AIGP Exam UPDATED ACTUAL
QUESTIONS AND CORRECT ANSWERS
Accountability - CORRECT ANSWER The obligation and responsibility of the
creators, operators and regulators of an AI system to ensure the system operates in a manner
that is ethical, fair, transparent and compliant with applicable rules and regulations (see
fairness and transparency). Accountability ensures the actions, decisions and outcomes of an
AI system can be traced back to the entity responsible for it
Active Learning - CORRECT ANSWER A subfield of AI and machine learning where
an algorithm can select some of the data it learns from. Instead of learning from all the data it
is given, an active learning model requests additional data points that will help it learn the
best. → Also called query learning.
Adversarial Machine Learning - CORRECT ANSWER A machine learning technique
that raises a safety and security risk to the model and can be seen as an attack. These attacks
can be instigated by manipulating the model, such as by introducing malicious or deceptive
input data. Such attacks can cause the model to malfunction and generate incorrect or unsafe
outputs, which can have significant impacts. For example, manipulating the inputs of a self-
driving car may fool the model to perceive a red light as a green one, adversely impacting
road safety.
AI governance - CORRECT ANSWER A system of laws, policies, frameworks,
practices and processes at international, national and organizational levels. AI governance
helps various stakeholders implement, manage and oversee the use of AI technology. It also
helps manage associated risks to ensure AI aligns with stakeholders' objectives, is developed
and used responsibly and ethically, and complies with applicable requirements.
Algorithm - CORRECT ANSWER A procedure or set of instructions and rules
designed to perform a specific task or solve a particular problem, using a computer.
AGI - CORRECT ANSWER Artificial General Intelligence
AI that is considered to have human-level intelligence and strong generalization capability to
achieve goals and carry out a variety of tasks in different contexts and environments. AGI
,still remains a theoretical field of research. It is contrasted with "narrow" AI, which is used
for specific tasks or problems.
.beyond reach right now
.experts expect AGI systems to have strong generalization abilities, the ability to think, learn
and perform complex tasks, and achieve goals in different contexts and environments
Artificial Intelligence - CORRECT ANSWER Artificial intelligence is a broad term
used to describe an engineered system that uses various computational techniques to perform
or automate tasks. This may include techniques, such as machine learning, where machines
learn from experience, adjusting to new input data and potentially performing tasks
previously done by humans. More specifically, it is a field of computer science dedicated to
simulating intelligent behavior in computers. It may include automated decision-making. →
Acronym: AI
.has hallmarks of human intelligence: ability to think creatively; can consider various
possibilities; & keep a goal in mind while making short term decisions,
.common elements in a definition of AI:
1. Technology: use of technology and specified objectives for the technology to achieve
2. Autonomy: level of autonomy by the technology to achieve defined objectives
3. Human Involvement: need for human input to train the technology and identify objectives
for it to follow
4. Output: technology produces output - performing tasks, solving problems, producing
content
Automated Decision Making - CORRECT ANSWER The process of making a
decision by technological means without human involvement, either in whole or in part.
Bias - CORRECT ANSWER There are several types of bias within the AI field.
Computational bias is a systematic error or deviation from the true value of a prediction that
originates from a model's assumptions or the input data itself. Cognitive bias refers to
inaccurate individual judgment or distorted thinking, while societal bias leads to systemic
,prejudice, favoritism and/or discrimination in favor of or against an individual or group. Bias
can impact outcomes and pose a risk to individual rights and liberties.
Bootstrap Aggregating - CORRECT ANSWER A machine learning method that
aggregates multiple versions of a model (see machine learning model) trained on random
subsets of a dataset. This method aims to make a model more stable and accurate. →
Sometimes referred to as bagging
Chatbot - CORRECT ANSWER A form of AI designed to simulate human-like
conversations and interactions that uses natural language processing and deep learning to
understand and respond to text or other media. Because chatbots are often used for customer
service and other personal help applications, chatbots often ingest users' personal
information.
Classification Model - CORRECT ANSWER A type of model (see machine learning
model) used in machine learning that is designed to take input data and sort it into different
categories or classes. → Sometimes referred to as classifiers
Clustering - CORRECT ANSWER An unsupervised machine learning method where
patterns in the data are identified and evaluated, and data points are grouped accordingly into
clusters based on their similarity. → Sometimes referred to as clustering algorithms.
