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AIGP Practice Questions

Question # 1
Which of the following most encourages accountability over Al systems?
A. Determining the business objective and success criteria for the Al project.
B. Performing due diligence on third-party Al training and testing data.
C. Defining the roles and responsibilities of Al stakeholders.
D. Understanding Al legal and regulatory requirements.


C. Defining the roles and responsibilities of Al stakeholders.

Explanation:

Defining the roles and responsibilities of AI stakeholders is crucial for encouraging accountability over AI systems. Clear delineation of who is responsible for different aspects of the AI lifecycle ensures that there is a person or team accountable for monitoring, maintaining, and addressing issues that arise. This accountability framework helps in ensuring that ethical standards and regulatory requirements are met, and it facilitates transparency and traceability in AI operations. By assigning specific roles, organizations can better manage and mitigate risks associated with AI deployment and use.


Question # 2
Training data is best defined as a subset of data that is used to?
A. Enable a model to detect and learn patterns.
B. Fine-tune a model to improve accuracy and prevent overfitting.
C. Detect the initial sources of biases to mitigate prior to deployment.
D. Resemble the structure and statistical properties of production data.


A. Enable a model to detect and learn patterns.

Explanation:

Training data is used to enable a model to detect and learn patterns. During the training phase, the model learns from the labeled data, identifying patterns and relationships that it will later use to make predictions on new, unseen data. This process is fundamental in building an AI model's capability to perform tasks accurately. Reference: AIGP Body of Knowledge on Model Training and Pattern Recognition.


Question # 3
All of the following are penalties and enforcements outlined in the EU Al Act EXCEPT?
A. Fines for SMEs and startups will be proportionally capped.
B. Rules on General Purpose Al will apply after 6 months as a specific provision.
C. The Al Pact will act as a transitional bridge until the Regulations are fully enacted.
D. Fines for violations of banned Al applications will be €35 million or 7% global annual turnover (whichever is higher).


C. The Al Pact will act as a transitional bridge until the Regulations are fully enacted.



Question # 4
Each of the following actors are typically engaged in the Al development life cycle EXCEPT?
A. Data architects.
B. Government regulators.
C. Socio-cultural and technical experts.
D. Legal and privacy governance experts.


B. Government regulators.

Explanation:

Typically, actors involved in the AI development life cycle include data architects (who design the data frameworks), socio-cultural and technical experts (who ensure the AI system is socio-culturally aware and technically sound), and legal and privacy governance experts (who handle the legal and privacy aspects). Government regulators, while important, are not directly engaged in the development process but rather oversee and regulate the industry.

Reference:

AIGP BODY OF KNOWLEDGE and AI development frameworks.


Question # 5
To maintain fairness in a deployed system, it is most important to?
A. Protect against loss of personal data in the model.
B. Monitor for data drift that may affect performance and accuracy.
C. Detect anomalies outside established metrics that require new training data.
D. Optimize computational resources and data to ensure efficiency and scalability.


B. Monitor for data drift that may affect performance and accuracy.

Explanation:

To maintain fairness in a deployed system, it is crucial to monitor for data drift that may affect performance and accuracy. Data drift occurs when the statistical properties of the input data change over time, which can lead to a decline in model performance. Continuous monitoring and updating of the model with new data ensure that it remains fair and accurate, adapting to any changes in the data distribution. Reference: AIGP Body of Knowledge on Post-Deployment Monitoring and Model Maintenance.


Question # 6
Pursuant to the White House Executive Order of November 2023, who is responsible for creating guidelines to conduct red-teaming tests of Al systems?
A. National Institute of Standards and Technology (NIST).
B. National Science and Technology Council (NSTC).
C. Office of Science and Technology Policy (OSTP).
D. Department of Homeland Security (DHS).


A. National Institute of Standards and Technology (NIST).

Explanation:

The White House Executive Order of November 2023 designates the National Institute of Standards and Technology (NIST) as the responsible body for creating guidelines to conduct red-teaming tests of AI systems. NIST is tasked with developing and providing standards and frameworks to ensure the security, reliability, and ethical deployment of AI systems, including conducting rigorous red-teaming exercises to identify vulnerabilities and assess risks in AI systems.

[Reference: AIGP BODY OF KNOWLEDGE, sections on AI governance and regulatory frameworks, and the White House Executive Order of November 2023., , ]


Question # 7
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.


C. Autoregression, which analyzes and makes predictions about time-series data.

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​​.


Question # 8
According to the GDPR, an individual has the right to have a human confirm or replace an automated decision unless that automated decision?
A. Is authorized with the data subject s explicit consent.
B. Is authorized by applicable Ell law and includes suitable safeguards.
C. Is deemed to solely benefit the individual and includes documented legitimate interests.
D. Is necessary for entering into or performing under a contract between the data subject and data controller.


A. Is authorized with the data subject s explicit consent.

Explanation:

According to the GDPR, individuals have the right to not be subject to a decision based solely on automated processing, including profiling, which produces legal effects or similarly significantly affects them. However, there are exceptions to this right, one of which is when the decision is based on the data subject's explicit consent. This means that if an individual explicitly consents to the automated decision-making process, there is no requirement for human intervention to confirm or replace the decision. This exception ensures that individuals can have control over automated decisions that affect them, provided they have given clear and informed consent.


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IAPP AIGP Exam Dumps

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

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  • Total Questions: 100
  • Last Updation Date: 17-Feb-2025

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