm analyzes to make predictions.
  • D. A program that has been trained on a set of data to find patterns within the data.
Answer:

D


Explanation:
An AI model is best defined as a program that has been trained on a set of data to find patterns
within that data. This definition captures the essence of machine learning, where the model learns
from the data to make predictions or decisions. Reference: AIGP BODY OF KNOWLEDGE, which
provides a detailed explanation of AI models and their training processes​​.

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Question 6

CASE STUDY
Please use the following answer the next question:
Good Values Corporation (GVC) is a U.S. educational services provider that employs teachers to
create and deliver enrichment courses for high school students. GVC has learned that many of its
teacher employees are using generative Al to create the enrichment courses, and that many of the
students are using generative Al to complete their assignments.
In particular, GVC has learned that the teachers they employ used open source large language
models (“LLM”) to develop an online tool that customizes study questions for individual students.
GVC has also discovered that an art teacher has expressly incorporated the use of generative Al into
the curriculum to enable students to use prompts to create digital art.
GVC has started to investigate these practices and develop a process to monitor any use of
generative Al, including by teachers and students, going forward.
Which of the following risks should be of the highest concern to individual teachers using generative
Al to ensure students learn the course material?

  • A. Financial cost.
  • B. Model accuracy.
  • C. Technical complexity.
  • D. Copyright infringement.
Answer:

B


Explanation:
The highest concern for individual teachers using generative AI to ensure students learn the course
material is model accuracy. Ensuring that the AI-generated content is accurate and relevant to the
curriculum is crucial for effective learning. If the AI model produces inaccurate or irrelevant content,
it can mislead students and hinder their understanding of the subject matter.
Reference: According to the AIGP Body of Knowledge, one of the core risks posed by AI systems is the
accuracy of the data and models used. Ensuring the accuracy of AI-generated content is essential for
maintaining the integrity of the educational material and achieving the desired learning outcomes​​.

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Question 7

CASE STUDY
Please use the following answer the next question:
Good Values Corporation (GVC) is a U.S. educational services provider that employs teachers to
create and deliver enrichment courses for high school students. GVC has learned that many of its
teacher employees are using generative Al to create the enrichment courses, and that many of the
students are using generative Al to complete their assignments.
In particular, GVC has learned that the teachers they employ used open source large language
models (“LLM”) to develop an online tool that customizes study questions for individual students.
GVC has also discovered that an art teacher has expressly incorporated the use of generative Al into
the curriculum to enable students to use prompts to create digital art.
GVC has started to investigate these practices and develop a process to monitor any use of
generative Al, including by teachers and students, going forward.
What is the best reason for GVC to offer students the choice to utilize generative Al in limited,
defined circumstances?

  • A. Toenable students to learn how to manage their time.
  • B. Toenable students to learn about performing research.
  • C. Toenable students to learn about practical applications of Al.
  • D. Toenable students to learn how to use Al as a supportiveeducational tool.
Answer:

D


Explanation:
The best reason for GVC to offer students the choice to utilize generative AI in limited, defined
circumstances is to enable students to learn how to use AI as a supportive educational tool. By
integrating AI in a controlled manner, students can learn the practical applications of AI and develop
skills to use AI responsibly and effectively in their educational pursuits.
Reference: The AIGP Body of Knowledge highlights the importance of teaching students about AI's
practical applications and the responsible use of AI technologies. This aligns with the goal of
fostering a better understanding of AI's role and its potential benefits in various contexts, including
education​​.

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Question 8

CASE STUDY
Please use the following answer the next question:
Good Values Corporation (GVC) is a U.S. educational services provider that employs teachers to
create and deliver enrichment courses for high school students. GVC has learned that many of its
teacher employees are using generative Al to create the enrichment courses, and that many of the
students are using generative Al to complete their assignments.
In particular, GVC has learned that the teachers they employ used open source large language
models (“LLM”) to develop an online tool that customizes study questions for individual students.
GVC has also discovered that an art teacher has expressly incorporated the use of generative Al into
the curriculum to enable students to use prompts to create digital art.
GVC has started to investigate these practices and develop a process to monitor any use of
generative Al, including by teachers and students, going forward.
All of the following may be copyright risks from teachers using generative Al to create course content
EXCEPT?

  • A. Content created by an LLM may be protectable under U.S. intellectual property law.
  • B. Generative Al is generally trained using intellectual property owned by third parties.
  • C. Students must expressly consent to this use of generative Al.
  • D. Generative Al often creates content without attribution.
Answer:

C


Explanation:
All of the options listed may pose copyright risks when teachers use generative AI to create course
content, except for students must expressly consent to this use of generative AI. While obtaining
student consent is essential for ethical and privacy reasons, it does not directly relate to copyright
risks associated with the creation and use of AI-generated content.
Reference: The AIGP Body of Knowledge discusses the importance of addressing intellectual property
(IP) risks when using AI-generated content. Copyright risks are typically associated with the use of
third-party data and the lack of attribution, rather than the consent of users​​.

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Question 9

Random forest algorithms are in what type of machine learning model?

  • A. Symbolic.
  • B. Generative.
  • C. Discriminative.
  • D. Natural language processing.
Answer:

C


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​​.

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Question 10

What is the 1956 Dartmouth summer research project on Al best known as?

  • A. A meeting focused on the impacts of the launch of the first mass-produced computer.
  • B. A research project on the impacts of technology on society.
  • C. A research project to create a test for machine intelligence.
  • D. A meeting focused on the founding of the Al field.
Answer:

D


Explanation:
The 1956 Dartmouth summer research project on AI is best known as a meeting focused on the
founding of the AI field. This conference is historically significant because it marked the formal
beginning of artificial intelligence as an academic discipline. The term "artificial intelligence" was
coined during this event, and it laid the foundation for future research and development in AI.
Reference: The AIGP Body of Knowledge highlights the importance of the Dartmouth Conference as a
pivotal moment in the history of AI, which established AI as a distinct field of study and research​​.

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