Compute - CORRECT ANSWER Refers to the processing resources that are available
to a computer system. This includes the hardware components such as the central processing
unit or graphics processing unit. Computing is essential for memory, storage, processing data,
running applications, rendering graphics for visual media, powering cloud computing, among
others.
Computer Vision - CORRECT ANSWER A field of AI that enables computers to
process and analyze images, videos and other visual inputs.
Conformity Assessment - CORRECT ANSWER An analysis, often performed by a
third-party body, on an AI system to determine whether requirements, such as establishing a
risk-management system, data governance, record keeping, transparency and cybersecurity
practices, have been met. Often referred to as an audit.
, Contestability - CORRECT ANSWER The principle of ensuring that AI systems and
their decision-making processes can be questioned or challenged. This ability to contest or
challenge the outcomes, outputs and/or actions of AI systems can help promote transparency
and accountability within AI governance. → Also called redress.
Corpus - CORRECT ANSWER A large collection of texts or data that a computer uses
to find patterns, make predictions or generate specific outcomes. The corpus may include
structured or unstructured data and cover a specific topic or a variety of topics.
Decision Tree - CORRECT ANSWER A type of supervised learning model used in
machine learning (see machine learning model) that represents decisions and their potential
consequences in a branching structure.
Deep Learning - CORRECT ANSWER A subfield of AI and machine learning that
uses artificial neural networks. Deep learning is especially useful in fields where raw data
needs to be processed, like image recognition, natural language processing and speech
recognition.
Deepfakes - CORRECT ANSWER Audiovisual content that has been altered or
manipulated using AI techniques. Deepfakes can be used to spread misinformation and
disinformation.
Discriminative Model - CORRECT ANSWER A type of model (see machine learning
model) used in machine learning that directly maps input features to class labels and analyzes
for patterns that can help distinguish between different classes. It is often used for text
classification tasks, like identifying the language of a piece of text. Examples are traditional
neural networks, decision trees and random forests.
Disinformation - CORRECT ANSWER Audiovisual content, information and synthetic
data that is intentionally manipulated or created to cause harm. Disinformation can spread
through deepfakes by those with malicious intentions.
QUESTIONS AND CORRECT ANSWERS
Accountability - CORRECT ANSWER The obligation and responsibility of the
creators, operators and regulators of an AI system to ensure the system operates in a manner
that is ethical, fair, transparent and compliant with applicable rules and regulations (see
fairness and transparency). Accountability ensures the actions, decisions and outcomes of an
AI system can be traced back to the entity responsible for it
Active Learning - CORRECT ANSWER A subfield of AI and machine learning where
an algorithm can select some of the data it learns from. Instead of learning from all the data it
is given, an active learning model requests additional data points that will help it learn the
best. → Also called query learning.
Adversarial Machine Learning - CORRECT ANSWER A machine learning technique
that raises a safety and security risk to the model and can be seen as an attack. These attacks
can be instigated by manipulating the model, such as by introducing malicious or deceptive
input data. Such attacks can cause the model to malfunction and generate incorrect or unsafe
outputs, which can have significant impacts. For example, manipulating the inputs of a self-
driving car may fool the model to perceive a red light as a green one, adversely impacting
road safety.
AI governance - CORRECT ANSWER A system of laws, policies, frameworks,
practices and processes at international, national and organizational levels. AI governance
helps various stakeholders implement, manage and oversee the use of AI technology. It also
helps manage associated risks to ensure AI aligns with stakeholders' objectives, is developed
and used responsibly and ethically, and complies with applicable requirements.
Algorithm - CORRECT ANSWER A procedure or set of instructions and rules
designed to perform a specific task or solve a particular problem, using a computer.
AGI - CORRECT ANSWER Artificial General Intelligence
AI that is considered to have human-level intelligence and strong generalization capability to
achieve goals and carry out a variety of tasks in different contexts and environments. AGI
,still remains a theoretical field of research. It is contrasted with "narrow" AI, which is used
for specific tasks or problems.
.beyond reach right now
.experts expect AGI systems to have strong generalization abilities, the ability to think, learn
and perform complex tasks, and achieve goals in different contexts and environments
Artificial Intelligence - CORRECT ANSWER Artificial intelligence is a broad term
used to describe an engineered system that uses various computational techniques to perform
or automate tasks. This may include techniques, such as machine learning, where machines
learn from experience, adjusting to new input data and potentially performing tasks
previously done by humans. More specifically, it is a field of computer science dedicated to
simulating intelligent behavior in computers. It may include automated decision-making. →
Acronym: AI
.has hallmarks of human intelligence: ability to think creatively; can consider various
possibilities; & keep a goal in mind while making short term decisions,
.common elements in a definition of AI:
1. Technology: use of technology and specified objectives for the technology to achieve
2. Autonomy: level of autonomy by the technology to achieve defined objectives
3. Human Involvement: need for human input to train the technology and identify objectives
for it to follow
4. Output: technology produces output - performing tasks, solving problems, producing
content
Automated Decision Making - CORRECT ANSWER The process of making a
decision by technological means without human involvement, either in whole or in part.
Bias - CORRECT ANSWER There are several types of bias within the AI field.
Computational bias is a systematic error or deviation from the true value of a prediction that
originates from a model's assumptions or the input data itself. Cognitive bias refers to
inaccurate individual judgment or distorted thinking, while societal bias leads to systemic
,prejudice, favoritism and/or discrimination in favor of or against an individual or group. Bias
can impact outcomes and pose a risk to individual rights and liberties.
Bootstrap Aggregating - CORRECT ANSWER A machine learning method that
aggregates multiple versions of a model (see machine learning model) trained on random
subsets of a dataset. This method aims to make a model more stable and accurate. →
Sometimes referred to as bagging
Chatbot - CORRECT ANSWER A form of AI designed to simulate human-like
conversations and interactions that uses natural language processing and deep learning to
understand and respond to text or other media. Because chatbots are often used for customer
service and other personal help applications, chatbots often ingest users' personal
information.
Classification Model - CORRECT ANSWER A type of model (see machine learning
model) used in machine learning that is designed to take input data and sort it into different
categories or classes. → Sometimes referred to as classifiers
Clustering - CORRECT ANSWER An unsupervised machine learning method where
patterns in the data are identified and evaluated, and data points are grouped accordingly into
clusters based on their similarity. → Sometimes referred to as clustering algorithms.
Compute - CORRECT ANSWER Refers to the processing resources that are available
to a computer system. This includes the hardware components such as the central processing
unit or graphics processing unit. Computing is essential for memory, storage, processing data,
running applications, rendering graphics for visual media, powering cloud computing, among
others.
Computer Vision - CORRECT ANSWER A field of AI that enables computers to
process and analyze images, videos and other visual inputs.
Conformity Assessment - CORRECT ANSWER An analysis, often performed by a
third-party body, on an AI system to determine whether requirements, such as establishing a
risk-management system, data governance, record keeping, transparency and cybersecurity
practices, have been met. Often referred to as an audit.
, Contestability - CORRECT ANSWER The principle of ensuring that AI systems and
their decision-making processes can be questioned or challenged. This ability to contest or
challenge the outcomes, outputs and/or actions of AI systems can help promote transparency
and accountability within AI governance. → Also called redress.
Corpus - CORRECT ANSWER A large collection of texts or data that a computer uses
to find patterns, make predictions or generate specific outcomes. The corpus may include
structured or unstructured data and cover a specific topic or a variety of topics.
Decision Tree - CORRECT ANSWER A type of supervised learning model used in
machine learning (see machine learning model) that represents decisions and their potential
consequences in a branching structure.
Deep Learning - CORRECT ANSWER A subfield of AI and machine learning that
uses artificial neural networks. Deep learning is especially useful in fields where raw data
needs to be processed, like image recognition, natural language processing and speech
recognition.
Deepfakes - CORRECT ANSWER Audiovisual content that has been altered or
manipulated using AI techniques. Deepfakes can be used to spread misinformation and
disinformation.
Discriminative Model - CORRECT ANSWER A type of model (see machine learning
model) used in machine learning that directly maps input features to class labels and analyzes
for patterns that can help distinguish between different classes. It is often used for text
classification tasks, like identifying the language of a piece of text. Examples are traditional
neural networks, decision trees and random forests.
Disinformation - CORRECT ANSWER Audiovisual content, information and synthetic
data that is intentionally manipulated or created to cause harm. Disinformation can spread
through deepfakes by those with malicious intentions.
